Piers, congratulations on your appointment as the new CEO of The ai Corporation. Can you share your vision for leading the organization into the fuel and mobility payments sector?

Our vision at The ai Corporation (ai) is to revolutionise the retail fuel and mobility sector with secure, efficient, and seamless payment solutions while leading the charge against transaction fraud. ai delivers unparalleled payment convenience and security to fuel retailers and mobility service providers, enhancing the customer journey and safeguarding financial transactions. 

We believe in fuelling progress by simplifying transactions and powering every journey with trust and efficiency. In an era where mobility is a fundamental aspect of life, we strive to safeguard each transaction against fraud, giving our customers the freedom to move forward confidently. We achieve that by blending innovative technology and strategic partnerships and relentlessly focusing on customer experience: 

Seamless Integration: We’ve developed an advanced payment system tailored for the fuel and mobility sector. By embracing technologies like EMV and RFID, we ensure contactless, swift, and smooth transactions that meet our customers’ needs. Our systems are designed to be intuitive, providing easy adoption and enhancing the customer journey at every touchpoint.

Unmatched Security: Our robust fraud detection framework is powered by cutting-edge AI, meticulously analysing transaction patterns to identify and combat fraud pre-emptively. We’re committed to providing retailers with the knowledge and tools to protect themselves and their customers, fostering an environment where security and vigilance are paramount.

With the increasing demand for sustainable fuels and EV charging, how do you plan to address potential fraud and fraudulent data collection methods in unmanned EV charging stations?

The emergence of new and the continued growth of existing sustainable fuels means our experts are constantly identifying potential risks and methods of exploitation proactively. The increase in unmanned sites is particularly challenging as we observe a steady rise in fraudulent activity that is not identifiable within payment data, such as false QR code fraud. In these circumstances, our close relationships with our fuel retail customers enable us to utilise additional data to identify at-risk areas and potential points of compromise to assist in the early mitigation of fraudulent activity.

Mobile wallets are on the rise in fleet management. How do you navigate the balance between convenience for users and the potential risks of fraud and exploitation associated with these payment methods?

When introducing any new payment instruments, it is critical to balance the convenience of the new service with the potential risk it presents. As with all fraud prevention strategies, a close relationship with our customers is vital in underpinning a robust fraud strategy that mitigates exposures, while retaining the benefits and convenience mobile wallets offer. Understanding the key advantages a fleet management application brings to the end user is vital for understanding potential exposure and subsequent exploitation. That information enables us to utilise one or multiple fraud detection methods at our disposal to mitigate potentially fraudulent activity whilst balancing convenience and flexibility.

The trend of Abuse of Genuine fraud is noticeable despite advancements in mobile wallet payments. How do your AI-driven scoring systems combat this complex fraud type in the industry?

Our teams identify Abuse of Genuine fraud by using enhanced behavioural profiling across extended periods and utilising sector-specific data in full to enable us to create a detailed and accurate profile for both payment instruments and vehicles. Industry-specific data, for example, from fleet odometers, is exceptionally valuable when you are developing a behavioural profile for a specific vehicle. Combined with other methods, this enables us to quickly identify areas of increased spending or a change of spending profile. That insight is vital when identifying Abuse of genuine fraud, as this type of fraud is often perpetrated for long periods of time and in very high volumes.

Opportunistic fraud and overclaiming by legitimate customers can inflate fraudulent values. How can businesses enhance confidence in point-of-compromise identification and distinguish genuine customer behavior from fraudulent activity?

The short answer is that businesses need to ensure that they are working with experts who understand fraud and understand the impact that false positives can have on a fraud strategy. Incorrectly identified fraudulent transactions affect bottom-line losses and can severely harm a business fraud strategy and AI Scoring Systems. 

As a result, we firmly hold that visualising precise trend profiles and pinpointing potential compromise points are as critical as receiving the initial fraud alert. By combining industry-specific data with payment and transaction information, we can often clearly identify deviations from legitimate activities through proper visualisation. This forensic approach enhances our ability to understand and act on fraudulent behaviour effectively.

With the move to open-loop payment capabilities, what measures need to be taken to address the increased fraud and security risks associated with this wider acceptance payment instrument?

Robust security measures are crucial as open-loop payments gain traction in the fleet and mobility sectors:

• Multi-factor authentication, including biometrics, verifies user identity. 
• Machine learning analyzes transactions for suspicious patterns. 
• Encryption and tokenization protect sensitive data. 
• Fraud management systems monitor transactions and notify users of suspicious activity. 
• User and employee education on fraud tactics strengthen security. 
• Collaboration between payment providers allows for sharing best practices and adhering to industry regulations like PCI DSS, creating a secure payment environment. 

These efforts balance security with convenience to ensure safe user experiences.

Innovation is key in the fuel and mobility sectors. How does your technology contribute to fraud prevention while engaging directly with end-users, encouraging community growth, and promoting interaction with brands?

ai’s advanced technology has been developed to shield the fuel and mobility sectors from fraud. Our machine learning detects suspicious transactions, fake accounts, and identity theft in real-time, protecting businesses and helping them stay ahead of evolving fraudster tactics.

In addition to providing our users with a comprehensive rules management platform, our sophisticated fraud management solutions deploy machine learning to optimise rules in production, recommend new rules, and identify underperforming ones to remove. 

We model data in real time to enable probabilistic scoring or transactions to assess the likelihood they are fraudulent, allowing authorisation decisions to be taken in real-time to prevent fraud. By leveraging advanced algorithms and machine learning, our clients can stay ahead of fraudsters.

Our technology also ensures data quality by distinguishing deliberate fraud from genuine mistakes. This empowers businesses to make accurate fraud decisions. Additionally, our collaboration across industries strengthens the fight against fraud through shared solutions and regulations.

Beyond security, our technology fosters positive brand-consumer relationships – enabling our users to provide personalized experiences, loyalty programs, and feedback mechanisms to build a strong community with their customers.

Technology protects against fraud, ensures data reliability, and facilitates meaningful interactions between brands and their communities. By embracing innovation, businesses can safeguard operations while promoting growth and trust.

As vehicles become payment mechanisms, what security considerations and fraud prevention strategies should businesses adopt, especially in the context of innovations like integrating payment choices into vehicles?

As vehicles evolve into payment mechanisms, retailers need to put in place robust security measures and fraud prevention strategies to ensure the safety of financial transactions. Some payment security measures to consider include:

• Encryption – Employ robust encryption protocols to protect sensitive data during transmission and prevent unauthorized access.
• Tokenisation – replacing actual payment card details with tokens – unique identifiers that are useless to fraudsters even if intercepted.
• Secure communication channels – ensuring secure communication between vehicles and payment gateways to prevent/deter unauthorised use.
• Authentication – implementing multi-factor authentication to verify users’ identities will prevent the unauthorized use of payment instruments.
• Secure Hardware – consider using tamper-resistant hardware for payment processing within vehicles.

In terms of fraud prevention strategies, key considerations should include:

• Fraud detection systems – leveraging advanced machine learning algorithms to identify suspicious patterns and activities.
• Know Your Customer (KYC) – Deploy rigorous KYC practices to help verify user identities and prevent fraudulent transactions and account abuse.
• Regulatory compliance – adhering to industry standards and regulations to maintain a secure payment environment is a must, including PCI DSS compliance.
• Customer education – education of end users around safe payment practices and potential risks is the front line for fraud prevention.
• Behavioural analysis – monitoring user behaviour to detect anomalies – which can be enhanced and automated by using machine learning detection models.
• Real-time alerts – setting up real-time alerts to end users for unusual transactions or activities.
• Geolocation verification – validating the location of the transaction against the vehicle’s actual position.
• Device fingerprinting – creating unique fingerprints for each device to detect suspicious behaviour.

Businesses must adopt a holistic, layered approach that combines robust security practices, fraud prevention strategies, and regulatory compliance adherence to safeguard financial transactions while integrating payment choices into vehicles.

Tokenization is being considered to fight fraud. How do you approach this technology, considering potential regulatory requirements, and what implications do you foresee for PSD3?

Tokenization combats payment fraud by replacing sensitive data with meaningless tokens during transactions. This protects actual card details and can also be applied to other sensitive data.

New European regulations (PSD3) emphasize security and user privacy, aligning well with tokenization’s benefits. PSD3 is expected to tighten security measures further and encourage anti-fraud technologies.

While tokenization enhances security, regulations like PSD3 may not definitively address liability for fraudulent token transactions. As tokenization becomes more widespread, clear guidelines for such cases will be essential.

There is no doubt that tokenization is a powerful tool against fraud, but balancing security, innovation, and user rights will be essential for any robust payment ecosystem to comply with PSD3.

How do you foresee intelligent fuel management and predictive vehicle maintenance playing a role in fraud prevention and operational efficiency within the fuel and mobility sectors?

Intelligent fuel management and vehicle maintenance powered by AI are revolutionizing transportation. Businesses can optimise fuel usage, predict maintenance needs, and prevent fraud by analysing vast amounts of data, ultimately that translates to reduced costs, improved efficiency, and a more sustainable future.

