<description>Remember Shadow IT? This has long been an issue in big organizations, and in the era of generative AI — with its powerful, easy-to-operate, democratically available tools — the challenges have scaled, as one says in the vernacular. 

One person who has successfully met these challenges is Eric Pace, Head of AI at Cox Communications, who created an interesting and effective citizen developer program at his organization. He brings news of this to *The Resonance Test* in a conversation with Elaina Shekhter, EPAM’s Chief Marketing and Strategy Officer.

Shekhter begins by asking about the citizen developer model around the development and deployment of agents in the enterprise. 

One of the keys to unlocking value in any ecosystem is through adoption,” says Pace. But adoption, in this case, “hinges on one very important thing, and that's AI literacy.”

To accomplish this, Pace and his team gave their colleagues hands-on experience with the tools and capabilities that AI provides. They had access, guardrails, guidelines and references to follow.

Pace notes that he had two paths: (1) “We could either tell them everything is locked down and you can't do any of it” or (2) tell colleagues, “You can play in this open playground and just follow our rules and do all the things you want to go do.” He chose the second option, and it turns out, his people are “very happy in the playground with the fence around it, that we built for them, because it's got all the tools and toys that they need.”

All of which is great… but what does it mean for the business? 

“All the executives read are these articles about the trillion dollars that's being spent and the zero impact to the bottom line,” says Pace, adding that CFOs are mostly saying, “Stop wasting all our money.”

Pace correctly says that there is “no instant gratification” involved here. “The notion that I can ask a very complex question and instantly get a very complex answer sets the perception that I can just go implement at scale enterprise-grade capabilities and get value out of them tomorrow.”

Shekhter and Pace agree that this isn’t how things work, especially, says Pace, “When you take into account the change management adoption and process curves that you've got to crawl through to see the value come to fruition.”

Pace reports the projects his citizen developers have created “have absolute potential to go drive the value that we've prescribed as possible in a very near future.”

Listen, and improve *your own organization’s* journey. 



Host: Alison Kotin
Engineer: Kyp Pilalas
Producer: Ken Gordon

</description>

Remember Shadow IT? This has long been an issue i…

Remember Shadow IT? This has long been an issue in big organizations, and in the era of generative AI — with its powerful, easy-to-operate, democratically available tools — the challenges have scaled, as one says in the vernacular. 

One person who has successfully met these challenges is Eric Pace, Head of AI at Cox Communications, who created an interesting and effective citizen developer program at his organization. He brings news of this to *The Resonance Test* in a conversation with Elaina Shekhter, EPAM’s Chief Marketing and Strategy Officer.

Shekhter begins by asking about the citizen developer model around the development and deployment of agents in the enterprise. 

One of the keys to unlocking value in any ecosystem is through adoption,” says Pace. But adoption, in this case, “hinges on one very important thing, and that's AI literacy.”

To accomplish this, Pace and his team gave their colleagues hands-on experience with the tools and capabilities that AI provides. They had access, guardrails, guidelines and references to follow.

Pace notes that he had two paths: (1) “We could either tell them everything is locked down and you can't do any of it” or (2) tell colleagues, “You can play in this open playground and just follow our rules and do all the things you want to go do.” He chose the second option, and it turns out, his people are “very happy in the playground with the fence around it, that we built for them, because it's got all the tools and toys that they need.”

All of which is great… but what does it mean for the business? 

“All the executives read are these articles about the trillion dollars that's being spent and the zero impact to the bottom line,” says Pace, adding that CFOs are mostly saying, “Stop wasting all our money.”

Pace correctly says that there is “no instant gratification” involved here. “The notion that I can ask a very complex question and instantly get a very complex answer sets the perception that I can just go implement at scale enterprise-grade capabilities and get value out of them tomorrow.”

Shekhter and Pace agree that this isn’t how things work, especially, says Pace, “When you take into account the change management adoption and process curves that you've got to crawl through to see the value come to fruition.”

Pace reports the projects his citizen developers have created “have absolute potential to go drive the value that we've prescribed as possible in a very near future.”

Listen, and improve *your own organization’s* journey. 



Host: Alison Kotin
Engineer: Kyp Pilalas
Producer: Ken Gordon



The Resonance Test 102: Creating Citizen Developers with Eric Pace

<description>"The chaos we're seeing is really a reaction to the fact that the regulators have floated these enormous boats that are gathering tons of data, over 100,000 points of data in the EU alone. And they've now cut across that with a simplification directive," says PJ Di Giammarino, CEO of RegRisk, as our panel of experts settles in.

