Hi Steve, welcome to the AiThority Interview Series in 2023. Please tell us about your two decades of tech experience so far. How did you arrive at Mastercard?

My career has had several phases. For the first 10 years or so after graduating, I worked at various – mostly small – independent, software companies and consultancies. My position evolved over the years; I started as a developer before advancing to the role of a software engineering manager and then eventually becoming a CTO.

Next, I worked for Science Foundation Ireland (SF), Ireland’s national science funding agency, where I led our investments in topics such as computer science, data science, software engineering, and artificial intelligence.

In 2014 I started at Mastercard, which is where I still currently work today. Initially, I supported and grew a team called Start Path, an engagement program for innovative startups in the fintech space. A few years later, I joined Mastercard Foundry, the innovation and R&D arm within the company, leading research and development for AI, ML, and now also quantum computing. This July, I was appointed to Mastercard’s first class of Distinguished Engineers, a recognition for select Senior Vice President technical experts as part of the company’s continuing commitment to technology, innovation, and career growth. With this distinction, I continue my work with a focus on artificial intelligence and quantum computing. 

You are in charge of Mastercard R&D’s strategy and execution of AI and ML in new product development efforts. What is the biggest challenge to Digital Transformation in the market you cater to?

Of the many years that I’ve worked in technology – this current period is distinct for the speed and scale of innovation taking place. This dynamism is exciting because we’ve only just scratched the surface of what is possible for businesses and consumers, but with it also comes new challenges for enterprises.

For one – leveraging emerging technologies to build new products and services.

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Part of the equation is to understand and introduce technologies like web3, spatial computing, PETs, and AI/ML, while also maintaining and upgrading legacy systems, and aligning with ever-evolving legislation and regulation governing their application.

AI specifically has been top of mind for our market, especially following the fairly recent explosion of generative AI.  Mastercard has been putting AI to work for years, particularly in our products and solutions across open banking, routing, personalization, and fraud that enhance the safety and security of the payments ecosystem.  Although the step change between AI and generative AI is exponential in terms of what you can do with it, our deep roots in AI have afforded us the capabilities, talent, framework, and partnerships to keep a pulse and execute on emerging technologies.  

As a leader in the payments space, and as with any nascent technology, Mastercard has a responsibility to set the precedent for exploring generative AI responsibly.  We developed an AI governance program and guidelines for our data scientists to minimize risks in AI and best serve our customers, invested in partnerships with key institutions like RIT In Dubai and Howard University, and actively encouraged our employees to safety test and learn. 

What technologies within AI and computing are you interested in?

The idea of being able to control a computer system and anything connected to it through programming has fascinated me since I was a teenager.

Today I’m looking at how AI, mixed reality, spatial computing, and web3 have unlocked an entirely new frontier in technology. We’re likely to see several key trends, such as the rapid increase in computational power, both at the edge and in the cloud, and the tokenization of assets to start to coalesce around some of these new computing paradigms.

For AI, the incredible advances born from generative AI and Large Language Models (LLMs) are also contributing to the transformative period we’re in.

Currently, Mastercard is engaging in test-and-learn with generative AI applications to enhance operational efficiency and improve data quality, aggregation, entity resolution, and categorization.

We’re also using ML for certain models that support our open banking solutions, such as credit scoring, financial management insights, account opening, and payments. It enables us to extract, identify, and classify data quickly and more efficiently than rules-based models alone.

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In the longer term, I’m paying close attention to both quantum computing and AGI. With quantum, I’m tracking developments in both hardware and software, to understand how these new devices will help us to solve ever more complex computational problems, and what use cases will arise in our industry. With AGI, at some stage, we may be looking at the prospect of human-like machines that can solve a wide range of complex tasks at scale. 

In the current analysis, it is reported the global quantum computing (QC) market will be at $900 million. How do you see QC disrupting the digital market in the next couple of years? 

At $900m, quantum computing is still a very small part of the overall computing market.

Over the next few years, we’ll see quantum computers – inclusive of quantum annealers – get progressively more performant, capable, and reliable.

Currently, our best guess is that the earliest use cases in banking and payments will most likely be in the optimization space, with other applications such as machine learning coming later.

Rather than a disruption, it’s more probable that we’ll see quantum technology adopted gradually, across industries and companies, as the technology continues to improve, becomes more usable, and its primary use cases become more evident. 

What steps can young technology professionals take to enhance their proficiency in collaborating effectively with Cloud, Automation, and AI-based tools? 

Nothing beats getting “hands-on-keyboard” experience using these technologies.  One of the amazing benefits that all young tech professionals have today is readily available online learning materials. There are tutorials on YouTube for just about every emerging technology imaginable, and through cloud computing, there’s also access to the resources required to explore those areas. Many cloud and tech companies also offer cheap or free trial accounts to help young developers learn their technologies at little or no cost.

On the Mastercard Developers platform, for example, you’ll find a quick start guide that will walk you through how to create a new project using Mastercard’s APIs, and gain access to the Sandbox environment. So, armed with nothing more than a laptop and an internet connection, people can get access to all the technology they could imagine, even quantum computers!

One of the tried and tested ways to build skills in these areas has been through the open-source community – whether it’s contributing to an existing project that you find interesting or relevant, or starting a personal project that scratches your own itch. 

What are your predictions for AI/ML and other smart technologies heading beyond 2024?

As machine and deep learning evolve, so too will their role within our sector. This past year has been about experimentation. In 2024, we expect generative AI to continue to gradually integrate into business operations and products.

Companies are currently focused on internal generative AI applications, like software development co-pilots, knowledge bots and operational efficiency drivers that are serving as testbeds and laying the groundwork for what’s to come. This phase is likely to continue throughout the year, as companies start building the foundations for implementation. As challenges like data privacy, information accuracy and bias are addressed, we anticipate that the range of use cases will expand to include more ambitious and public-facing deployments.

 

One of the most compelling use cases for generative AI in the financial services industry is in open banking. With the aid of fine-tuned LLMs, generative AI can enable the cleaning and categorization of data at a significantly higher through-put and with more accuracy than previously available.

In line with informed data consent protocols, generative AI could streamline personal financial management, for example, by acting as a personal wealth manager to create an encompassed view of an individual’s financial well-being, help formulate college savings plans, procure loans and implement financial strategies – empowering people to navigate their financial lives more adeptly.

Thank you, Steve! That was fun and we hope to see you back on AiThority.com soon.

Hi, welcome to the AiThority Interview Series. Please tell us a bit about yourself and what is D-Wave.

I am Dr. Alan Baratz, President and CEO of D-Wave (NYSE: QBTS).

D-Wave is a leader in quantum computing technology and the world’s first commercial supplier of quantum computers. Our technology has been used by some of the world’s most advanced organizations, including Volkswagen, Mastercard, Deloitte, Siemens Healthineers, Pattison Food Group Ltd, DENSO, Lockheed Martin, the University of Southern California, and Los Alamos National Laboratory.

How do you see the quantum, computing market shaping in 2024?

The global quantum computing market is rapidly growing and some market analysts project it will reach upwards of 6 billion + by the end of this decade. As 2023 closes, it would be interesting to see how quantum computing influences 2024. The future of quantum computing would largely relate to a rapid government adoption, the future of work, and quantum supremacy.

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Will the economic recession affect the quantum computing industry in 2024?