Here’s how:

• AI optimises routes: Real-time traffic data helps choose the most efficient paths, saving fuel and time.
• Predicting demand patterns: Businesses can anticipate needs and strategise fuel management across different transportation modes, streamlining inventory control.
• Enhanced supply chain resilience: AI forecasts disruptions, identifies inefficiencies, and tracks inventory for better preparedness.
• Proactive vehicle maintenance: Sensor data helps detect potential problems before they become major breakdowns, reducing downtime and repair costs.
• Preventing fuel theft: In-vehicle sensors monitor fuel levels and detect unauthorised access, ensuring fuel security.

Intelligent fuel management and predictive maintenance create a win-win situation for businesses and the environment.

Piers Horak

Chief Executive Officer at The ai Corporation 

Piers Horak is Chief Executive Officer of The ai Corporation (ai). Horak brings over 15 years of extensive expertise in enterprise retail payments, banking, and fraud prevention. Horak is responsible for building on ai’s track record of developing innovative technology that allows its clients and their customers to take control and grow profitably by managing omnichannel payments and stopping fraud.

The post AITech Interview with Piers Horak, Chief Executive Officer at The ai Corporation first appeared on AI-Tech Park.

Hello Hussein, can you share with us your professional journey and how you became involved in the field of AI and technology, leading to your role as co-founder of Momentable?

I’ve always been fascinated with technology and sci-fi. AI is one of those things that sticks in your mind, and you can’t help but think about it. 

I studied engineering and worked in tech, and even with all the advancements in technology we have been witnessing in the past two decades, AI was one of those things that we always thought would remain a sci-fi pipe dream for a long time. 

This is not because there was nothing happening. But those who work in tech know it takes a while for the evolution of these technologies, and advancements are usually several degrees of separation from the regular user. 

I’m always learning, reading, and building tech products, so AI was a field of study; however, implementing it was never accessible for early-stage products. 

The status of AI has forever changed. OpenAI’s ChatGPT launch has had a remarkable impact on the field of AI and tech in general. AI is now available for regular users. People like me working in tech can now use AI in everything they are doing, which will accelerate product development and will impact the kind of products we can build and deliver to customers.

In addressing concerns surrounding AI ethics, you mentioned the importance of regulatory measures, technological transparency, and societal readiness. Could you elaborate on how Momentable approaches these areas to mitigate potential ethical dilemmas?

With great power comes great responsibility. AI is a powerful technology, and it’s very easy for those wielding it to amplify the impact of the good and the bad in the work they do. 

While we, in the tech space, are doing our very best to build great products that deliver great value, we are not social scientists, psychologists, or public servants. So, we can’t be expected to regulate and supervise ourselves, nor can we evaluate the impact of these technologies and the products using them on the individual and on society. 

It’s great when companies have values, codes of ethics, missions, and visions; however, those are not enough. Just like we do not rely on drivers to drive safely, we have traffic laws, signs, lights, and we make sure people driving a car are licensed and trained. We need to do the same with technologies, which, I would argue, have a massive impact on shaping our future as a species more than anything we’ve ever had in our history. 

At Momentable, we are acutely aware of the impact of generative AI on our stakeholders, artists, cultural organizations, and art lovers. We engaged our stakeholders, ran several experiments where generative AI created artworks with input from artists, with their permission and consent. 

In addition to using AI to enhance customer experience on our platform, we are using the learnings to evolve our product and introduce Generative AI in a thoughtful way that adds value and advances the art and culture space.

How do you personally strategize and prioritize addressing the ethical implications of AI within Momentable’s projects and initiatives?

We start by listening to our stakeholders; artists, art lovers, clients, and team. From simple Slack messages, to meetings with artists who are friends of Momentable, to talking to the experts, and sharing YouTube videos of leading content creators in the art space. 

By taking in the input, feedback, concerns, and advice, we make sure we are thoughtful about the next steps we plan to take. In addition to the data and numbers we get from market reports, we use the qualitative input we gather to help us focus on where we can add significance. 

We understand the AI conversation is ongoing, and as the industry keeps moving at rapid speed, we must stay engaged, always learning, and maintain an open attitude.

As someone deeply involved in the AI industry, what advice would you offer to our readers who are concerned about the ethical use and bias in AI technology?

 Ethical use and bias are not new to tech; it’s further amplified in AI, particularly generative AI. Three core reasons lead to challenges in ethical use and bias in generative AI: 

1. Products are developed by the tech sector, which deals with many ethical challenges and major bias due to the lack of diversity. These challenges are amplified by keeping the technology and products developed closed, which. 
2. The data used to train and develop the AI models also has many issues with how it was sourced, used, and also carries within it implicit bias. These issues are amplified even further since many AI models keep their. 
3. The nature of generative AI severely exacerbates these issues and challenges. By producing content mimicking the training data using code developed by a sector dealing with ethical challenges and bias, generative AI is adding to the problem with every answer it provides. 

Your ability to influence or mitigate the ethical use and bias in AI depends on where you are in the systemic hierarchy of the tech ecosystem. As a product builder and customer, there is very little you can do to change things.

The sector requires regulatory and systemic intervention. But it can’t be done without engaging with the stakeholders and having them at the table.

This is not to say that as a consumer you do not have any power; you do. You can make your voice heard through social media, customer feedback, calling your representatives, and voting.

I encourage you to learn and gain some hands-on experience to develop your understanding and appreciation for the technology and how powerful it is.

In your view, what role do education and skill development play in preparing society for the impact of AI, particularly in addressing job displacement and socio-economic challenges?

As technology continues to evolve and take over more of our roles at work as we know it today, the transformation will have massive implications on our lifestyles, how we do things, and even how we define ourselves and the value we assign to our roles.

We need to stop thinking about education as a precursor to job placement. This limited view meant that education is always lagging behind the needs of the economy and helplessly lacking in addressing any of the needs of our society.

Education must focus on the future beyond the jobs of today or tomorrow. It must graduate innovators and value creators. Education must focus on graduating creatives skilled at solving the problems we face 50-100 years from now.

To create a better world, schools and universities must become open spaces for research and discovery, where art, technology, and culture collide and fuse to inspire new thought forms.

Could you share some examples of how Momentable ensures transparency in its AI technologies, particularly regarding decision-making processes and algorithms?

We do everything in collaboration and coordination with our key stakeholders. This gives us a baseline to measure against.

It’s easy to be influenced by what we read and watch and think it’s an accurate representation of the world. To avoid the pitfalls of building on the learnings and understanding within our own bubble, we always start by expanding our perspective. Put simply, we talk to people.

It’s slow, inefficient, and important. If we are going to use technology to impact people’s lives, we better speak to those people, learn from them, understand their perspective, and take into consideration what matters to them.

This approach led us to experimenting with AI without limitations at the very beginning. We shared our results with our community: our users, partners, artists, and our advisors.

We wrote about our process and shared it through workshops and webinars, and we took on all the feedback we could gather.

While the inclination at the beginning was to keep things close to the chest, this open and transparent approach helped us focus on the areas where AI can add the most value in our work.

In the case of Momentable, we use AI to help us deliver the best user experience and make it easier, faster, and better for our users to use Momentable and capitalize on the democratized access to the largest collection of great art in the world.

Considering the rapid advancements in AI, how do you navigate the balance between innovation and the need for regulatory control within Momentable’s operations?

Until a clear regulatory framework is developed and introduced, like most companies, we continue to operate within the regulatory frameworks for the tech sector and business in North America and Europe.

At Momentable, we are governed by our internal ethical code and guided by our strong sense of mission to bring the best visual experience to customers through innovative software, personalization, and immersive storytelling.

With our stakeholders being engaged and involved throughout the process, we make sure we create a space for creativity and innovation with boundaries that keep our work focused on adding value with minimal negative impact on our stakeholders.

What steps do you believe are necessary for governments and regulatory bodies to effectively oversee AI development and ensure alignment with ethical and safety standards?

Bring all the stakeholders, industry players, academia, builders, users, communities, regulators, and the public to the table to collaborate and constructively build for the benefit of all.

Form a steering board and create a framework for engagement so that adding value to all stakeholders is a main condition.

Be clear and transparent about the objectives and outcomes you are after.

Develop a roadmap with realistic short-term goals and objectives, in addition to highlighting the mid-term and long-term areas of focus.

Maintain connection with stakeholders through regular roundtable meetings. Share regularly, and invite input, feedback, and criticism.

Keep moving forward and getting things done.

From your perspective, what are the most pressing ethical dilemmas or challenges currently facing the AI industry, and how can businesses and individuals contribute to addressing them?

The most pressing ethical dilemmas or challenges currently facing the AI industry can be viewed from three perspectives: long-term, mid-term, and short-term.

Long-term: AI is going to play a significant role in shaping who we are as a species and how we live our lives. Just like there are generations today that do not know a world without smartphones and the internet, we will have generations who do not know a world before AI, and we will have a generational gap and challenges that arise from this gap. Older generations will feel left behind, while new generations will be heavily dependent on AI and AI-enabled devices. The energy consumption will be extreme, and errors caused by AI will have massive ramifications, especially since AI will be embedded in essential services, infrastructure, and defense. In many ways, some might say we will be at the mercy of AI, and even if AI doesn’t become aware or evil, mistakes AI makes are possibly disastrous.