Di Giammarino is joined by Michael Nicholls, Principal of Financial Services Consulting at EPAM and Chris Owers, a Senior Director at First Derivative. Together, the trio has decades of experience in consulting and navigating the rigors of regulatory compliance.

Chaos isn’t a word you want to hear when discussing compliance with pending regulations, especially in the financial services sector. But it’s become a reality for thousands of banks across Europe and the UK thanks to last-minute pivots and sharp turns in dual-tracked MiFID 3 regulations originating from both regions. Meant to drive standardization in trade and transaction reporting, regulators from both regions have had to pump the brakes as the intent of their proposals bumped up against reality, resulting in a temporary pause.

"I think a lot of people breathed a sigh of relief. There is a lot of complexity in what's being proposed. I don't think it was a complete surprise if you look at what's happened with other regulations,” says Nicholls.

Owers follows this up with a question on how the differences between the UK and European versions – a divergent approach to regulation – are tangibly impacting clients. Nicholls responds, “if you're in a two-tier, two-speed environment where you've got to satisfy regulators in the EU and regulators in the UK, and those regulators become increasingly divergent no longer aligned, you’re going to need more complex systems, data and processes to deal with two environments.”

With this, the conversation shifts into how organizations can deal with these complex systems, touching on everything from technology and AI to the shortage of talent within the industry that’s both tech-savvy and versed in regulatory compliance. Ultimately, however, our speakers leave the conversation on a positive note, confident that today’s sprint toward AI can help organizations to even the odds in the great regulatory compliance race. As Giammarino says: “This is a time for organizations to put in robust proofs of concept and begin scaling so they can turn the rulebook into a runbook.” Listen carefully, and watch out for galloping insights! 

Host: Chris Tapley 
Engineer: Kyp Pilalas 
Producer: Scott MacAllister 
Executive Producer: Ken Gordon 
</description>

"The chaos we're seeing is really a reaction to t…

"The chaos we're seeing is really a reaction to the fact that the regulators have floated these enormous boats that are gathering tons of data, over 100,000 points of data in the EU alone. And they've now cut across that with a simplification directive," says PJ Di Giammarino, CEO of RegRisk, as our panel of experts settles in.

Di Giammarino is joined by Michael Nicholls, Principal of Financial Services Consulting at EPAM and Chris Owers, a Senior Director at First Derivative. Together, the trio has decades of experience in consulting and navigating the rigors of regulatory compliance.

Chaos isn’t a word you want to hear when discussing compliance with pending regulations, especially in the financial services sector. But it’s become a reality for thousands of banks across Europe and the UK thanks to last-minute pivots and sharp turns in dual-tracked MiFID 3 regulations originating from both regions. Meant to drive standardization in trade and transaction reporting, regulators from both regions have had to pump the brakes as the intent of their proposals bumped up against reality, resulting in a temporary pause.

"I think a lot of people breathed a sigh of relief. There is a lot of complexity in what's being proposed. I don't think it was a complete surprise if you look at what's happened with other regulations,” says Nicholls.

Owers follows this up with a question on how the differences between the UK and European versions – a divergent approach to regulation – are tangibly impacting clients. Nicholls responds, “if you're in a two-tier, two-speed environment where you've got to satisfy regulators in the EU and regulators in the UK, and those regulators become increasingly divergent no longer aligned, you’re going to need more complex systems, data and processes to deal with two environments.”

With this, the conversation shifts into how organizations can deal with these complex systems, touching on everything from technology and AI to the shortage of talent within the industry that’s both tech-savvy and versed in regulatory compliance. Ultimately, however, our speakers leave the conversation on a positive note, confident that today’s sprint toward AI can help organizations to even the odds in the great regulatory compliance race. As Giammarino says: “This is a time for organizations to put in robust proofs of concept and begin scaling so they can turn the rulebook into a runbook.” Listen carefully, and watch out for galloping insights! 

Host: Chris Tapley 
Engineer: Kyp Pilalas 
Producer: Scott MacAllister 
Executive Producer: Ken Gordon 


The Resonance Test 101: Navigating the Convoluted Web of Compliance

<description>When it comes to the topic of drug discovery and development, scientists are busy furrowing their lab-goggled brows trying to understand what’s real and what’s hype when it comes to the power and potential of AI. 

This *Resonance Test* conversation perfectly dramatizes the situation. In this episode, Emma Eng, VP of Global Data &amp; AI, Development at Novo Nordisk, and scientist and strategist Chris Waller provide a candid view of drug development in the AI era.   

“We're standing on a revolution,” says Eng, reminding us that “we've done it so many other times” with the birth of the computer and the birth of the internet. It’s prudent, she cautions, not to rush to judgement guided by either zealots or skeptics.