With economists projecting a shallow recession in 2024, organizations will seek new technologies, such as quantum computing, to navigate adversity and bolster business resilience. Quantum technologies can accelerate problem-solving and decision-making for a wide range of common organizational processes, such as supply chain management, manufacturing efficiency, logistical planning, and employee scheduling. Amidst a challenging economic environment, quantum’s ability to fuel operational efficiencies is critical.

How can organizations achieve supremacy with quantum computing in 2024?

The industry will achieve a proven, defensible quantum supremacy result in 2024. Ongoing scientific and technical advancements indicate that we are far from achieving quantum supremacy. 2024 will be the year where quantum definitively outperforms classical, full stop. There will be clear evidence of quantum’s ability to solve a complex computational problem previously unsolvable by classical computing, and quantum will solve it faster, better, and with less power consumption.

The breakthrough we’ve all been pursuing is coming.

What would be the role of the US government in pushing the bar higher in quantum computing innovations and adoption?

The US government’s usage of annealing quantum computing will increase given the anticipated passing of legislation including the National Quantum Initiative and the National Defense Authorization Act. 2024 will see a rapid uptick in the quantum sandbox and test bed programs — with directives to use all types of quantum technology, including annealing, hybrid, and gate models. These programs will focus on near-term application development to solve real-world public sector problems, from public vehicle routing to electric grid resilience.

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Could you define the international alliance needed to expand quantum computing?

The global quantum race will continue to heat up, as the U.S. and its allies aggressively push for near-term application development. While the U.S. is now starting to accelerate near-term applications, other governments like Australia, Japan, the U.K., and the E.U. have been making expedited moves to bring quantum in to solve public sector challenges.  This effort will greatly expand in 2024.

Top public sector areas of focus will likely be sustainability, transportation and logistics, supply chain, and health care.

In 2024, what would be the impact of quantum computing technology and applications on the future of work? 

Quantum computing will show proven value and utility in daily business operations through in-production applications.

As we close 2023, companies are beginning to go into production with quantum-hybrid applications, so it’s no stretch of the imagination to see corporations using quantum solutions daily for ubiquitous business challenges such as employee scheduling, vehicle routing, and supply chain optimization. In time, it will become a part of every modern IT infrastructure, starting with the integration of annealing quantum computing.

Thank you, Dr. Alan! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi Michael, Please tell us about the latest trends in IT security budgeting.

Hi, Sudipto. In 2023, IT security leaders are facing tighter budgets and they will need to optimize and consolidate the tools they have already procured. When looking at new tools, they will have to be able to take out two or three existing products to fit within budgets in 2024. It means cybersecurity vendors will need to double down on technical innovations that drive productivity while keeping costs top-of-mind.

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Beyond product enhancements, we will also see continued partnerships and integrations between vendors to meet this need and reach more customers.

That’s great! Does it mean Security leaders would find it more economical to leverage AI tools for their mission-critical operations?

Yes. AI will have a huge impact in 2024.

A huge issue for organizations (especially education, healthcare, and other industries) is that trained cybersecurity talent is scarce and expensive. These organizations struggle to hire and retain best-in-class talent. ISC2’s 2023 Cybersecurity Workforce Study found that the cybersecurity workforce grew by 8.7% to 5.5 million but open cybersecurity positions increased 12% to over 4 million. With this in mind, organizations will seek to leverage AI to help compensate for the talent gap.

Generative AI has the opportunity to generate training content specific to various roles and deliver that content on an ongoing and interactive basis to ensure every employee is best equipped to be a protector of their organization.

AI makes it possible to apply adaptive learning techniques across organizations at scale.

Which areas would continue to pose challenges to security leaders in 2024?

Cybersecurity, for sure…

Gaining access to any enterprise via valid credentials remains the preferred method of access for cyber actors.

As Generative AI matures over the next year and beyond, social engineering attacks fueled by Generative AI will become easier to perpetrate, will increase in scale, and will be increasingly realistic. No amount of training will be able to prevent some of these tactics, so we will surely see an increase in cyberattacks. Therefore, over the next year, we’ll see how many organizations have built their defense strategy around a cyber resilience mindset, e.g. micro-segmentation, passwordless authentication, phish-resistant MFA, moving from privilege escalation to separate privileged user accounts, and when it all fails, having immutable data backups.

How do you see AI and regulations shaping the security marketplace in 2024? Are CISOs ready to meet these regulations?

The recent SEC action against SolarsWinds and more importantly against the CISO Tim Brown shows that CISOs are increasingly in perilous situations. There will never be enough resources devoted to cybersecurity in any enterprise yet CISOs have to make risk-based decisions every day. If that were not difficult enough, add to that the threat of criminal charges if you get it wrong and it only adds to an already incredibly stressful environment.

Will we see more and more CISOs leave the profession?

Will we see an increase in CISO turnover?

How will the relationship between the CISO the board and the executive leadership team change?

On a positive note, New York recently announced a new cybersecurity strategy that will mandate comprehensive cybersecurity programs, vulnerability assessments, access controls, and security awareness training for hospitals, offer $500 million in funding for healthcare IT, and expand the cyber resources of state-wide criminal investigative entities. This is a huge step forward and I can only hope other states and municipalities follow New York’s lead.

Thank you, Michael! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi, Dan. Welcome to the Interview Series. Please tell us about your role at HTC VIVE.

I am the General Manager of the HTC VIVE Business for the U.S. region which is inclusive of Product Management, Sales, Marketing, and Operations. I have oversight and responsibility to deliver our full portfolio of HTC VIVE Products, Services, and Solutions for all our Consumer and Enterprise customers.

What has changed in the AR VR technology development landscape in the last three years?

I think it’s safe to say that for all tech, advancement and miniaturization go hand in hand. The XR industry is starting to hit its stride in this regard, with smaller and more powerful devices coming to market. HTC VIVE released the first glasses-style VR headset, VIVE Flow, in 2021. We followed it this year with VIVE XR Elite, which is also foldable and compact, but much more powerful.

Mixed reality (MR) is also in the spotlight these days. That’s largely thanks to improvements in passthrough technology, and the addition of depth sensors to headsets. VIVE XR Elite was our first headset with a sharp, color passthrough that makes MR not only practical but also fun. We’re starting to see some groundbreaking applications developed by our partners Taqtile, HAVIK, and more. But we’ve only scratched the surface of MR; there will be advancements in cameras and computer vision techniques in the coming years to bring these experiences even closer to natural human eyesight.

There are also big changes happening on the wireless infrastructure side. You need powerful, high-throughput connections to run immersive content in a secure environment – much more than what’s needed to stream movies. 5G and eventually 6G antennas will be integrated right into VR headsets. In the interim and to meet market needs, we’ve developed a Private 5G solution called REIGN CORE that can blanket a 10,000 m2 warehouse in a secure 5G signal. Recently, we attended the Interservice/Industry Training, Simulation, and Education Conference (I/ITSEC) demonstrating secure XR training solutions for defense, military, and law enforcement.

Connectivity was part of every conversation as government organizations looked to implement training solutions and scale in a secure environment. This Private 5G solution then enables organizations to run VR training with almost no latency.

Could you tell us about the XR product roadmap at HTC Vive? Which industries are you currently focusing on?

We count a lot of great partners in the defense vertical, as well as in healthcare and training. The technology trends I mentioned before – miniaturization and better passthrough – lend themselves well to all different types of training scenarios.

At I/ITSEC, we had up to 30 partners showcase their immersive training simulations that replicate real-world scenarios, giving trainees a safely controlled space to learn and advance their skill sets for mission-critical procedures on VIVE devices. 