Mid-term: AI will cause massive socio-economic shifts that require offering support and help to those individuals and businesses impacted until the transformation is complete. Changes to the education sector are inevitable, and the evolution of our economy will have positive and negative implications that must be observed and prepared for. Focusing on the energy sector, making sure equitable, democratized, and open access to AI tools and training is crucial. New incubators, accelerators, resources, and support services must be made available to help manage the shift and protect society and the economy from the negative implications. As more people become proficient in using AI tools, they will be able to build massive businesses that compete with existing businesses, and just like smaller teams were able to disrupt businesses with software, now individuals can disrupt businesses with a few tools. Not to mention the malicious use of these tools can lead to even more challenges and threats.

Short-term: The immediate priority lies in creating spaces for engagement, learning, and hands-on experience with AI. It’s crucial to create an environment where individuals and businesses can understand, interact with, and ethically utilize AI technologies. This involves opening dialogues, providing educational resources, and encouraging ethical AI use through policy advocacy and community involvement. Businesses can lead by example, ensuring their AI applications adhere to ethical standards and are transparent in their operations, and share their learnings and discoveries. By actively participating in these efforts, we can navigate the complex and ever-changing terrain brought forth with the advancements in AI.

Finally, what are your thoughts on the future of AI and its potential to positively impact society, and do you have any closing remarks or key insights you’d like to share with our audience?

The future of AI holds remarkable potential for bettering every part of our lives. This technological evolution will accelerate advancements and enable breakthroughs in healthcare, climate science, education, and the sustainability of our species.

This optimistic vision is dependent on democratizing access, sharing openly, and ensuring there is transparency in how AI models work.

In addition, we must have an unwavering commitment to ethical principles, inclusivity, and equitable access to AI technology, prioritizing creating and delivering value to ensure all technological advancement, including AI, is a catalyst for positive change.

I invite you, the reader, to think of yourself as an active participant in this future being shaped today. Do not be a spectator; instead, take part, engage with AI, learn, build, and innovate. 

Now more than ever, the barriers to entry are minimal, and you can make an impact with less time, money, and resources. Embrace your roles as a shaper of the future, and engage with the world being created in front of our eyes with your thoughts, words, and actions for the greater good.

Hussein Hallak

Co-founder of Momentable

Hussein Hallak is the Founder and CEO of Next Decentrum, the launchpad for the world’s most iconic NFT products.  Heavily experienced in the art and technology fields, his recent roles include General Manager of Launch, one of North America’s top tech hubs and startup incubators, where he helped over 6500+ founders and 500+ startups raise over $1 billion. In 2019, Hussein joined 3 tier logic as VP of Products & Strategy and worked with some of the world’s most valuable brands including Universal Studios, P&G, and Kimberly Clark.

Hussein writes and speaks about startups, blockchain, and NFTs, and advises several blockchain and tech startups including Ami Pro, Gigr, Mobile Art School, Fintrux, Majik Bus, Traction Health, Cloud Nine, and Peace Geeks.  He was recognized in 2019 as one of 30 Vancouver tech thought-leaders and influencers to follow and has been featured in Forbes, BBC, BetaKit, Entrepreneur, DailyHive, Notable, and CBC.  When not building products, he enjoys writing, reading, and engaging in meaningful conversations over good coffee, and his favorite pastimes include playing chess with his kids, binging on good drama and science fiction, drawing, and learning new guitar licks, sometimes all at the same time.

The post AITech Interview with Hussein Hallak, Co-founder of Momentable first appeared on AI-Tech Park.

Table of contents:

1. What are data democratization and self-service analytics?
1.1 Empower Employees to Make Data-Driven Decisions:
1.2 Improve Operational Efficiency:
1.3 Gain Insights from Customer Data:
2. Affordable Self-Service Analytics Tools
2.1 Free and Open-Source Options
2.2 Cloud-Based Solutions with Freemium Tiers
2.3 Subscription-Based Tools with Budget-Friendly Options
3. Choosing the Right Tool for Your Business (Actionable Tips):
3.1 Identify Your Data Analysis Needs
3.2 Evaluate the Ease of Use
3.3 Scalability and Future Growth
3.4 Integrations with Existing Systems
4. Embracing Data-Driven Success on a Budget

Business in a dynamic environment no longer considers data a luxury; it’s the fuel that makes wise decisions and drives business success. Imagine real-time insights at your fingertips regarding your customers or the ability to identify operational inefficiencies buried in data sets. Be empowered to drive growth by making data-driven decisions that enable you to optimize marketing campaigns and personalize customer experiences.

However, unlocking this potential is where many of the SMBs struggle. Traditional data analytics solutions often come with fat price tags, thereby positioning themselves beyond companies with limited resources. But fear not! That doesn’t mean it has to be a barrier to entry into the exciting world of data-driven decision-making.

1. What are data democratization and self-service analytics?

Data democratization means extending access to organizational data to all employees, regardless of their technical nature. It essentially rests on the very foundation that the availability of data should be such that everybody in the entity can get access to information for making decisions and creating a culture that is transparent and collaborative in nature.

Self-service analytics involves tools and platforms that allow users to perform analysis on their own, outside the IT department. They are designed to be user-friendly enough for people in other functions within a company to generate reports, visualize trends, and extract insights on their own from any data they may want.

For small and medium-sized businesses, the benefits that come from data democratization and self-service analytics are huge:

1.1 Empower Employees to Make Data-Driven Decisions:

Arm workers at all levels with the ability to make more informed decisions that will have improved outcomes and innovative implications by providing them with relevant data and the proper tools with which to analyze it.

1.2 Improve Operational Efficiency:

Much of this IT bottleneck is removed through self-service analytics, improving operational efficiency and increasing decision-making at high speeds.

1.3 Gain Insights from Customer Data:

With data democratization, SMBs can get a closer look at customer behavior and preferences to ensure better customer experiences and focused marketing.

Basically, data democratization and self-service analytics democratize the power vested in data to drive efficiency, innovation, and growth within SMBs.

2. Affordable Self-Service Analytics Tools

2.1 Free and Open-Source Options

If the budget is a constraint, free and open-source options are just the place to start. Popular ones include Apache Spark and Google Data Studio. Apache Spark is a really powerful data processing engine that comes very cheap if the business can deal with the technical expertise required by it. On the other hand, Google Data Studio provides a user-friendly drag-and-drop interface for developing interactive dashboards and reports. In this respect, despite these tools above-mentioned having very affordable pricing, technical knowledge can be required to a certain extent sometimes, and that can pose a hindrance to certain companies.

2.2 Cloud-Based Solutions with Freemium Tiers

Those looking for a cost-to-ease-of-use ratio should investigate cloud-based solutions with freemium tiers. Very good examples are Google Data Studio and Tableau Public. They have limited functionality at no cost that could support small businesses. In these tools, the interfaces are user-friendly, and they can grow with a business. The free versions may have lower caps on data volume or advanced features; therefore, companies that are growing may need to upgrade to one of their paid offerings.

2.3 Subscription-Based Tools with Budget-Friendly Options

The subscription-based tools will provide all the features at nominal rates for small and medium-scale businesses. Notable tools that fall into this category are Power BI Desktop and Zoho Analytics. Power BI Desktop provides a drag-and-drop interface along with various different kinds of pre-built dashboards to help meet the specific needs of small and medium businesses. Zoho Analytics offers the same kind of benefits with industry-specific templates and strong data visualization. Not only are these tools budget-friendly, but they also give businesses the scalability to upgrade without any hiccups if their analytics needs grow.

The right self-service analytics tool would be one that aligns with the requirements and resources available to a business. Enterprises can tap into cost-effective or freemium options, then scale up as needed to truly reap the rewards of data democratization, all without truly breaking the bank.

3. Choosing the Right Tool for Your Business (Actionable Tips):

3.1 Identify Your Data Analysis Needs

This means you first need to specify exactly which data will be analyzed and what kind of insights are supposed to be extracted. Are you looking at customer behavior, sales trends, or operational efficiency? Knowing what you want to do will limit the options to only those tools that really fit your business needs.

3.2 Evaluate the Ease of Use

This is most critical when a business lacks technical expertise within its ranks. Ensure it has an intuitive user interface, featuring easy navigation. You want to empower your team with the ability to generate insights with minimal intervention from information technology experts.

3.3 Scalability and Future Growth

Choose a tool that will satisfy not only your immediate needs but also scale with your business. Make sure that the tooling can handle increasing volumes and more complex analysis over time. Having such foresight will keep you away from the pains of changing tools in view of the increasing demands on your data.

3.4 Integrations with Existing Systems

Integrate one that will be easy with the running tools, such as CRM, ERP, or marketing automation software. This type of integration enables smooth data flow between platforms and aids in enhancing efficiency while providing a holistic view of business operations.

Equipped with these factors, you can now select an inexpensive and powerful self-service analytics tool to drive data democratization within your organization.

4. Embracing Data-Driven Success on a Budget

Data democratization and self-service analytics are how businesses should drive decisions with insight without outrageously high costs. By using cost-effective tools and rigorously choosing the right solution to meet your unique needs, you will gain valuable insights, drive operational efficiency, and foster a culture of innovation within your organization. These strategies unleash the power of data for any business to drive growth and gain a competitive advantage. With the right approach, any business—regardless of budget—can drive business forward with data-driven decision-making.