Waller says, of the articles about AI and leadership in *Harvard Business Review,* one could do “a search and replace ‘AI’ with any other technological change that's happened in the last 30 years. It's the same kind of trend and processes and characteristics that you need in your leadership to implement the technology appropriately to get the outcomes that you're looking for.”  

Which means, for pharma, much uncertainty and much experimentation. 

“I think experimentation is good,” says Eng, who then adds that we need to always keep track of what is it that we're experimenting on. She says that the word “experimentation” can “sound very fluid” but in fact, “It's a very structured process. You set up some very clear objectives and you either prove or don't prove those objectives.”

Waller references the various revolutions (throughput screening, combinational chemistry, data, and analytics revolutions) that pharma has seen and says: “We've all held out hope for each and every one of these revolutions that the drug discovery process is going to be shrunk by 50% and cost half as much. And every time we turn around, it's still 12 to 15 years, $1.5 to $2 billion.”

Will AI make the big difference, finally?

“Maybe we need to be revolutionized as an industry,” she says. “It can be hard to make much of a difference as long as there are few big players.” Just a few big players, she says, is “the nature of pharma.”

Of course, our scientists are measured in their assessments about industry change. After all, as Waller says, the systems involved—the human body, the regulatory environment, the commercial ecosystems—are all “super-complicated.”

Eng notes that an important side-effect around the AI hype is corporate interest in data. “Now it's much easier to put that topic on the table saying, ‘If you want to do AI, you need to take care of your data and you need to treat it like an asset.’”

Listen on as they test topics such as regional and regulatory challenges in AI adoption, change management, and future tech and long-term impact (watch out for quantum, everyone!). 
In the end, Eng returns to the idea of revolutions. “You think you want so much change in the beginning which you don't get because it takes time,” says Eng. This makes us underestimate what will happen later. Having such a farseeing mindset is significant, she says, because “these technology shifts will have a large impact on the long term.”

Host: Alison Kotin
Engineer: Kyp Pilalas
Producer: Ken Gordon</description>

When it comes to the topic of drug discovery and …

When it comes to the topic of drug discovery and development, scientists are busy furrowing their lab-goggled brows trying to understand what’s real and what’s hype when it comes to the power and potential of AI. 

This *Resonance Test* conversation perfectly dramatizes the situation. In this episode, Emma Eng, VP of Global Data & AI, Development at Novo Nordisk, and scientist and strategist Chris Waller provide a candid view of drug development in the AI era.   

“We're standing on a revolution,” says Eng, reminding us that “we've done it so many other times” with the birth of the computer and the birth of the internet. It’s prudent, she cautions, not to rush to judgement guided by either zealots or skeptics.

Waller says, of the articles about AI and leadership in *Harvard Business Review,* one could do “a search and replace ‘AI’ with any other technological change that's happened in the last 30 years. It's the same kind of trend and processes and characteristics that you need in your leadership to implement the technology appropriately to get the outcomes that you're looking for.”  

Which means, for pharma, much uncertainty and much experimentation. 

“I think experimentation is good,” says Eng, who then adds that we need to always keep track of what is it that we're experimenting on. She says that the word “experimentation” can “sound very fluid” but in fact, “It's a very structured process. You set up some very clear objectives and you either prove or don't prove those objectives.”

Waller references the various revolutions (throughput screening, combinational chemistry, data, and analytics revolutions) that pharma has seen and says: “We've all held out hope for each and every one of these revolutions that the drug discovery process is going to be shrunk by 50% and cost half as much. And every time we turn around, it's still 12 to 15 years, $1.5 to $2 billion.”

Will AI make the big difference, finally?

“Maybe we need to be revolutionized as an industry,” she says. “It can be hard to make much of a difference as long as there are few big players.” Just a few big players, she says, is “the nature of pharma.”

Of course, our scientists are measured in their assessments about industry change. After all, as Waller says, the systems involved—the human body, the regulatory environment, the commercial ecosystems—are all “super-complicated.”

Eng notes that an important side-effect around the AI hype is corporate interest in data. “Now it's much easier to put that topic on the table saying, ‘If you want to do AI, you need to take care of your data and you need to treat it like an asset.’”

Listen on as they test topics such as regional and regulatory challenges in AI adoption, change management, and future tech and long-term impact (watch out for quantum, everyone!). 
In the end, Eng returns to the idea of revolutions. “You think you want so much change in the beginning which you don't get because it takes time,” says Eng. This makes us underestimate what will happen later. Having such a farseeing mindset is significant, she says, because “these technology shifts will have a large impact on the long term.”