In terms of products, we launched our newest device, the VIVE Ultimate Tracker recently. It’s a “self-tracking” tracker which means it knows its own position in 3D space and can thus be used to track your body parts in VR precisely. You can also attach it to physical objects and bring them into VR experiences. This is extremely useful for a lot of different vertical partners: healthcare, industrial training, defense, design, and more.

According to HTC VIVE’s latest report, 80% of active military-duty trainers said that XR enhances their education plans and empowers trainers to be more effective. Can you please explain what this means for realism-based training programs in critical operations?

XR training is kinesthetic in nature. It’s the most effective learning method for lots of people, as opposed to reading or listening to lectures. According to the National Training Laboratory, the retention rate for VR learning is 75% compared to 10% for textbooks and only 5% for lectures. In other words: humans learn by doing. XR makes it possible to go through potentially dangerous scenarios in the headset, without any actual safety risk, and get better prepared for real-world missions.

How is HTC VIVE eliminating work silos in remote settings? 

We have an enterprise platform called VIVERSE for Business, which lets employees with all different kinds of roles collaborate remotely. We built it with enough features to make it as powerful as you need – for example, for group visualization of 3D objects – but also with many core productivity features like scheduled meetings, support for 2D video calls on Zoom and Teams, and Microsoft Office file support.

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The whole idea is for VIVERSE to be an extension of the conventional office, particularly for globally distributed and remote teams.

Sales and Marketing organizations are steady users of XR technology for their lead-gen campaigns. How do your customers use VR to improve their lead gen operations?

It’s a great question as we use the workflow tools from VIVERSE for Business applications for our meetings as well as reviewing the content and preparing presentations for our customers and training on new products. We are also integrated with Salesforce in our VIVERSE for Business application and we can review customer information and engagement plans and strategy in our XR Headsets. In addition, we have integrated over five MDM partners as well as our own native solution for commercial customers looking to bring better management and security. Overall, we’re seeing great results with training, collaboration, and integration of useful applications like Salesforce. There’s a lot more to come on applications we are integrating and how we’ll continue improving workflows and efficiencies.

Your predictions on the future of AI in the XR industry that requires highly optimized and CX-driven workflow automation: 

AI will make our interactions with XR technology easier and more natural. Working with virtual input methods like keyboards is tricky, with a learning curve. AI can help us more naturally interact in VR through speech and gestures, in a human-centric way. Soon, we’ll probably be able to speak things into existence – like virtual objects and worlds. This means that the advent of AI will make it much faster and easier for businesses to develop intuitive, customer-first workflows.

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Thank you, Daniel! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi Ryan, welcome to our Interview Series. Please tell us a little bit about your role and responsibilities at Salesforce.

I’m the SVP of Product Management of Service Cloud at Salesforce, where I oversee the platform and help thousands of companies utilize our trusted AI for customer service to create seamless conversational, predictive, and generative AI experiences for agents and customers.

Could you tell us more about the ideal customer profile of Salesforce Service Cloud? Which industries rely on your solutions and services?

Delivering efficient customer support is crucial to driving satisfaction, loyalty, and positive customer experiences for companies of all sizes, in every industry, around the world. Any company looking to streamline and enhance its customer service operations is a good fit for Salesforce Service Cloud. Service Cloud helps organizations of all sizes, like Heathrow Airport and AAA, deliver personalized customer service with AI-powered insights, recommendations, and productivity tools.

Salesforce Service Cloud also offers industry-specific applications for business across more than 13 industries, from IT to retail, consumer goods, and beyond. Leading solar services provider Sunnova is using Service Cloud to easily track the performance of its hardware, automatically create work orders, and resolve cases faster using predictive AI from Einstein for Service.

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Tell us more about your newly launched Sales and Service AI capabilities. Can you tell us about Einstein GPT’s role in these announcements?

Salesforce recently debuted new AI capabilities for both Sales Cloud and Service Cloud. The Sales Cloud innovations are designed to boost productivity and help sales teams close more deals, faster. Service Cloud boasts a broad set of AI capabilities, including Einstein Copilot for Service, which automates personalized responses based on real customer interactions to help resolve issues faster. The newly launched AI innovations for Service Cloud bring AI-powered insights directly into the flow of work for service professionals. These capabilities transform how service teams deliver value across customer touchpoints — from process and automation to operations — to boost agent productivity, cut costs, and enhance customer satisfaction.

Our latest launch is Service Intelligence for Service Cloud with Einstein Conversation Mining. This innovation uses AI to analyze customer chats and emails to uncover insights. For example, the new solution can analyze a customer’s specific challenges and then asses the likelihood of complaint escalation to proactively address the customer’s issue. It could also identify a trend in customer cases, like if there’s an increase in customers asking about a return policy. With that information, service agents then train a bot to spot similar customer cases and automatically surface a self-help article on returns to help them resolve the issue faster.

How does Service Cloud align with Marketing and Sales Cloud? What are the benefits of using Salesforce for omnichannel customer experience management?

Omnichannel is designed to combine all channels into one seamless experience, whether before the purchase, during the purchase, or after the purchase. Omnichannel helps break down the siloes that can complicate customer interactions. With an omnichannel mix, information is shared between sales, service, and marketing team members to ensure that support staff have information readily available to assist the customer.

Renowned Italian fashion designer, Boggi Milano, adopted the omnichannel mix to improve their customer experience from discovery to service. With this approach, Service Cloud enables Boggi Milano customers to begin shopping online, chat through purchasing decisions with a service rep, and transition seamlessly to a personalized in-store retail experience.

What kind of infrastructure does a financial services organization need to match the demands of modern contact center transformation?

Could you share some use cases from the financial services industry specifically mentioning your differentiated Sales and Service AI products and services?

The customer service demands of modern financial service organizations are unique. Salesforce technology is designed to help these organizations tackle constantly evolving demands by providing the tools to tailor individualized client experiences.

The AI revolution is here, but at the foundation of the contact center transformation is really a data revolution. Industries like financial services need the infrastructure in place to ensure that their customer data can be the basis of next-generation AI experiences. Building a proactive, personalized service experience based on real customer data and interactions can help these organizations solve customer challenges more efficiently.

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For example, Santander UK relies on Service Cloud for automation in the customer support process, which has transformed how it manages relationships. Powered by Service Cloud’s Live Agent feature, Santander helps subscribers of its digital platform Navigator directly connect with support team members via live chat. Every new business contact and each subscriber case is automatically created in Service Cloud, helping Santander streamline other important tasks with intelligent workflows. These AI integrations enable Santander to personalize experiences for each client’s unique journey and build true partnerships with their growing businesses.

Beyond financial services, organizations across industries count on Service Cloud to help support their customer needs. Organizations spanning industries like retail, healthcare, manufacturing, and more use Service Cloud to incorporate automation into the service process and nurture customer relationships throughout every stage of the lifecycle.

Lighter notes:

Coffee, or Tea?

A Chemex Pourover is absolutely part of my morning ritual at home, but a cuppa is always welcome when traveling.

Most useful app that you currently use:

I wouldn’t even know how to answer these questions without Slack’s new Canvas feature for team collaboration.

Your favorite Salesforce product marketing initiative that you want everyone to know about:

It’s difficult to pinpoint just one initiative, but adding new AI-powered capabilities to Salesforce Service Cloud is one of my favorites. Salesforce has long been a pioneer in the AI space and the future holds even more exciting AI-driven developments for Service Cloud.

Your first memorable experience in your Salesforce career

My first time on the main Dreamforce stage was as a partner, where I was meant to silently give a demo on behalf of one of our customer Trailblazers. Marc kept asking me all these great questions… not realizing that I didn’t have a microphone to give him answers!