Explore AITechPark for top AI, IoT, Cybersecurity advancements, And amplify your reach through guest posts and link collaboration.

The post Data Democratization on a Budget: Affordable Self-Service Analytics Tools for Businesses first appeared on AI-Tech Park.

1. Raj, please share key insights into your role as the Founder and CEO of Techwave and your journey contributing to its rapid growth.

As the Founder and CEO of Techwave, my journey has been one of relentless pursuit of excellence and innovation. Steering Techwave from its inception to becoming a global leader in digital transformation services has been both challenging and rewarding. My role has demanded a visionary outlook to foresee industry trends, a strategic mindset to navigate market dynamics, and a people-first approach to leadership. This trifecta has been crucial in contributing to Techwave’s rapid growth. We’ve expanded our global footprint, diversified our service offerings, and nurtured a culture that champions innovation, inclusivity, empathy, and continuous learning. My leadership philosophy has always been about empowering our teams, fostering a collaborative environment, and placing our clients at the center of everything we do.

2. What notable accomplishments has Techwave achieved under your leadership, particularly in terms of expansion, capitalization, and employee engagement initiatives?

Under my stewardship, Techwave has achieved remarkable growth, a testament to our innovative solutions, customer-centric approach, and the dedication of our global workforce. We’ve significantly expanded our presence, now operating with a prominence presence in 11 countries across the globe and serving a diverse client base across industries. Our workforce has grown to over 3000 associates, a reflection of our robust expansion and capitalization strategies.

Our employee engagement initiatives, particularly the SPARK framework, underscore our commitment to creating a vibrant and inclusive work culture. This framework focuses on engaging employees, fostering community engagement, and promoting diversity, which has significantly contributed to our high levels of employee satisfaction and retention.

Our corporate social responsibility efforts, like supporting the Houston Food Bank and participating in Primiethon – The Hope Run, reflect our commitment to making a positive impact in the communities we serve. These initiatives, alongside our accolades such as Asia’s Best Employer Brand Award and the President’s Volunteer Service Award, highlight our achievements in fostering a culture of excellence and community service.

3. How has Techwave positioned itself to stay ahead in a competitive digital landscape?

In a rapidly evolving digital landscape, staying ahead requires agility, foresight, and a commitment to innovation. At Techwave, we’ve positioned ourselves at the forefront of digital transformation by continuously investing in emerging technologies and nurturing a culture that embraces change. Our R&D efforts are focused on leveraging AI, machine learning, cloud-native technologies, and blockchain to develop solutions that address our clients’ most complex challenges of today and tomorrow.

We prioritize understanding our clients’ unique needs and market dynamics, which enables us to tailor our solutions for maximum impact. Our approach to innovation is not just about adopting new technologies but integrating them in ways that redefine business processes, enhance customer experiences, and drive sustainable growth.

4. Could you highlight Techwave’s approach to trending topics such as Platform Engineering, Cross Border Payments, and Artificial Intelligence Modelling Language?

Our approach to platform engineering, cross-border payments, and AI modelling language is rooted in our deep industry knowledge and technical expertise. In platform engineering, we focus on building scalable and resilient systems that support our clients’ business strategies. For cross-border payments, we leverage blockchain and other fintech innovations to offer secure, efficient, and compliant solutions. In AI, we’re pushing the boundaries of what’s possible with advanced modelling techniques that enhance decision-making and operational efficiencies for our clients.

These areas are critical to our mission of delivering comprehensive digital transformation solutions. By focusing on these domains, we ensure that our clients are well-equipped to navigate the complexities of the digital economy.

5. What are the essential core components for a successful omni-channel strategy, and how do they contribute to an integrated customer experience across channels?

A successful omni-channel strategy hinges on seamless integration, personalization, and real-time engagement. At Techwave, we understand that an integrated customer experience across all channels is paramount. We leverage data analytics and AI to gain insights into customer behaviors and preferences, which allows us to deliver personalized experiences. Our technology stack, designed for agility and scalability, supports the seamless integration of various channels, ensuring that our clients can offer their customers a cohesive and engaging experience.

6. How does technology play a critical role in ensuring a seamless digital customer experience through omnichannel integration at Techwave?

Technology is the cornerstone of creating a seamless digital customer experience. At Techwave, we use a combination of cloud computing, AI, and machine learning to ensure that all customer touchpoints are integrated, providing a unified and personalized customer journey. Our investments in technology enable us to automate processes, analyze vast amounts of data, and deliver insights that drive better customer engagement and loyalty.

7. What challenges do businesses typically face during the implementation of omnichannel strategies, and what effective solutions and best practices has Techwave adopted?

Implementing an omni-channel strategy comes with its set of challenges, including data silos, platform integration, and maintaining a consistent brand experience. At Techwave, we tackle these challenges head-on by employing a holistic approach that includes robust data management practices, leveraging cloud-native technologies for flexibility and scalability, and adopting a customer-centric mindset that informs all our strategic decisions.

8. Can you provide insights into how Techwave navigates the complex landscape of Cross Border Payments and its approach to ensuring success in this area?

The complexity of cross-border payments requires a nuanced approach that balances efficiency, compliance, and security. At Techwave, we employ the latest in fintech innovations, including blockchain, to streamline the process while ensuring adherence to global regulatory standards. Our expertise in financial technologies enables us to design payment solutions that are not only secure but also enhance the customer experience by reducing transaction times and costs.

9. In terms of Enterprise Digital Services, how does Techwave drive innovation in a competitive climate, combining technical knowledge and breakthrough analytics?

Innovation is at the heart of Techwave’s strategy for enterprise digital services. We combine our deep technical knowledge with insights from data analytics to develop solutions that anticipate market trends and meet our clients’ evolving needs. Our commitment to R&D, along with a culture that encourages experimentation and learning, allows us to stay ahead of the curve and deliver cutting-edge solutions that drive value for our clients.

10. What emerging trends and innovations do you anticipate in the digital customer experience and omnichannel integration, and how is Techwave preparing to adopt them proactively?

The future of digital customer experience is likely to be shaped by advances in AI, augmented reality, IoT, and other emerging technologies. At Techwave, we are actively exploring these technologies to understand how they can enhance the omni-channel experience. We are particularly focused on how AI and machine learning can further personalize customer interactions, making them more engaging and effective. Our proactive approach to adopting these technologies ensures that we are ready to integrate them into our solutions, keeping our clients ahead in a rapidly changing digital landscape.

In conclusion, as we navigate the ever-evolving digital landscape, our commitment at Techwave remains unwavering: to deliver innovative solutions that drive growth, enhance customer experiences, and contribute positively to our communities. Our achievements and our approach to the future reflect our dedication to being a leader in digital transformation, poised to meet the challenges and opportunities of the digital age. With focus on employee well-being, community service, and continuous learning underscores my vision for Techwave to be a leader not just in technology, but in creating a sustainable and inclusive future.

Raj Gummadapu

Co-Founder and Chief Executive Officer at Techwave

Co-Founder and Chief Executive Officer, Techwave Raj Gummadapu is a visionary enterprise transformation leader with over 20 years of experience in the IT & engineering solutions business. With his inherent dynamism and deep people-first approach to work, Raj has been instrumental in leading Techwave’s expansion and diversifying its strength across multiple growth avenues.

He has been instrumental in inculcating a strong client focus and developing various business solutions that would enable organizations to harness the potential of a data-driven, digital future. He is strongly motivated by his desire to make digitalization accessible to enterprises across the world and empower them with powerful, secure and affordable tech solutions.

As the Chief Executive Officer of Techwave, Raj has been enabling Techwave to rise as a leading global digital transformation partner by expanding its robust service offerings, delivery strength and customer-focused innovation. He has played an instrumental role in laying the foundation of Techwave’s client-driven approach to business and fostered a culture of diversity and learning in the company. Previously, he has held key leadership positions in companies like Sysco & Deloitte and has led the charge for Business Intelligence and Performance Management Practices. Raj has earned his Bachelor of Commerce from the prestigious Osmania University in Hyderabad, India. He then went on to become a Chartered Accountant with the premier Institute of Chartered Accountants of India (ICAI) and holds the title of a Certified Public Accountant (CPA). With his strong finance background, Raj seamlessly infuses his business acumen and multidisciplinary thinking to develop holistic solutions for customers and partners at large.

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Jim, as the CEO of Conversica, a leading AI provider for sales and marketing revenue teams, how do you see personalization and recommendations playing a crucial role in enhancing customer experience during their shopping journeys?

At Conversica, we understand the importance of personalization and recommendations in improving the customer experience during any and all shopping journeys. Leveraging AI-driven personalization allows us to tailor interactions based on individual preferences,
creating targeted and relevant experiences. However, BE AWARE. One of the main concerns with AI for retail is the intrusion of privacy. Customers might perceive generative AI and similar as being too intrusive, especially since it collects data over time to monitor purchasing behaviors and make product recommendations.
Our recommendation engines, powered by AI, analyze customer behavior and history to suggest products aligned with their interests, streamlining the shopping process and increasing engagement. We leverage partner AI technologies, like Salesforce Einstein as well. Where there are many choices, our commitment is to provide Conversational AI tools that not only automate processes but also elevate the overall customer experience, making the shopping journey more enjoyable and efficient for each individual customer. BUT, we do so, with a privacy-first approach.

