Companies have many things on which they must focus each day. From staying on top of the latest financial trends, to workforce scheduling, to ensuring that they have products of the highest quality, every element is crucial. At the top of the list, though, is customer satisfaction. Keith Strier at EY Global understands that it is critical for companies to be “ethical” while keeping their customers first. That is why Keith and his team make it a priority to provide AI solutions that meet their clients’ needs, no matter how complex. With their expert advice, Keith and EY Global are clearing the paths for “purpose-driven services” to help their clients reach their goals.

Tamara: Can you share a story that inspired you to get involved in AI?

Keith: In the summer of 2016, I was in a shopping mall, looking around for one of those wall maps so I could locate a store, but I had no luck after wandering for ten minutes. Then I saw a poster that advertised, “Can’t find a store? Text us and our bot will help.” I had nothing to lose, so I stopped walking in circles, and texted the bot, “Where’s the pharmacy?” The response back was fast, and personalized (to my location), providing perfect directions. I followed up with a second question, “What are the options in the food court?” and was again quickly rewarded with a list of dining choices. I was hooked. I knew right then that AI, the ability to talk with machines, to ask questions in a natural way, was the future. I also thought it would be cool to end the tyranny of mall maps.

Tamara: Describe your company and the AI/predictive analytics/data analytics products/services you offer.

Keith: EY is a global professional services firm that assists clients in the public and private sectors along the entire AI journey with services that include implementing foundational data management programs, developing enterprise AI strategies, prototyping AI use-cases and designing anticipatory user experiences as well as the hands-on coding, training, scaling and continuous monitoring of algorithms and models. EY also helps clients apply AI across the value chain in every domain, from cognitive tools that automate complex procurement processes to predictive models that optimize public transportation systems, from media and mining companies to law enforcement agencies and water authorities.

Tamara: How do you see the AI/data analytics/predictive analysis industry evolving in the future?

Keith: AI will become increasingly more democratized and accessible through innovative interfaces and cloud services. The first wave will be force multipliers for data scientists, tools that make their jobs easier, automating menial tasks, like data cleansing and feature extraction. The second wave will be more disruptive, expanding use-cases and the user-base by making data science possible without a data science degree. This will ignite widespread adoption at the business level, outside of IT and the Analytics team. We already saw this play out over the last decade with mobile apps. Initially, building an app was a real chore, requiring a team of highly trained developers, architects, designers, and testers. Today, a 12 year old can assemble a high-functioning mobile app and submit it to the app store in minutes, using any number of DIY “app builder” platforms. This has already started to happen, in fact, with the rise of DIY chatbot platforms that require little to no coding.

Tamara: What is the biggest challenge facing the industry today in your opinion?

Keith: This is a complex space with many challenges, but there is perhaps one fundamental challenge – widespread misunderstanding around the nature of AI. AI is not implemented like a mature technology; rather, AI is emergent and must be applied, leveraging a spectrum of methods, tools and knowledge domains. In this nuanced description lies a world of implications for how AI – apart from other technologies – should be evaluated, developed, prototyped, tested, integrated, scaled, governed and monitored over time to ensure performance, reliability, accountability and explainability. Many companies do not have this understanding and approach AI with a more classic IT mindset that sets the stage for unmet expectations and poor outcomes. However, this is an addressable issue and the collective responsibility of advisory firms, systems integrators and service providers. As well, industry and professional associations have this responsibility along with the need to clarify and forge a common view and vocabulary.

Tamara: How do you see your products/services evolving going forward?

Keith: EY’s end-to-end AI advisory services must stay current with a dynamically evolving space, which requires a relentless commitment to scanning, learning and experimenting. Moreover, this isn’t “one space”, but an amalgam of landscapes. It includes the actions of business leaders, data scientists, service providers and entrepreneurs working across adjacent fields (robotic, intelligent and autonomous systems). I expect that EY’s portfolio of AI capabilities and solutions will keep evolving in lock-step with academic, commercial and regulatory advancements.

Tamara: What is your favorite AI movie and why?