Thank you, Ryan! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi, Dr. Karin. Welcome to the Interview Series. Please tell us about your role at LinkedIn. How did you arrive at LinkedIn?

I’m LinkedIn’s Chief Economist, leading a team of economists and data scientists who track, analyze, and report on key workforce and labor market trends unfolding on LinkedIn. Before joining LinkedIn in 2020, I held a variety of positions, including Assistant Treasurer for Google, Managing Director, and Head of Macroeconomic Policy at Bank of America Merrill Lynch, and I worked at the Federal Reserve Bank of New York for about a decade. What excited me about joining LinkedIn was the mandate to explore the wealth of data on the global labor market and to apply our insights toward LinkedIn’s mission of creating economic opportunity for every member of the global workforce.

How do you differentiate AI skills from non-AI skills? Which skills would likely improve the quality of life of employees and workers in 2024?

LinkedIn members self-report their skills on their LinkedIn profiles. Currently, more than 41,000 distinct, standardized skills are identified by LinkedIn. These have been coded and classified by our skills taxonomists into 249 skill groupings, which are the skill groups represented in the dataset. AI is one of these groupings in which we track 121 distinct AI skills. The top, most popular, skills within the AI skill grouping are machine learning, natural language processing, data structures, computer vision, and image processing among others.

There is a broad range though, and AI skills can include everything from the skills needed to build and finetune AI models and tools to the skill of knowing how to apply AI tools for various business purposes.

What we’re seeing at LinkedIn is that while AI skills are on the rise in terms of demand, people skills are gaining importance right alongside them. So when we look at the U.S. specifically, the most in-demand AI skills are machine learning, data structures, and natural language processing, while some of the most in-demand people skills across many large economies are communication, analytical skills, and leadership. And employers are increasingly looking for talent who combine these two types of skills –AI and people skills– together.

To prepare for the changes AI and Generative AI (GAI) are bringing to the world of work, businesses will need to thoroughly understand the skills they have and the skills they need. Professionals will need to focus on acquiring and developing AI literacy skills to better position themselves as they go forward in 2024.

AI adoption has grown at lightning speed. How are AI conversations on LinkedIn and other networking platforms shaping the business landscape?

Conversations around AI on LinkedIn have increased by 70% globally since GAI sparked in popularity — a very significant jump when compared to other recent tech advancements like cryptocurrency (which saw a 19% increase at its peak in November 2021) and augmented and virtual reality (which experienced a 5% increase at its peak in October 2021).

We are seeing these conversations being driven in large part by millennials, professionals in executive or engineering roles, and people based in industries like professional services, technology, and education.

Interestingly, conversations around AI aren’t just happening within one industry or organization — these conversations are top of mind across genders, generations, occupations, and industries. I believe these conversations are helping to bring what used to be a somewhat niche topic into the mainstream, and it’s driving excitement to explore and adopt AI tools. It’s also demonstrating just how widely applicable AI can be — professionals across almost every industry and position can find ways that AI can help them become more productive at work.

Could you highlight key takeaways from your Future of Work Report? Should business owners embrace AI more freely in 2024 to become more competitive?

In general, business owners, business leaders, and professionals at all levels should be developing their understanding of AI and embracing their AI literacy. These are the skills of the future, but they’re also quickly becoming the skills of the present. As of September 2023, 74% of U.S. executives see at least one way GAI will benefit their businesses and employees — including increasing productivity and unlocking more growth and revenue opportunities. But the plans themselves are still very much being formed.

We’re at an exciting place right now where business executives are enthusiastic about AI and plan to increase their use of AI in their organizations within the next year, but more than half of executives do not yet know exactly how their organization is going to use it. It’s very much at a point where businesses are still figuring it out — and like most new technologies, the early adopters will likely have a leg up on the competition. This is why my team at LinkedIn is focusing on this topic — to help business leaders abstract from all the noise and acquire a structured and data-driven way of thinking about the impact of AI on their organizations.

The fear of job losses is getting real. And, so are the dangers of abusing the powers of AI, especially when we talk about deep fakes, ransomware attacks, and copyright infringements. Could you tell us how AI leadership can bring more transparency to the whole job marketplace to meet the above-mentioned challenges?

As an economist, I’m probably not the best person to weigh in on trust and security-related topics, but as we consider business leaders’ responsibilities as this AI transformation begins, there are a couple of things I’d like to mention.

We are just starting to scratch the surface and many companies are just starting to invest in AI training. Employers must be thoughtful about what AI means for their employees, ethical about how they bring in AI, and invest in the needed training for their employees. It is also critical to ensure cross-sector outreach to diverse communities and to invest in skills that can help lead to expanded access to opportunity. Employers will need to be conscious of training both more senior and junior employees in AI.

It’s also important that mitigation and strict guidelines are in place to ensure that AI is not disproportionately impacting one group of people over another. As one example, in terms of representation right now in AI, we are seeing that the artificial intelligence sector is overwhelmingly represented by men (70%) compared to women (~30%) — this makes men more than twice as likely as women to be in the AI industry. So these are some of the things business leaders need to consider and be thoughtful about moving forward as AI becomes more mainstream.

Age is just a number in the digital space. What does your Future of Work report state about the excitement around AI among different age groups?

When it comes to conversations around AI and overall excitement for AI, we see that younger generations are particularly excited about AI and how it could help them in their careers.

We know that Millennials and Gen Z are driving the bulk of conversations around AI on LinkedIn (45% and 26%, respectively). At the same time, Millennial and Gen Z survey respondents globally expressed noticeably higher excitement than their Gen X and Baby Boomer counterparts when it comes to AI’s ability to provide access to knowledge and information faster, improve the quality of their work (copywriting, creating presentations, etc.), and help them summarize a lot of information quickly.

In addition, Millennials and Gen Z professionals globally are the most likely to say they’ve begun experimenting with AI tools like ChatGPT and Microsoft Copilot at work, as well as most likely to say they’ve taken an online course to better understand AI. In the U.S., Gen Z are 1.6 times more likely to want to learn AI skills than Boomers and 1.1 times more likely than Gen X.

Your predictions on AI’s role in democratizing workplace equality globally?

Unlike the rise of machinery and automation, or any number of technological advancements that have largely displaced select subsets of workers, the AI revolution is poised to transform over 50% of jobs across all professional levels, education levels, and industries. So, the impact of AI will be felt more evenly across the workforce than we’ve seen in the past, which is worth noting.

We at LinkedIn believe that the rapid rise of AI will produce opportunities for professionals of all levels of education and years of experience to not only find but excel in their roles. Over the past decade, and particularly during the pandemic when employers were deeply struggling to fill open roles, we’ve observed a steady move away from relying on degrees or years of experience in a hiring situation and towards skills-first hiring among business leaders.

The rise of AI is accelerating this shift. Employers are increasingly looking for professionals who can demonstrate specific skills — both hard skills and people skills. With AI being so new and rapidly evolving, professionals who embrace it early on and begin to gain AI literacy will have the upper hand when looking for a job, even if they don’t have the strongest “traditional” professional background (like a four-year-degree or a decade of experience).

We also believe the rise of AI within the workplace will in some ways reduce the need for specialized knowledge on a certain topic or industry overall, thereby making job mobility more possible. For instance, having the AI skills and literacy to draft a white paper, create a promotional video, or translate a company-wide memo into different languages may become just as valuable to an employer as having a background in film production or fluency in several languages. It therefore becomes a matter of knowing how to use AI to create those things, rather than necessarily needing to know them themselves. If you can acquire those AI skills and learn how to generate the end-result you need, in many ways those skills become industry- and role-agnostic and can be applied very widely.