Chatbots have become integral in customer service. Could you share insights on the impact of chatbots in improving customer interactions and support, especially in the context of sales and marketing during the recent holiday season?

Chatbots have become vital in revolutionizing customer interactions, particularly in the realms of sales and marketing, and especially during the holiday seasons. At Conversica, we’ve witnessed the transformative impact of chatbots in enhancing customer support with simple FAQ – frequently asked questions. By deploying AI-driven chatbots, we enable real-time engagement, providing instant responses to customer queries. In our case, our focus is to guide customers through the sales process efficiently. This not only improves responsiveness but also ensures a seamless and personalized experience, crucial during the high-demand holiday season. Chatbots excelin handling repetitive tasks, allowing human agents to focus on complex inquiries – more than just FAQ but rather the infrequent questions. The result is increased efficiency, improved customer satisfaction, and ultimately, a more successful sales and marketing strategy during the shopping rush. Conversica is dedicated to harnessing the power of chatbots to elevate customer interactions, making the shopping seasons a smoother and more enjoyable experience for both businesses and their customers.

With the increasing reliance on AI in the sales and marketing domain, how does Conversica address the concerns related to security and privacy, ensuring that customer data is handled responsibly and securely?

Compliance, Data Security, Privacy, and Transparency are core tenants. Our AI use cases are certified for SOC 2 Type II, ISO 27001, CCPA, COPPA, GDPR, PCI-DSS, and HIPAA/HITECH. Conversica recognizes and shares the excitement over current and potential uses of AI as well as the concerns regarding how and for what purposes AI is and may be used and the resulting consequences. Because our clients and their customers share these concerns, we have provided Conversica’s Responsible Use of AI policies. As a veteran of AI for over 15 years, we know that it’s a must to prioritize the security and privacy of customer data in our AI-driven sales and marketing solutions. We have implemented, for example, strong encryption, access controls, and authentication measures to protect data during storage and transmission. Complying with regulations and following industry best practices, we ensure responsible and transparent handling of customer information. Our commitment is to maintain high standards of security and privacy, allowing businesses to leverage AI benefits confidently and responsibly.

Navigating AI-driven sales can be a challenge for some businesses. What strategies or best practices would you recommend for sales and marketing teams to effectively integrate and leverage AI in their operations during peak shopping seasons?

Navigating AI-driven sales during peak shopping seasons can be challenging, but adopting effective strategies is key. Firstly, it’s crucial to align AI tools with specific business goals, identifying areas where automation can enhance efficiency in order to increase lead generation, improve discovery of products and services, or boost sales conversions.
Training teams on AI usage and fostering a culture of collaboration between AI and human agents is essential. Utilizing AI for data analysis can provide valuable insights to segment your customer base effectively. This allows for more targeted campaigns and messaging, improving engagement and conversion rates. Use AI to analyze customer data and behavior, enabling personalized communication. This could mean tailored product recommendations or customized messaging based on past interactions. AI can help automate the lead scoring process, identifying and prioritizing leads based on their likelihood to convert. This ensures your team focuses on the most promising prospects
during high-volume periods. Additionally, employing conversation automation for real-time customer engagement during peak seasons helps manage increased demand.

What future trends do you foresee in AI for e-commerce? How do you anticipate technology advancements shaping the landscape of sales and marketing processes on online platforms?

In the future of AI for e-commerce, expect more personalized experiences, improved recommendation engines, and advanced chatbots that will be referred to as digital concierges. AI analytics will provide deeper insights into customer behavior, and innovations like voice-activated commerce and visual search or augmented reality shopping will become prominent. These advancements will enhance efficiency and reshape the landscape of online sales and marketing processes.

Personalization is often a key factor in successful marketing campaigns. Can you provide examples or case studies where Conversica’s AI solutions have significantly contributed to personalized and effective marketing strategies?

Conversica’s AI has proven effective in personalized marketing. For instance, our AI assistants engage leads in natural conversations, boosting engagement and conversions resulting in a 24x ROI across the entire network. Conversion rates improve by an order of magnitude, increasing opportunities at every point in the funnel. The AI analytics help businesses analyze customer data for targeted campaigns, while chatbots provide real-time support, enhancing customer satisfaction. These examples showcase how Conversica’s AI contributes to personalized and successful marketing strategies.

With chatbots and customer service on the rise, how does Conversica ensure that its AI solutions are adaptive and responsive to the evolving needs and preferences of consumers in the fast-paced e-commerce environment?

Conversica keeps its AI solutions adaptable by staying tuned to consumer trends, and leveraging the latest in AI technology. We regularly update and improve our chatbots based on feedback and customer interactions, ensuring they remain responsive to the evolving needs and preferences in the fast-paced e-commerce environment. Core technologies, such as GPT 4.0, are leveraged to ensure the most human-like experience.

As AI continues to evolve, how do you envision the future collaboration between AI technologies and human teams in sales and marketing? What role do you see for AI in enhancing the productivity and creativity of human professionals?

Marketing teams produce more high-quality leads to their sales counterparts, getting more for their dollar, ultimately reducing the cost per lead and cost per customer. Sales
teams close more business faster. Both of these are a function of simply being able to focus on more high quality opportunities produced via AI automation.
As AI continues to evolve, the future collaboration between AI technologies and human teams in sales and marketing is poised to be synergistic. AI will take on routine tasks, allowing human professionals to focus on more complex and creative aspects of their roles. People will naturally have to reskill themselves for more high-value activities. People won’t be replaced by AI, but duties and in some cases entire roles will.
AI-driven analytics will provide valuable insights, aiding human teams in making informed decisions and crafting targeted strategies. The combination of AI’s efficiency in data processing and human creativity will lead to more innovative and effective marketing campaigns. Overall, AI is expected to enhance productivity by automating repetitive tasks and augment creativity by providing data-driven insights, fostering a collaborative and dynamic relationsahip between AI and human professionals in sales and marketing.

Considering the diverse nature of e-commerce platforms, how does Conversica tailor its AI solutions to cater to different industries and markets? Are there specific challenges or opportunities that arise in customizing AI for various business domains?

E-commerce involves buying and selling without the sales person. The holy grail is for the e-commerce experience to involve a digital concierge which removes friction anywhere and everywhere in the digital journey.
Conversica tailors its AI solutions to suit diverse e-commerce platforms by understanding the unique needs of different industries. We customize our AI conversations to leverage specific business domain data, addressing the challenges and opportunities each industry presents. This process requires a careful understanding of market nuances to ensure effective customization. Our goal is to provide tailored AI solutions that meet industry-specific requirements and unlock revenue opportunities for businesses in various domains.

Could you share any success stories or notable examples where Conversica’s AI solutions have made a significant impact on the performance and outcomes of sales and marketing campaigns for businesses?

Conversica’s collaboration with KEMP Technologies resulted in generating over $100,000 of opportunities within a month. But what is important for all marketers to understand is that for every AI automation dollar spent, 48 dollars in revenue are produced. When you take both revenue and people cost savings into account AI automation can deliver a 50x ROI (that’s an order of magnitude more than your typical Marketing ROI target). KEMP Marketing initiated the exploration by deploying
Conversica’s AI Assistant, Olivia, to engage with incoming leads, especially those from their ‘freemium’ product’s dedicated website. The freemium product attracted many users for trial purposes, and Conversica became the first point of contact for these leads. Additionally, Olivia was utilized to reconnect with older and inactive leads, providing a means to reengage with prospects and customers who had longer-term projects. This approach proved effective in situations where individuals initially showed basic interest on the website but did not directly engage with KEMP, either due to lower project priority or to explore other options first.

Jim Kaskade

CEO of Conversica

Jim currently leads Conversica, a PE-backed category creator and leader in AI-enabled augmented workforce solutions. Prior, he led Janrain, PE-backed category creator of Consumer Identity & Access Management (CIAM) & acquired by Akamai.

Prior to this Jim led CSC’s (now DXC’s) newly formed Digital Applications business in the Americas, a team of over 7K. The convergence of disruptive technologies such as analytics, mobile, cloud & cyber security were leveraged to help clients become digital businesses. Prior to this, he led CSC’s global Big Data & Analytics (BD&A) business unit, CSC’s fastest growing business of over 1K.

As a senior executive/CEO, Jim Kaskade has built companies in Big Data, Cloud Computing, Software as a Service (SaaS), Online & Mobile Digital Media, Advertising, & Semiconductors. He has also spent 10+ years in leadership roles developing enterprise data warehousing, data mining, and business intelligence solutions.

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The rise of Generative AI (GenAI) has enormous potential for the banking and finance industries. By utilizing GenAI, banks and credit unions speed applications from submission to approval, save time and effort, and deliver a desirable customer experience.

A recent report from the Society for Human Resource Management (SHRM) and The Burning Glass Institute details how GenAI will have an outsized role on the banking and finance industries. The report lists Morgan Stanley, Bank of America and Northwest Mutual as some of the organizations that are most likely to capitalize on the implementation of GenAI. Their study also measures GenAI exposure among several different professional industries; “investment banking and securities dealing and brokerage” measured third highest while “mortgage and nonmortgage loan brokers” ranked highest overall. If SHRM and The Burning Glass Institute are so convinced that GenAI will profoundly alter how financial institutions operate, what will that change look like and why does it matter?