Keith: I don’t have a favorite AI movie, but I have a favorite AI scene. It’s from the animated show, Rick and Morty, in which Rick is this super-genius who frequently designs robots to serve his every need. In one scene, Rick is eating dinner, and there is a small robot on the table serving him butter. This tiny robot starts to share his dreams about doing more, revealing his hope for a bigger purpose. However, Rick shuts him down: “Your purpose is to serve me butter. That’s it. You will always serve me butter.” At that moment, this tiny robot realizes the narrow, pointless nature of its existence, saying with despair: “OMG.” For most normal people, it was just a funny scene about a robot that’s really upset that its life revolves around butter. For me, the scene cleverly reveals one of the more fundamental challenges with AI, which will be understanding how best to apply it. Of course, learning that it was and will always be a butter-serving robot was devastating for the little machine, but in the real world, it will be essential to design AI systems with a clear and focused intent. Perhaps not so much fun for them, but the highest value machines will have the most tightly scoped purpose.

Tamara: What type of advice would you give my readers about AI?

Keith: Don’t fear the rise of AI and smart machines; take the time to understand the full narrative. Despite the movies, the most likely scenarios are much less cinematic. Stunning improvements in diagnostic accuracy, energy efficiency, manufacturing quality and workplace productivity will materialize, as human and machine capabilities are more deeply integrated and scaled in every context. For sure, mistakes will be made along the way, some AI systems will not perform as engineered. For this reason, we also need to understand not only the potential value but also the potential risks, and to design these systems to be ethically-aligned, transparent, accountable and explainable. Ultimately, however, I believe humanity will be greatly improved through the increased reliance of algorithms in every field from medicine to transportation to public safety.

Tamara: How does AI, particularly your product/service, bring goodness to the world? Can you explain how you help people?

Keith: EY advises the world’s leading private sector companies as well as many governments around the world on how to apply AI, and when doing so, we educate our clients on the importance of anchoring to key design principles that promote a human-centered and ethical approach. As with sustainability, diversity and inclusiveness, promoting responsible uses of AI is consistent with EY’s purpose-driven culture. We aspire to help large enterprises and public agencies achieve their objectives, but also to help them stay informed of the potential disruptiveness of these technologies and to plan appropriately for their integration into a human workforce. In this way, EY helps to build a better working world through purpose-driven AI services.

Tamara: What would be the funniest or most interesting story that occurred to you during your company’s evolution?

Keith: The most interesting story in this area was learning that EY was not only building up capabilities in this space, but was already one of the largest consumers of intelligent automation within its core operations and business. That is, EY has built and deployed over 600 software robots, saving millions of hours of work for thousands of EY employees, enabling them to do their jobs better as they run our day to day operations in HR, finance, procurement and tax. EY is in fact one of the most automated enterprises in the world, among the top ten earliest adopters of robotics and AI at scale, which is a surprising revelation to those who see EY as just an “accounting firm.”

Tamara: What are the 3-5 things that most excite you about AI? Why? (industry specific)


  • AI will accelerate scientific discovery by orders of magnitude, enabling us to discover new galaxies and cancer treatments.

  • AI will create unprecedented levels of public safety, enabling models to predict natural disasters much earlier and to respond to emergencies much faster.

  • AI will transform the boundaries of human abilities, equipping those without sight with AR/AI systems that see for them, and enabling machine-to-brain interfaces that power a new generation of sensory-rich prosthetics.

Tamara: What are the 3-5 things worry you about AI? Why? (industry specific)


  • AI is just math at enormous scale, and its potency as a tool for dramatic change in every facet of our lives is not a function of some unseen, uncontrolled, mythical force; it depends entirely on our decisions and actions. Nothing worries me about AI specifically, only what we do, or don’t do, with it. This includes:

    • Lack of planning that leads to failed AI programs and disillusioned executives, delaying the realization of value for shareholders and customers

    • Poorly designed AI systems, governance models and training approaches that lead to biased and/or unreliable outcomes

    • Failure to passionately pursue AI use-cases that could meaningfully improve the human condition out of fear and misunderstanding.

Tamara: Over the next three years, name at least one thing that we can expect in the future related to AI?

Keith: The inevitable integration of AI into everything – within three years, we will be gesturing to televisions, talking to toasters and accessing financial data with a facial expression. However, it is likely that we’ll still be sitting in traffic and shuttling our kids all weekend between friends, the mall, the field, among others things. All the while, we will be counting the days to the arrival of autonomous, if not aerial vehicles.