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Additionally — and this is one of the things LinkedIn members are most excited about when it comes to AI — tapping into AI tools can remove much of the day-to-day busy work that many professionals do regularly. By automating many tedious and time-consuming tasks like note-taking in a meeting, researching, summarizing documents, and scheduling, AI can enable us to unblock our schedules and to-do lists and give us more time to hone our creativity, passions, and people skills. The hope is that AI will ultimately bring us greater satisfaction in our jobs and enable us to make a greater impact in our careers.

Thank you, Dr. Karin! That was fun and we hope to see you back on AiThority.com soon.

Hi Jenni, please tell us about your role at AWS and how you arrived here in the company.

I lead a team that’s focused on creating and delivering cloud computing skills training for people at all levels of technical proficiency. It’s an exciting time for the team because there is so much excitement and demand around cloud computing and cloud-enabled technologies like generative AI. We understand that there is no one size fits all approach to honing your skills, and my team is focused on innovating new courses and programs ranging from self-paced courses to hands-on labs and game-based courses, too.

I previously worked at New Relic and VMware, helping them upskill their sales and technical field organizations. These experiences ignited my passion to continue pursuing a career helping individuals and organizations skill-up in the latest technologies, including helping leaders think through how to empower and excite their workforce.

You have managed a wide range of roles and functions. Could you please tell us how you promote learning and upskilling opportunities within AWS? 

“Learn and Be Curious” is one of Amazon’s leadership principles, so as you can imagine the whole company values and supports employee skills training and education. In fact, Amazon is committing more than $1.2 billion to provide free education and skills training opportunities to more than 300,000 employees. We do this through a range of programs designed to meet employees’ various learning goals—whether they are looking to learn a new skill or completely reimagine their careers. This commitment is our way of setting the example from the top—a crucial element for success for any business that’s considering upskilling their workforce. It’s the first thing I tell executives who ask me, “How can I make sure my workforce has the skills they need to support our digital transformation?” Within my team specifically, we take things a step further by making every Friday a meeting-free day across AWS Training and Certification. This is designed to allow our team to make space for training or focus on a creative project that requires a big chunk of uninterrupted thought-space.

Importantly, many of the courses that we recommend to our employees are the same ones we make available to the public. We are investing hundreds of millions of dollars to provide free cloud computing skills training to 29 million people around the world. Many courses and programs require nothing more than an internet connection to get started—and we have more than 80 courses and resources for individuals who are looking to hone their AI and generative AI skills.

How can CXOs come to speed with the AI learning courses? 

Regardless of your organization’s adoption of cloud technologies, executives who understand the capabilities of cloud and its impact on operations across the organization are better equipped to set the vision for their organization’s digital transformation.

We recently released an educational series for CXOs designed to provide a primer on the cloud’s capabilities and business benefits for innovation and competitive advantage.

AI upskilling is the need of the hour. However, budget constraints toward AI adoption and professional training are considered as the biggest barriers. How would AWS training courses solve these challenges for organizations?

Investing in training is investing in your business. It’s that simple. As cloud adoption accelerates, having a cloud-skilled workforce makes or breaks an organization’s ability to succeed in the cloud. In fact, employees’ IT skills account for 40% of an organization’s digital transformation results. Research also shows that 90% of organizations that invest in employee training report faster achievement of reach their digital transformation goals and nearly 85% noting improved worker retention.

One of the most effective ways an organization can close its cloud skills gap is by modernizing IT skills within your existing staff. We recommend a comprehensive education strategy that includes both cloud fundamentals training for a wide range of stakeholders, as well as deep cloud training for key technical teams. A good place to start is AWS Skill Builder, which has more than 600 free courses in up to 14 languages ranging from foundational to advanced levels. It provides role-based training and learning plans focused on a specific domain or role so there is something for everyone, no matter where in the organization they sit. We also work with organizations to create customized training plans specific to meet their business goals and have worked with companies including Lockheed Martin and Pearson to upskill their workforces.

Please tell us more about the unique features of the AI courses AWS has just released. What kind of background should a professional have to avail the course?

Generative AI is here to stay, and that means organizations and individuals should be thinking and taking steps to hone their knowledge in this area now. To help people of all technical levels get smart on the topic, we released seven free and low-cost courses. This includes a course specifically designed to help CXOs better understand how generative AI can help their business. There is something for everyone, no matter your level of technical experience  including a free Generative AI Foundations on AWS course designed for technologists already familiar with AI modeling, as well as AWS Jam Journey – Build Using Amazon CodeWhisperer that provides hands-on practical experience.

What’s your opinion on the role of AI-based training and learning programs on employee career mobility opportunities? 

I have yet to meet someone who regretted learning a new skill. I encourage anyone curious to learn about AI to do it. There’s only upside. From a career advancement standpoint, employers want to see employees and job applicants who are hungry to learn. Additionally, job opportunities in AI and generative AI will only increase with time. The World Economic Forum’s Future of Jobs Report 2023 indicates that more than 75% of organizations plan to adopt big data, cloud computing, and AI in the next five years.

Where is AI at the workplace heading? Do you have any case study or research papers at AWS that identified the state of the future of work built on AI capabilities? 

I recommend, “How Technology Leaders Can Prepare for Generative AI,” by Phil Le-Brun. Phil is an enterprise strategist at AWS, which means he speaks with C-suite executives regularly about their digital transformation journeys, including generative AI adoption strategies and considerations. It’s a great review of key considerations when thinking about how to adopt generative AI within your organization, and includes a section on upskilling your workforce.

Thank you, Jenni! That was fun and we hope to see you back on AiThority.com soon.

Hi Shagun, welcome to our AiThority Interview Series. Please tell us about your journey in the tech industry so far.

I was educated in the United States and Switzerland and had briefly contemplated pursuing a career in fashion. I started my career in the travel and hospitality industry and ultimately fell in love with the world of audit, controls, and the accounting process.

Over the course of working in this industry, I knew firsthand the multitude of problems and risks accountants faced when employing manual methods to close the books and complete account reconciliations. Whether it’s a large corporation or a small company, closing and reconciling is part of the routine function in the accounting department. Although not the most glamorous part of accounting, it is the last line of defense to identify errors and/or fraud and hence a critical organizational process. I also realized that existing platforms that have automation in this area are priced quite high, and often beyond reach for mid-sized companies.

Mid-sized companies are often operationally complex, and can benefit from automation during the close, but may lack the excess capacity and resources to make a large investment and undergo a multi-month implementation. This realization became the spark that compelled me to found SkyStem, a SaaS provider that aimed to create an affordably priced solution to help automate month-end closes and reconciliations.

SkyStem’s flagship solution, ART, was brought to the market shortly after. ART’s main purpose is to modernize the month-end close and reconciliation process through automation. It was designed to meet four criteria: robust in features, easy to use, fast to implement, and reasonably priced. SkyStem’s core belief is that software should be robust, but never break the bank or cause unnecessary business disruption.

We have a heavy financial services presence in our customer roster which is where we got our start but have expanded into a variety of industries since then. We service public and private companies mostly in the mid-size space. We are obsessed with customer service and have enjoyed building out the product to feed into what customers really need. We have users in over 15 countries and look forward to more innovation in our product and in the industry.

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What book inspired you through your entrepreneurial journey?