GenAI is distinct from other forms of automation by its ability to automate what is typically considered knowledge work. This represents a sea change in how professional industries, including financial services, will implement automation technology in their workplaces. In fact, financial services are especially dependent on repetitive manual processes requiring specialized knowledge. Processes like loan underwriting and credit card applications require knowledge workers to manually input data and individually connect with customers or members, which takes up the majority of workers’ time and tasks.  GenAI excels in automating repetitive, manual tasks—such as data processing and pattern identification—streamlining operations and freeing up valuable time for knowledge workers.

The applications of GenAI within financial services manifest in both evident and nuanced ways, each offering distinct advantages to forward-thinking institutions. Many industries have begun employing GenAI solutions as chatbots for customer service, and financial services are no exception. GenAI-powered chatbots, operational around the clock, offer an immediate response to customer inquiries, significantly reducing the need for direct intervention by skilled professionals and enhancing service efficiency.  However, these solutions become even more compelling for financial institutions when embedded in the bank or credit union’s broader systems. For example, a loan applicant can interact with a GenAI-enabled chatbot and get a real-time status update on their loan status by providing a few identifying details. In this way, GenAI increases efficiency while also directly improving the customer or member experience.

As lending processes are vitally important to any bank or credit union, they are also ripe for GenAI enhancement. Much of lending involves knowledge workers reaching out to customers and acquiring all the documents and data necessary to complete the loan application. This can be a tedious process that can take days or weeks to complete. With GenAI solutions, not only can financial institutions instantly reach out to applicants requesting documents, but those same solutions can also automatically identify all necessary documents by analyzing the application status without a human ever laying eyes on it. Some tools can even go one step further by identifying the document category, extracting data from the documents and validating them against the loan application instantly. Imagine your own knowledge worker advancing loan processing overnight and over the weekend!

Additional GenAI solutions go beyond immediate revenue-generating processes for bank and credit unions. These tools can assist with marketing efforts by creating personalized offers based on account information. GenAI-enabled marketing tools can detect patterns in account behavior and automatically generate personalized offers based on customer preferences. Just like with lending processes, GenAI tools can then automatically reach out to customers and members via email, SMS or other communication channels. These marketing efforts again increase efficiency, improve the customer or member experience and create more lending opportunities.

GenAI’s distinctive ability to automate professional tasks, particularly in the realm of financial services, where repetitive manual processes dominate, is reshaping traditional workflows. The adoption of GenAI solutions, from chatbots enhancing customer service to automating lending and revolutionizing marketing efforts, signifies a paradigm shift towards efficiency, improved customer experiences and increased lending opportunities. 

GenAI technology is novel, and its implementations are sure to evolve further in the coming months and years. However, its potential for financial services is undeniable. In order for banks and credit unions to take full advantage of this nascent technology, financial institutions need to create AI policies, complete digital transitions and start exploring and investing in GenAI use cases now. 

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Table of Contents
Introduction
1. The Technology Behind Spatial Computing
2. The Area of Applications of Spatial Computing
2.1. Logistics and Supply Chain Optimization
2.2. Augmented Reality in Manufacturing
2.3. Smart Buildings and Facility Management
2.4. Urban Planning and Construction
3. Conclusion

Introduction

In the digital era, spatial computing (SC) is a rapidly evolving field as we have started to interact with humans and machines in three-dimensional spaces. Technologies under this umbrella, including augmented reality (AR) and virtual reality (VR), can redefine the enterprise’s interaction with these gadgets and unlock a new realm of possibilities and opportunities.

Today, spatial computing is no longer a vision but a reality for finding the correct applications in numerous fields, especially in the business world. 

In this AI Tech Park article, we will take a closer look at how spatial computing is the new solution for IT professionals who are looking to improve their data analysis and process optimization.

1. The Technology Behind Spatial Computing

Spatial computing has emerged as an interactive technology that can merge the digital and physical worlds, allowing users to interact with computers in an immersive and seamless manner. 

With the help of a wide range of technologies, such as artificial intelligence (AI), camera sensors, computer vision, the Internet of Things (IoT), AR, VR, and mixed reality (MR), IT professionals can develop new technologies, a seamless business process, and better data analysis to optimize the process. 

This technology employs numerous devices and hardware components to provide an interactive customer experience. A few well-known devices in the business world are smart glasses such as Apple Vision Pro and Meta Quest 3, which interface virtual objects with the real world. 

Another interactive spatial computing technology is the depth camera by Microsoft Azure Kinect and the Intel RealSense D400 series, which captures the depth of the physical world and creates virtual objects that will fit into the real world. 

Spatial computing leverages numerous technologies, such as machine learning (ML), advanced sensors, and computer vision, to understand and interact with the physical world. 

Computer vision, also a subset of AI, enables computers to process and understand visual information by tracking users’ movements and understanding the environment. This allows IT professionals to create a digital representation of the physical world, which can be further used to overlay digital content onto the real world.

ML is another key technology in spatial computing that IT professionals use to train computers to understand and predict user behavior. For instance, if the user reaches to touch a digital object, the computer needs to understand this information and take action to respond accordingly and further predict the user’s future actions. 

Sensors are also an essential component of spatial technology as they provide the data that the computer needs in the physical world, which includes the user’s behavior, environment, and interaction with digital content.

2. The Area of Applications of Spatial Computing

At the business level, spatial computing technology enables machines to collect information about the physical environment and gather data on the movements and behavior of employees working in their workspace.

2.1. Logistics and Supply Chain Optimization

B2B logistics and supply chain companies often use spatial computing technologies to improve the flow of raw materials and goods in their supply chains. The machines have built-in location data sensors, real-time analytics, and sensors to track shipments, efficiently manage inventory, and optimize routes.  

2.2. Augmented Reality in Manufacturing

In the manufacturing industry, spatial computing is used to employ AR technology for the production process, where employees can use AR glasses to receive digital instruction and real-time visual aids that will guide them. The implementation of AR has proven to be quite efficient and has reduced the error of miscalculation in purchase, distribution, and installation by 62%. 

2.3. Smart Buildings and Facility Management

The implementation of spatial computing is to create smart buildings that automatically optimize resources such as air conditioners, lights, heating, or any other gadgets that are linked with this technology. The integration of advanced sensors and data analytics allows electronics and technology companies to improve users’ energy consumption and reduce companies’ operational costs as they adhere to environmental responsibility laws and regulations. 

2.4. Urban Planning and Construction 

In the field of architecture and construction, numerous developing and developed cities are using spatial computing to plan and optimize urban spaces. With spatial computing capabilities, especially with mixed reality headsets, architects and civil engineers can design buildings through 3D models. Further, they can analyze the traffic flows, neighboring infrastructure, and demographic data to develop an informed decision to address traffic and water issues and promote sustainable development. 

3. Conclusion

Spatial computing is indeed considered the future of technology, as it has the potential to revolutionize any industry by enabling human interaction with machines and the environment. This innovative blend of the virtual and physical worlds provides immersive experiences and boosts productivity. At its core, spatial computing integrates MR, VR, and AR to bridge the gap between the real world and the digital realm, which helps shape the future of technology.

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Table of Contents

Introduction
1. The Evolution of Data Literacy in the Technological Era
2. Establishing a Data Literacy Program
Wrapping Up

Introduction

As we have entered the digital era, data and analytics strategies (D&A) have become important, as these technologies can transform any business during a massive data spike. According to global research, it was observed that around 2.5 quintillion bytes of data are produced by IT companies every day; therefore, to understand the importance of data, every employee must be data literate.

For a better understanding of data, the Chief Data Officers (CDOs) play an important role in making every employee data literate, i.e., able to understand, share, and have meaningful insight into data.  

With this mindset, organizations can seamlessly adopt emerging and existing technologies and transform their business outcomes across all departments while fostering quality decision-making, innovation, and a better customer experience. The CDOs 

In this exclusive AI TechPark article, we will discuss the evolution of data literacy and how it can transform any organization into a data-literate one.

Read more about The Value of the Chief Data Officer in the Data Governance Framework 

1. The Evolution of Data Literacy in the Technological Era

In the past few decades, data literacy has experienced a significant transformation with the introduction of new technologies and the explosion of data. This shift has ignited from traditional data analysis to a modern era of big data that has redefined the way organizations can make data-driven decisions. 

To analyze data, data scientists and analysts were confined to basic statistics and simple datasets. Even to analyze the data, data professionals needed more tools, narrow, small-scale datasets, and internal data sources. However, in the late 20th century, there were a lot of technological advancements, such as the introduction of data storage, big data, and cloud computing. This helped data scientists collect and process massive amounts of data from complex, unstructured datasets that could be further analyzed for deeper insight.

Read more about Navigating the Future With the Integration of Deep Learning in Big Data Analytics 

As a result of these technological advancements, the power of data has become a center point for developing strategic planning and seamlessly operating business efficiency in the IT industry. Thus, data literacy becomes equally important to developing a data-literate workforce and ensuring that professionals harness the full potential of data for competitive advantage in the data-driven landscape.

2. Establishing a Data Literacy Program

To achieve the goal of robust D&A strategies, the CDOs need to address the existing skill gaps among each employee by rolling out data literacy training programs. These programs can help every employee who is handling data daily by developing D&A skills and acquiring knowledge on data literacy as a part of organizational culture.

Before initiating the programs, CDOs should look for speakers who are data analysts, data stewards, and architects, as they can be the right people to speak about data naturally and effortlessly. 

Secondly, CDOs must interact with the employees to understand communication barriers and conduct data literacy assessments to identify the gaps and encourage employees to work on them. 

Employees who are not aware of the subject matter often find it tedious to understand; therefore, it is essential to develop an open environment of fun and games to teach about data.

Finally, CDOs must arrange a data literacy proof-of-concept workshop where participants can describe real-life common use cases, which can be a lesson for every employee to raise awareness and understand the data literacy gaps. The data teams can also hold biweekly meetings and discussions with the participants and provide them with the KPIs they need to work on. 

With this approach, CDOs can eliminate the data literacy gap and generate better methods of data analysis without being biased. 

Read more about Modernizing Data Management with Data Fabric Architecture 

Wrapping Up

Data is necessary, empowering at both individual and organizational levels by creating a pathway to harness real-world data-driven decision-making and data-driven organizational strategy. 

In an era where artificial intelligence, data analysis, machine learning, and big data are driving critical business decisions and the ability to steer through complex datasets and extract business insights, data literacy is the epitome of enhancing employability, making informed business decisions, driving innovation, and gaining a competitive edge.

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Neda, please share some key milestones and experiences from your professional journey that have shaped your perspective and approach as Chief Product Officer at Stibo Systems.

I have the honor of mentoring a couple of young leaders, and they ask this question a lot. The answer I always give is that I approach each day as an opportunity to learn, so it’s difficult to pinpoint a specific milestone. However, there have been some crucible moments where I made radical decisions, and I think those moments have influenced my journey. One of them was my shift towards computer science. Despite having a background in linguistics and initially aspiring to be a teacher, I took a complete shift and decided to explore computer science. Programming was initially intimidating for me, and I had always tried to avoid math throughout my student life. I saw myself more as an art and literature person, and that gutsy shift turned out to be a great decision in the long term. The decision was made by me, but it wouldn’t have turned into a success without support from my mentors and leaders – it’s super important to have champions around you to guide you, especially early in your career. 

Another significant moment was when I accepted a consulting job that involved phasing out legacy systems. This required negotiating with users who would lose functionalities they had been using for years. These conversations were often challenging, and I was tempted to quit. However, I made the decision to stay and tackle the problem with a more compassionate approach towards the application users. It was during this time that I truly understood the nature of change management in the product development process. People find it difficult to let go of their routines and what has made them successful. The more successful users are with their apps, the less likely they are to embrace change. However, sometimes solutions become outdated and need to be replaced – plain and simple. The challenge is how to build a changing product while ensuring that users come along. This story applies to Stibo Systems. We have been around for over 100 years and have managed to transform our business. Stibo Systems is a perfect example of how to build lasting products, be open to change and transformation and make sure you aren’t leaving any customers behind.

Could you provide an overview of Stibo Systems’ mission and how it aligns with the concept of “better data, better business, better world”?

Our heritage extends far back, but we are a cutting-edge technology company. We specialize in delivering data management products that empower companies to make informed decisions, resulting in remarkable outcomes. This approach not only contributes to our sustainable growth but also supports our profitability, allowing us to reinvest and expand.

Our mission statement encapsulates our business ethos – one with a strong sense of conscientiousness. Our primary focus revolves around doing what’s right for our customers, employees and the environment. Customer satisfaction is at the forefront of our priorities, evident in our high software license renewal rates, a testament to our commitment to delivering top-notch products and services.

Moreover, we hold a unique position in the market as one of the few major companies headquartered in Europe. Europe is facing increasing pressure to embrace sustainable practices, and we are actively engaged in leading this transformation. Our commitment extends to reducing our environmental footprint while leveraging our tools to assist large-scale customers in sectors such as retail, manufacturing and consumer packaged goods (CPG) in monitoring and sharing sustainability data. Through these efforts, our aim is to contribute to the creation of a better world.

Better Data

What specific strategies does Stibo Systems employ in acquiring and managing data to ensure it meets the requirements of today and tomorrow?

Stibo Systems helps companies manage their data in a well-governed manner. What does that mean? The very high-level explanation is we help companies acquire data from different sources, manage that data, govern it and prepare it for a specific use. Sometimes, the use case is to build a single source of truth that can be leveraged by other analytics or reporting tools. Other times, we become the input layer for recommendation engines, and sometimes the data is used to build contextualized and relevant product detail pages. 

Data domains we manage include:

• Product data: Think stock keeping unit (SKUs), think digital shelf where customers interact with product data related to price, inventory, color, size – everything that makes a shopper make a purchase decision.
• Location data: Consider a restaurant that has multiple locations and needs to manage and enrich their location data. This can be super useful for fast food or grocery stores, as physical location plays an important role in customer experience. During Covid, we even saw stores using their retail space as a warehouse; all is possible if you manage your location data in a scalable manner.
• Supplier data: Retailers deal with thousands of suppliers. Stibo Systems’ solution enables enterprises to manage supplier data in a central way and even have scorecards for each supplier for a better experience for both retailers and suppliers. An example is that some suppliers are providing excellent product data and assets, and therefore you don’t need to do much working with them, but other suppliers’ data may not be prime time ready. You would need to have more processes and approval workflows – we help retailers manage all that data.
• Sustainability  Sustainability data is becoming a prominent topic for many companies invested in EST and it is a complex topic, as it entails multiple dimensions. We welcome the complexity because our multidomain data management solution provides the foundation to manage sustainability data which can touch; product data, location data, and supplier data. In addition, out of the box functionalities will empower companies to design and deliver sustainability related reporting concerning their products and services

Overall, Stibo Systems Products help companies manage their data and leverage accurate, trustworthy data to make the right business decisions resulting in spectacular results. 

Better Business

Could you share a couple of customer examples where Stibo Systems’ solutions have significantly contributed to their growth and efficiency? How did multi-domain MDM play a role in this?

Stibo Systems has a robust customer base of about 600, and each customer has had results using our solutions. We help with data operations and internal efficiencies around managing data, but more importantly, we help them scale their business and drive business value. Most of our customers are billion-dollar-plus revenue customers – you can imagine they have many employees who touch data, and there are many handovers in the process, leading to high cost of data ops. Using our products help them reduce waste in the process and also reduce data liability. 

Imagine you are a manufacturing company trying to sell a product or service on a digital shelf, whether that digital shelf sits within your own channel or other channels such as Amazon or other marketplaces. Now, imagine the data you published about your product or service is wrong. Besides the embarrassment of having incorrect data, there can be legal consequences, not to mention lost revenue because customers will buy something they were misinformed or misguided on. So, the impact of not having a data management platform can be utterly negative.

Next, picture you are a retailer tasked with increasing your supplier count by 25%, but you don’t have one single headcount to deal with these suppliers. If you are interacting with your suppliers through spreadsheets and emails instead of a solution like Stibo Systems, that will be almost impossible. The same example applies if you are heavily investing in AI, and your machine learning modules are not giving you sufficient results unless you have trustworthy data. Therefore, you will not get the ROI on your data science teams and machine learning applications – recommendations or decision engines all need accurate data. 

Regardless of your industry, Data management is a necessity if you are thinking about scale, efficiency and time to market. And now, with evolving requirements like sustainability and ESG reporting, a data management tool that provides credible data is more important than ever before.  

Better World

What is the foundation story of Stibo Systems, and how does it tie into the company’s commitment to sustainability and ESG goals?

Stibo Systems believes fueling businesses with better data empowers them to make better decisions grounded in accurate data. As an example, we are working with one of the largest connected technical device manufacturers. These folks are amazing at what they do, and they understand the impact they can have on the planet by sharing their carbon footprint with their distributors and taking a collective approach towards reducing carbon footprint in the end-to-end supply chain. We help them manage that data and then share with their distributors at scale. 

Another example is companies that want to share product ingredients with their end customers. We help them with that and also show their customers data depending on their demographics. The keto diet might be a big driver for a certain region, whereas a consumer in the same country but a different zip code may be more interested in buying a whole food ingredient with less carbon footprint.

“Our partnership with Microsoft was in part based on their commitment to having have power purchase agreements for green energy contracted for 100% of carbon-emitting electricity consumed by all Azure datacenters, buildings, and campuses by 2025.”

In summary, Stibo Systems enables companies use their data to support their strategic vision, whether that vision is to become a sustainable company or provide the best digital shelf experience, or have the best experience for your supplier.

Sustainability and MDM

Could you delve into how multi-domain master data management is leveraged to address trending issues, particularly in the realm of sustainability and managing sustainability data?

By 2025, companies operating in the EU will be required to report on their sustainability efforts and progress. This reporting, akin to financial accounting, will encompass aspects like carbon footprint. European companies, as well as multinationals operating in Europe, are actively working to comply with these regulations. However, when we look at regions like Asia or North America, companies that operate within a single region or country might not have the same level of awareness about impending sustainability reporting requirements, primarily because it isn’t yet regulatory there.