I read a lot of books during the initial creation of SkyStem, but the book that stands out the most is “The Founders Dilemma” by Noah Wasserman. It was specifically relevant due to the tech nature of our business.

Founders often struggle with the best course to take in terms of investment, how to get co-founders, equity distribution etc. To take money or not to take money was personally my biggest dilemma. This book objectively discusses the pros and cons of taking outside capital. There is no right answer but there is an answer that feels right for an individual and the type of business they are pursuing.

This book covers all major milestones that occur during the lifecycle of a company and it was a great go-to book to remind yourself what options there are and how to navigate through that.

What inspired you to start Skystem and what were the main challenges you faced?

SkyStem began with a $4 billion dollar problem. I discovered broken internal controls while consulting at a troubled financial services giant, resulting in the balance sheet of over 10,000 accounts being off by billions of dollars.

This didn’t just happen overnight. Years of manual inefficiencies, the absence of consistent processes, and the lack of a centralized repository for spreadsheets and documentation created the monster. As a CPA and CIA, I experienced this situation and its recurring issues from both sides. I had empathy for accountants, understanding they were often working late nights with limited resources, and sympathized with auditors, who needed to hold companies accountable to the public.

The business spent a full year and millions of dollars fixing a mess that could have been prevented. Life would have been so different if there had been automation infused in this process. I realized that even large companies were grappling with manual processes despite having the resources. It made me think of how inaccessible automation was to those who didn’t have big budgets and how much they could benefit. Shortly thereafter, SkyStem’s flagship solution, ART, was born.

ART is a B2B SaaS product developed to help mid-market companies automate and streamline their month-end close. It was made with affordability and customer service as pillars of its ethos.

According to a recent industry study, financial executives waste 21.8 hours a week on repetitive tasks, but when you automate them, you set up your employees for more strategic work.

How do you see automation capabilities solving the productivity issues in the financial services industry?

Automation is a key to survival for companies. It has become a necessity rather than a nice to have and now provides a competitive edge. We work in the accounting space for month-end close automation but the benefits for automation in any area would provide similar benefits.

Here are some key benefits of adopting software/automation:

• Streamline  processes and create disciplined workflows
• Make it easier to review results for accuracy
• Embedded automation within reports means that they can be generated quickly and easily, eliminating the need to manually enter data and create them
• Reduce the risk of error or miscommunication

Companies are less prone to data loss due to power outages, as cloud-based systems automatically store data securely. Additional benefits include:

• Saves time spent on manual tasks, writing emails, following up
• Helps to reduce costs by eliminating the need to hire additional staff
• Obtains real-time information as it happens

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What are the new skills required to thrive in the evolving financial landscape in the Generative AI era?

Changes in customer expectations, and shifts in regulatory environments, demand a set of skills that go beyond traditional financial skills. Here are the top 3 skills that I believe could be a great add-on to traditional financial skills.

Data Analytics and Data Science – Skills in data analysis, including proficiency in data visualization, statistical analysis, and machine learning, are increasingly valuable. Financial professionals who can extract insights from large datasets are in high demand.

Digital Literacy – A strong understanding of digital tools, software, and platforms is crucial. This includes proficiency in using financial software, understanding blockchain technology, and navigating digital banking systems.

Coding and Programming – Basic programming skills, particularly in languages like Python and R, can be highly beneficial. They enable financial professionals to automate tasks, build financial models, and work with data more effectively.

Could you please throw some light on the modern digital literacy tools?

With so many digital literacy tools, we can take control of our own education for a myriad of topics without having to enroll in a college/school, etc. It’s been a boon in helping people stay connected and up to date with information that they need to enhance their skills and pursue all types of careers.

Modern digital literacy tools cater to a wide range of skill levels and areas of interest. Whether you’re a beginner looking to improve basic computer skills or an advanced learner seeking to develop coding proficiency, there are resources available to help you enhance your digital literacy. Education via these tools has been game-changing for any type of learning.

Although there are countless numbers of portals and tools in the market a few to note are as follows:

• Udemy –  Features a diverse collection of courses on digital literacy, computer basics, and software applications.
• Coursera –  Offers a wide range of online courses, including digital literacy and technology-related topics.
• Online Webinars and Workshops – Many organizations and institutions host webinars and workshops on various digital topics.
• Khan Academy –  Offers courses in computer programming, computer science, and mathematics.

Please share your thoughts on the organic and inorganic growth marketing strategies in the tech domain for SkyStem.

For now, we have focused most of our efforts on organic growth. We are a customer-funded company and are very proud of that. Our organic strategies have focused on 2 areas primarily:

• Product Development – we continue to build out our product by adding features and modules that continue to help accounting teams. Much of our roadmap is determined by our customers as we proactively solicit feedback and have made it a company goal to have at least 30% of our build comprise customer requests.
• Market Expansion – Starting last year we have seen an increase in international inbound inquiries. And although we have users in over 15 countries, we have not proactively targeted markets outside the US. Recently, we signed a large deal with a company headquartered in the Netherlands and this will begin our journey in the geographical expansion of SkyStem.

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What are your predictions for the future of FinTech?   

Fintech is a hot and lucrative space so there is bound to be a variety of growth, either directly or tangentially in this industry. The main prediction that seems imminent is the introduction and enhancement on Fintech products to take them further in helping humans do their jobs. This will definitely impact the products that SkyStem develops.

Other high level predictions include things like –

• Moving away from traditional banking to digital banking only
• AI-powered advisors (Robo-Advisors) that will be able to guide users through investment decisions
• Digital wallets and mobile payments will continue to replace cash even further
• There will be more banked people all over the world

With the advent of the above, there will be a need for more regulation and oversight with which will come different types of jobs and careers. 

Thank you, Shagun! That was fun and we hope to see you back on AiThority.com soon.

Hi Manish, welcome to our interview Series. Please tell us about Reltio’s core offerings.

At Reltio, we have been helping financial services and insurance companies modernize and transform their businesses for several years. We work with large and mid-sized companies like Fulton Bank, helping them achieve a full 360 view of the customer across core banking, compliance, and digital channels, including entity-to-entity relationships and the ability to enrich the data with, among other things, advanced analytics and real-time data collection for sales representatives leading to improved customer satisfaction.

Recently, we expanded our commitment to our financial services and insurance clients – and the industry as a whole – with customized, pre-configured models for both industries: Reltio for Financial Services and Reltio for Insurance. We call these solutions “velocity packs” because they help organizations speed time-to-value for their modern data management (MDM) transformations. The velocity packs come with pre-built configurations, integrations, and other assets specific to the financial services or insurance industries, which significantly slashes implementation time – from potentially years to just weeks. These products make collecting, unifying, and enriching core data much easier. The built-in, intuitive, low-code/no-code integration tools let business leaders begin using real-time data to drive business outcomes far more quickly than traditional MDM solutions.

What can Reltio do for its client business? Please highlight your modern multi-cloud platform.

I launched Reltio, the industry’s first cloud-native SaaS MDM platform, in 2011 when I recognized that companies in every industry need to unify siloed information, data, and applications in a trusted, timely way. I understood then that the cloud was the ultimate opportunity for all to transform their businesses and remain competitive in today’s digital-first world. Most large companies have significant challenges gaining value from their data because it is “siloed” or trapped inside their legacy systems.

Fixing this problem via traditional methods became overly complicated, time-consuming, and expensive and failed to deliver the results needed for these transformations.