Three primary reasons are driving this change. First and foremost is the regulatory aspect. Companies, especially those in the developed world, should proactively prepare to meet these upcoming regulations. Europe is leading the way with its 2025 deadline, and it’s likely that states in the U.S., particularly California, will follow suit. Second, brand reputation is increasingly tied to environmental, social and governance (ESG) issues. Reputation can be influenced by various stakeholders, and companies don’t want to find themselves lagging behind. The impact on the reputation of industries like tobacco and oil due to changing consumer expectations is a stark example.

Last, consumer purchase behavior is evolving. Consumers are becoming more purpose-driven in their choices. While price and product attributes were historically key factors, now, consumers are considering whether a product is good for the planet. They are making choices based on trustworthy information regarding packaging, recyclability, carbon footprint and more.

In essence, we specialize in managing various types of business data, and sustainability data is no exception. Stibo Systems doesn’t generate this data; we make it readily available. As the market shifts towards sustainability-conscious consumer choices and regulatory requirements loom, companies across industries, including grocery retail, will need to consider the carbon footprint of their products and supply chains. This data will play a crucial role in decisionmaking, such as selecting locally grown items with a lower carbon footprint over imported alternatives.

In summary, we focus on consolidating, governing, cleansing, and sharing sustainability data, recognizing the increasing significance of sustainability in today’s business landscape.

Learn more about Stibo Systems’ sustainability data management.

Challenges in Sustainability Reporting

Managing and governing the collection and reporting of sustainability data can be complex and error-prone. How does Stibo Systems approach this challenge and what solutions do you offer to mitigate risks?

Quite frankly, no one has all the answers to this right now. An area we feel we can help is data exchange. At the moment, there are no predefined standards about what attributes are needed or the format that they should be restored in. There’s no metadata dictionary. You might start collecting sustainability data attributes, but you have to keep reissuing them. Certain certifications only last for a year or a fixed period of time before they’re obsolete. And it’s not just capturing a company’s immediate data – it’s their suppliers, who in turn must get data from their suppliers, and so on. 

The key takeaway – sustainability data is more than just an attribute and a value. There’s a context and a lifespan around it. Stibo Systems’ role here is to make it manageable. We help create a formalized process – data controls, guardrails that MDM provides around applying data quality rules, sufficiency scores, business rules, workflows, approval processes and more. Flexibility is a big asset, too. Sustainability data management helps keep you updated as ESG standards change and as new ones come along. You must be agile to compete and win.

Future of MDM and Sustainability

How do you envision the role of multi-domain master data management evolving in the context of sustainability over the next few years? 

More so than ever, businesses are moving beyond sustainability pledges and setting carbon footprint benchmarks and targets. The next phase is about being able to prove the milestones you’ve hit, not only to shareholders and internal stakeholders but to current and future customers. As I said before, nobody has every answer yet – but I feel confident in saying that accurate and transparent data is a big first step toward being able to meet and prove the work that’s being done to lower our carbon footprints and grow sustainably.  

Is there anything else you’d like to add or share with our audience about Stibo Systems’ vision and its impact on businesses and the world at large?

I feel it’s important to point out that Stibo Systems is a business with a conscience. Meeting our sustainability and ESG goals is a realization of our company culture and who we want to be as an organization. We’re taking the same steps as our customers to ensure we are a responsible organization and take actions which are most efficient and beneficial to the surrounding environment and diverse communities. As a symbol of our sustainable growth and development, we plant a tree for every one of our new customers and employees. We are on a journey, and we want to bring our customers along with us. 

Neda Nia

Chief Product Officer at Stibo Systems

As Chief Product Officer at Stibo Systems, Neda Nia is responsible for our Product Organization that consists of Cloud Operations, Product Management, UX, Innovation, and R&D. With over 16 years of global experience spanning technology and commerce, Neda has deep knowledge of our market and has proven to establish product strategies that put the customer first. Before joining Stibo Systems, Neda has been a Managing Director at a global software and technology provider, where she defined a go-to-market strategy in North America, developed partnerships, participated in investment activities, and took part in the company’s global strategy exercises.

Neda holds a degree in Business Administration – Information Technology from Seneca College and has completed a Digital Transformation program from MIT as well as a Business Analysis program from the University of Toronto. As an agile enthusiast, Neda has obtained Scrum Master, Scrum Product Owner, and PMI Agile Practitioner certifications. She is a student at heart and continues to learn about emerging technologies to keep up with the fast-evolving market needs.

The post AITech Interview with Neda Nia, Chief Product Officer at Stibo Systems first appeared on AI-Tech Park.

“Inspire Inclusion” sets the tone for this year’s International Women’s Day theme. It’s a fitting reflection of the ever-evolving nature of marketing, where change is the only constant. The last third-party cookie has finally crumbled, privacy laws are tightening, and now, Generative AI is quickly ushering in a new era of innovation and adaptation.

With mounting research demonstrating that gender-diverse teams outperform their peers time and time again, we turned the conversation over to the exceptional women thought leaders who are at the forefront of shaping the narrative surrounding Gen AI and marketing. 

Let’s dive into their insights and experiences:

Julie Shainock, Managing Director Travel, Transport & Logistics (TTL) at Microsoft

Shainock is responsible for developing Microsoft’s point of view and future strategy for our WW Travel and Transport Industry. She is focused on leading the airlines, hospitality companies, cruise and freight logistics and rail companies to driving innovation that will enhance the customer and employee journey, while driving increased productivity and cost reduction with the use of Microsoft’s technology and its ecosystem of solution partners. 

Generative AI is set to revolutionize the Travel, Transport, and Logistics industries by delivering unprecedented levels of personalization, efficiency, and innovation. It’s not just about automation; it’s about creating intuitive, seamless customer experiences and unlocking new levels of operational efficiency. For organizations to tackle the full potential of GenAI effectively, establishing a clean data foundation and a clear strategic vision for desired outcomes is critical.”

Heather Roth, Director of Digital Strategy, Slalom

Roth has over a decade of experience in digital strategy and analytics, marketing technology, AdTech and marketing transformation for a variety of clients in all key industries, both midmarket and enterprise.

“The promise of Generative AI in marketing has brought forward the importance of data quality and having a strong data strategy. For years, marketers have operated around data owned by publishers, often piecemealed together in different platforms and spreadsheets. The ability to execute on Generative AI tactics is only as good as the data you put into it, which is really driving companies to focus on understanding what data is needed across the business to execute on AI-driven experiences and making investments in owning their data and building out higher quality data inputs. The investment in data maturity has accelerated by years in a matter of months.”

Lisa Gately, Principal Analyst at Forrester (Forrester Blog)

Lisa has 20 years of experience in B2B technology content, communications, events, and services marketing. She helps Forrester clients build and optimize their B2B content engines and transform them into competitive differentiators. Lisa is an evangelist for audience-centric content strategy, content marketing, and content operations.

“During the past year, we’ve seen genAI capabilities appear in the martech stack along with a rise of multimodal capabilities, where AI models can understand, interpret, and generate content across multiple formats like text, images, audio, and video. It can be overwhelming to understand which systems do what tasks and to determine which ones to embrace. However, making time to learn about these capabilities is important. GenAI brings more power to content creation, audience engagement, and personalization. Content use cases aren’t only a practical entry point for scaling genAI adoption; they also represent a large part of an organizations’ activities and offer enormous potential for enhancing the customer experience and speeding time to market. Acting now is essential because the pace of change for genAI will only accelerate.”

Joyce Gordon, Head of Generative AI, Amperity

Gordon leads Amperity’s generative AI product development and strategy. She’s also worked on the product development for many investments across the ML and ML Ops spaces, including launching Amperity’s predictive models and infrastructure used by many of the world’s top brands.

Here, she offers insights into using gen AI to gain a leg up on the competition and highlights the crucial significance of a clean data foundation.

“Gen AI is only as good as the data that powers it. And since customer data is notoriously complex, it takes a different AI process to unify it into accurate, comprehensive profiles that can feed your Generative AI tools to get the best results.  

Customer data tools can use AI to power critical processes behind the scenes, including data unification, insights, and predictions, so you have the answers to the questions “Who are my customers? What did they do? And what should I do next?” 

In a world where the same Generative AI tools for activation are available to everyone, the data you feed into your Gen AI systems will be a key competitive differentiator, since it determines the quality of the output. In short, it’s not enough to have AI tools at the last mile — it needs to be part of your approach from the first step.”

In celebration of International Women’s Day, the theme “Inspire Inclusion” brilliantly mirrors the perpetually shifting landscape of marketing, emphasizing the necessity for continual evolution. Amidst the demise of third-party cookies and the tightening grip of privacy regulations, Generative AI (Gen AI) stands out as the vanguard of progress and adaptability. This pivotal moment highlights the critical insights and pioneering efforts of distinguished women leaders in marketing, who are at the helm of steering the Gen AI conversation. Their collective wisdom underscores the importance of embracing Gen AI not only as a tool for innovation but as a fundamental pillar for cultivating growth and establishing meaningful relationships within the rapidly transforming marketing domain.

Explore AITechPark for the latest advancements in AI, IOT, Cybersecurity, AITech News, and insightful updates from industry experts!

The post Celebrating Women Leaders Shaping the Future of Marketing with Gen AI first appeared on AI-Tech Park.