Reltio provides clean, connected, high-quality, and actionable data that analysts, data scientists and business users can trust to give them accurate, up-to-date insights. This lets leaders and experts focus on growing revenue, becoming more efficient, and improving risk management rather than finding, merging, and fixing core data. Reltio does everything for them in a user-friendly way and in real-time, which has been a game-changer for our customers.

Our multi-cloud strategy allows businesses to choose the best-of-breed solutions from different providers and minimizes the risk of disruption. An enterprise can protect its systems and ensure business continuity by using multiple cloud providers and building redundancies, which is particularly important for mission-critical systems that must be up 24/7. Reltio’s platform is multi-cloud which simplifies data unification across an organization, allowing great flexibility and helps us meet our customers where they want to be.

You entered into partnership with Google to streamline the consolidation, and data enrichment in real-time through master data management (Google BigQuery).

Could you please explain your strategies behind this?

Reltio’s partnership with Google Cloud addresses the problem of data fragmentation and poor data quality head-on. We are simplifying the process of harnessing, cleansing, and unifying core data sets — like customer data — from various sources and creating a single source of trusted data directly within Google Cloud BigQuery through an integrated and automated experience.

Reltio enables customers to unify their data in BigQuery easily and helps them deliver better outcomes using clean, trusted, real-time data.

How is Artificial Intelligence playing its role for your company?

What more are you expecting out of the tech domain?

We view AI/ML through several lenses, including a capability within our platform and a challenge our customers are trying to solve. As organizations across every industry integrate AI/ML tools in various ways, there is a significant and growing need for clean, connected, and accurate real-time data for feeding those models. The performance of an AI/ML model heavily depends on the quality of the data it is trained on. The model’s predictions or classifications can be wrong if data is inaccurate, biased, or incomplete. “Garbage in, garbage out” is the phrase we commonly use at Reltio to convey the significance of trusted data in the context of AI/ML.

We also integrate ML capabilities into our product to streamline and enhance the process of core data unification.

Our teams have incorporated AI and ML tools into our platform for years.

Most recently, we launched our 2023.2 release upgrades, which include augmented entity resolution capabilities with the industry’s first pre-trained ML models. As application proliferation grows exponentially across organizations, unifying data across siloed sources becomes increasingly challenging. Many organizations deploy teams of data stewards to manage this through manual processes. ML significantly speeds up the process and frees up the time of data stewards to work on more value-added projects.

Reltio’s Connected Data Platform provides trusted, high-quality matching recommendations out of the box and in a fraction of the time and cost previously required.

It’s 2023, and one needs a data management solution that scales with changing regulatory landscapes as regulators create more privacy protection.

How are you dealing with it?

Our philosophy is that Modern Data Management platforms should organically support the key elements of regulatory frameworks in every jurisdiction and in every context around the globe.  One key step is to ensure that data is stored in a location that complies with the relevant laws and regulations. This may involve working with cloud providers or other third-party vendors that can provide appropriate data storage solutions. Another important step is to develop appropriate data management policies and procedures that comply with the relevant data protection laws and regulations.

Our platform ensures that organizations can store and manage their data in compliance with relevant local laws and regulations. This includes coordinating or directly managing local data centers to ensure data is stored in compliance with requirements. These local facilities understand the local policies and update their business continuously according to all local and residency policies, each with robust data management procedures to protect sensitive data from unauthorized access. Reltio can protect sensitive data and comply with data sovereignty regulations, no matter where our customers operate. Not all data sovereignty regulations are the same or limited to data privacy. Many countries restrict where data can reside, and some even restrict the ability to view private data from outside the country.

Regardless of the regulatory environment in which our customers operate, we are committed to helping them achieve and maintain compliance.

What are the key trends that are changing the digital landscape for 2023-24?

Not surprisingly, there have been significant advancements in AI and ML within data management platforms within the last year. I expect to see even more growth and innovation in AI and machine learning technology.

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As seen with our AI product release or others from Salesforce and IBM, AI has already made a mark on the community, and more updates are promised for users.

In addition to AI and ML, I expect to see templatized, and low-code / no-code data solutions become more widely adopted. These easily customizable services are faster to implement and save money for businesses. In the current economic climate, companies, and business leaders are lowering operational costs anywhere possible, including replacing legacy tech solutions and platforms. These legacy solutions transition to new, less expensive products with a fast onboarding process and less long-term maintenance.

Beyond the faster integration, these solutions must also be easily scalable for any sized business. With simple adoption and scalability, business owners and leaders can realize these data points and understand the long-term impacts quickly.

One of the biggest challenges retail businesses have today is delivering a truly omnichannel experience to their customers.

How are you overcoming this issue?

Retailers can dramatically improve customer experience using cloud-based data solutions that unify core customer data in real-time, and transform their business.

With Reltio, our customers can make high-quality recommendations, experience a seamless history of each customer, and truly understand and anticipate what they might need or want.

Across industries, data is partially or completely transitioning from on-premise to cloud storage. While cloud solutions improve the overall customer experience, they also demand better security and must avoid creating low-quality data or data silos.

Large and small retailers use multiple applications and services, and their data is created there, but many applications don’t verify data quality or integrate with other apps. These missteps generate fragmented data, and teams can waste time and money fixing serious problems. That’s why modern data management solutions with AI-fueled entity resolution are so necessary.

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As per recent statistics, there is a hacker attack every 39 seconds, what are your strategies to deal with this situation where security is being compromised?

Similarly, with regulatory standards, data privacy and security are a top priority for any data management company. Our products are consistently updated to protect against attacks, and our security teams work with customers night and day to ensure their data is safe. As we also operate Reltio in the public clouds, our customers can leverage the billions of dollars invested in the security, expertise, and infrastructures of AWS, Azure, and GCP.  As these services are so large and universal, they have set the industry standard for security.

Companies moving and storing data in the cloud can leverage best-in-class and the highest standards in today’s landscape.

What technology have you leveraged to improve models using real-time data?

Could you explain to our readers with an example?

The importance of real-time operations cannot be overstated, especially for B2C companies.

Access to updated customer data across all channels in real time allows businesses to offer a consistent and connected customer experience. This increases customer retention, loyalty, wallet share, and facilitates seamless cross-channel experiences, such as online orders with in-store pickups or returns. Moreover, a unified and mastered product data system means new product data can be input once and instantly made available across all consumer-facing systems, paving the way for synchronized product launches across various channels, including mobile, web, and in-store.

CarMax, a leading retailer in the used auto sector, set out to redefine automotive retail with an unwavering focus on integrity, honesty, and transparency. To support fast-paced and responsive customer interactions across an ever-expanding digital landscape, CarMax aimed to seamlessly integrate a myriad of legacy and cloud-based applications, emphasizing the necessity of real-time operations where data, even 15 minutes old, was considered outdated.

The Reltio Connected Data Platform was implemented to integrate CRM, POS, and other vital systems, enabling CarMax to achieve real-time operational capabilities.

As a result of implementing the MDM solution, CarMax witnessed transformative outcomes. It provided a personalized and interconnected customer experience across all touchpoints, free from data duplicity and inaccuracies. This allowed it to swiftly adapt to shifting consumer needs, as evidenced by its introduction of new services such as curbside pickup during the COVID pandemic.

Furthermore, CarMax could confidently rely on consolidated source data for auditing and set the stage for future data-centric projects.

Summing up the strategic value of the Reltio platform, it was highlighted that Reltio stands central to CarMax’s customer interactions, acting as a linchpin in uniting all user experiences.

Tell us about some of the top tech events that you’ll be participating in (as a speaker or guest) in 2023-2024.

In October, Reltio is co-sponsoring DataDriven24, a Modern Data Management Conference, in Dallas, Texas. I will be speaking on modern data management, the role of AI/ML in the tech landscape. We’re also bringing in luminaries in the data field, including DJ Patil, former U.S. Chief Data Scientist from 2015-2017, Bill Schmarzo, known as the Dean of Big Data, and Inderpal Bhandari, IBM Global Chief Data Officer.

We will also have practitioners and professionals from Liberty Mutual, Fulton Bank, Google, HPE, and Workday as panelists and moderators.

Thank you, Manish! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]

Hi Cory, welcome to AiThority.com’s Predictions Series interview. You have witnessed the technology industry grow into a multi-billion dollar economy in 2023.

Please tell us about your fintech journey. What is your current role at Blackhawk Network (BHN)?

Throughout my career, I’ve focused on creating innovative products and product experiences that push the status quo on a global scale. I’ve held senior leadership roles across several Fortune 100 organizations including Visa, Citibank, Bank of America, and PayPal, in addition to roles at Green Dot and Lively.

At Blackhawk Network (BHN), I lead the organization’s aggressive efforts to leverage payment technologies to deepen the connections between people and brands they love. As a digital payments expert, my focus is to help drive customer acquisition and deepen engagement, at scale, by developing new products and product experiences.

Please tell us something about your company Blackhawk Network (BHN). What are your core offerings?

BHN is the leader in global branded payments. For more than 20 years, BHN’s mission has been to connect brands with their customers, employees, and partners. During that time, we’ve built a platform that drives those connections, at scale, in 32 markets.  We deliver hundreds of brands to consumers through hundreds of thousands of physical and digital commerce locations. Our services include Gift Card and eGift products, promotion and distribution, rewards & incentives, payment acceptance, loyalty solutions, and mobile applications, all to enhance those connections.

How do you leverage artificial intelligence to make payments seamless? How is it beneficial for Fintech customers?

We’re just beginning to scratch the surface of how fintech organizations will be able to leverage AI to make payments even more seamless. One of the most beneficial uses for BHN and in the industry is—and will likely continue to be—fraud detection and prevention.

AI-powered algorithms for Fintech decision-makers can more quickly and thoroughly analyze payment data in real-time to detect and identify suspicious patterns or even come up with the best protection methodology to use to secure consumer data. This will provide an additional layer of security to protect against fraudulent activities and safeguard organizations and consumers.

However, another way we are exploring AI is to improve recommendations and considerations.

Ensuring that a gift or a reward for an employee generates the right impact is not always easy, even for those we love or know well.  AI will be another way to leverage data to improve choices and make any reward or gift more enjoyable for the recipient.

The prepaid card sector is doing its part by streamlining an evergreen payments product, making it more convenient for consumers regardless of what channel they’re shopping in. What are your thoughts?

Prepaid cards are already one of the most inclusive and ubiquitous payment options and offer convenient ways to connect gifts, budget tools, disbursements, rewards, and even payments from employers. However, it’s no surprise that we are in the middle of a massive shift in the way consumers research, shop and connect with others so even though friction is disappearing with more streamlined processes, we are still seeing a few trends worth paying attention to.

With more than 5 billion people having access, the internet now connects more than 60% of the world’s population, according to a 2023 Digital Snapshot by DataReportal. But what we consider to be the internet is also changing. What was dominated by websites, email, and large screens is evolving into chat, messaging, video, and smartphones.

More than 95% of consumers use chat or messaging versus 49% using email.

About 15% of internet users use messaging and live chat to research brands in addition to more than a billion people now using social media to find products.

Consumers are also increasingly relying on other people for information and advice when they are looking to buy something rather than traditional search engines. Data from GWI Core shows that this gap has narrowed for all users over the last seven years but has already been flipped for a few years when it comes to Gen Z, who look to their favorite influencers more than traditional search. People are also spending more time in gaming and virtual experiences and brands are looking for ways to establish themselves in these channels and exploring how to transact in these venues.

Because of these meaningful shifts, we all have to continue to figure out how to be relevant in this space and streamline experiences, contextually adding capabilities in the newer channels where people are shopping and interacting with each other. The good news is—in addition to the traditional ways of driving people to websites, like ads—messaging platforms have evolved to allow third-party integration and become super apps. We now have ways to put gifting and rewards right where people are sending birthday wishes or giving virtual high-fives to one another.

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How according to you will the fintech segment evolve in the coming years?

Which industries will benefit most from the latest fintech innovations?

Embedded finance will become more prevalent, enabling non-financial organizations to integrate financial services into their offerings seamlessly, including embedded payments and rewards. The technology already exists that will marry into existing software platforms and allow organizations to embed payments and rewards into user experiences for a variety of use cases, but adoption will expand.

Leveraging intelligent apps or APIs enables brands to dole out digital rewards people can access from anywhere which translates into real-time reinforcement and deep customer insights that can help tailor future interactions and promotions and frequent touchpoint opportunities.

A wide range of industries are likely to benefit from the expanded use of embedded finance, but eCommerce and retail will be among some of the biggest beneficiaries. Embedded payments and rewards allow eCommerce platforms and retailers to offer integrated payment options, personalized financing and loyalty programs directly through their websites or mobile apps, enhancing the checkout process, improving overall customer experiences and boosting conversion rates for online businesses.

Beyond brands and merchants, for almost any organization, instead of having to invest in yet another expensive platform to reward and engage employees or customers, they can insert a rewards app right into the tech tools they are already using for day-to-day business. Microsoft Teams is one prominent example of this—it now offers a BHN Rewards app, allowing teams to issue instant rewards during group and private meetings, as well as chats, via eGifts.

What are some of the biggest challenges you face when marketing your new idea and trying to improve the overall customer experience for them?

Often the biggest challenge is simply technology fatigue, brought on by the overwhelming abundance of new and constantly changing technologies. Gartner predicts that global IT spending will total $4.6 trillion in 2023—a 5.1% increase from last year. The 2023 Zylo SaaS Management Index Report found that even organizations with fewer than 500 employees have a staggering 172 SaaS subscriptions on average.

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APIs will continue to lead the way in digital transformations, but many organizations don’t realize that APIs can help get more out of the tech stacks and subscriptions that they already have.

Many organizations are feeling the strain of global economic challenges, and optimizing existing tech stacks is a smart, strategic way to streamline resources, reduce training time and time spent switching between platforms, and help protect budgets.

Effectively using and streamlining the technology already at an organization’s fingertips allows businesses to reach people in more powerful ways.

We’d love to know what are your predictions for the AI in Fintech domain for 2030.

Predicting tech innovations and advancements is challenging with the rapid evolution that has taken place over the last few years, but some developments that I think are likely to take shape for the tech domain over the next decade include:

AI regulation: As AI gets embedded in more aspects of our lives, ethical considerations, transparency and a need for regulation will all become more prevalent to address potential biases and create guardrails for responsible AI deployment.

Climate-focused FinTech: FinTech will also need to focus on sustainable finance and climate-related initiatives, with eco-friendly manufacturing processes, sustainable materials, and overall ESG considerations growing more prominent.

Expanding financial inclusion: With wider mobile wallet adoption, FinTech will continue to play a significant role in expanding financial inclusion through mobile-based solutions for non-banked and under-banked consumers.

Thank you, Cory! That was fun and we hope to see you back on AiThority.com soon.

[To share your insights with us, please write to sghosh@martechseries.com]