Host: Alison Kotin
Engineer: Kyp Pilalas
Producer: Ken Gordon

The Resonance Test 100: Emma Eng of Novo Nordisk

<description>“In French, we say when it’s raining at a wedding, it will be a beautiful marriage leading to a happy life,” says Syz Bank COO, Boris Chave. Reflecting on an announcement made on stage in 2023 alongside EPAM’s now-CEO Balazs Fejes during an afternoon storm in Geneva, Chave adds: “I think this rainy event was the beginning of a successful project and a happy partnership between Syz and EPAM.”  

Swiss banks have a well-known reputation for being protective of customer data, and Syz Bank is no exception. For years, the bank relied on on-prem servers and top-shelf security solutions to protect its customer data. However, the cost of those solutions was rising sharply, which led Chave to wonder if there existed a better solution. “The challenge with our setup was that even though we had these best-in-breed technology solutions, the ongoing investments we needed to make to protect our data just weren’t sustainable. I had to ask myself, should we continue down this path with its huge impact on P&amp;L? Not to mention I wasn’t comfortable with the complexity of our systems.” 

Fast forward to June of 2025, and EPAM has just finished helping Syz Bank migrate all its IT infrastructure to cloud-based systems, no small feat. As Fejes points out, “You got new notebooks, new applications, you migrated everything to the cloud. You basically built, de facto, a brand-new bank.” As Chave notes, not only did EPAM help Syz Bank navigate the cloud migration, but we did so with minimal impact on operations. “So many aspects of this project have been a huge success. We delivered on time and on budget without any outages for customers or employees.”

The move to the cloud came at a rather fortuitous time. Fejes says: “When you and I met on that stage in 2023, nobody was really talking about AI yet. But now you’re probably finding yourself in a very privileged situation because some of your competitors might still need to work on what I would call the foundational elements of their infrastructure, whereas you’re in a situation where you can take advantage of the capabilities of the cloud.” Says Chave: “The foundation we have now will give us access to some of the best AI technology without having to make huge investments in infrastructure just to deliver something. We can try out new tools and pivot quickly.”

Beyond enabling new and surprising technologies, the move to the cloud also had another major impact on Syz Bank: a reduction in complexity. What was previously 140 applications working together to protect the bank’s data has been reduced to seven on the cloud system. “So many people are underestimating the impact of complexity in terms of environment stability and cost. Program simplification is probably one of the best ways to achieve cost-efficient operations,” says Fejes.

It might seem counterintuitive that such a complex transformation could result in such simplicity, but that’s exactly how this project played out. Now, with the stage set, let’s raise the curtain on this episode.  

Host: Michael Nicholls  
Engineer: Kyp Pilalas 
Producer: Scott MacAllister 
Executive Producer: Ken Gordon</description>

“In French, we say when it’s raining at a wedding…

“In French, we say when it’s raining at a wedding, it will be a beautiful marriage leading to a happy life,” says Syz Bank COO, Boris Chave. Reflecting on an announcement made on stage in 2023 alongside EPAM’s now-CEO Balazs Fejes during an afternoon storm in Geneva, Chave adds: “I think this rainy event was the beginning of a successful project and a happy partnership between Syz and EPAM.”  

Swiss banks have a well-known reputation for being protective of customer data, and Syz Bank is no exception. For years, the bank relied on on-prem servers and top-shelf security solutions to protect its customer data. However, the cost of those solutions was rising sharply, which led Chave to wonder if there existed a better solution. “The challenge with our setup was that even though we had these best-in-breed technology solutions, the ongoing investments we needed to make to protect our data just weren’t sustainable. I had to ask myself, should we continue down this path with its huge impact on P&L? Not to mention I wasn’t comfortable with the complexity of our systems.” 

Fast forward to June of 2025, and EPAM has just finished helping Syz Bank migrate all its IT infrastructure to cloud-based systems, no small feat. As Fejes points out, “You got new notebooks, new applications, you migrated everything to the cloud. You basically built, de facto, a brand-new bank.” As Chave notes, not only did EPAM help Syz Bank navigate the cloud migration, but we did so with minimal impact on operations. “So many aspects of this project have been a huge success. We delivered on time and on budget without any outages for customers or employees.”

The move to the cloud came at a rather fortuitous time. Fejes says: “When you and I met on that stage in 2023, nobody was really talking about AI yet. But now you’re probably finding yourself in a very privileged situation because some of your competitors might still need to work on what I would call the foundational elements of their infrastructure, whereas you’re in a situation where you can take advantage of the capabilities of the cloud.” Says Chave: “The foundation we have now will give us access to some of the best AI technology without having to make huge investments in infrastructure just to deliver something. We can try out new tools and pivot quickly.”

Beyond enabling new and surprising technologies, the move to the cloud also had another major impact on Syz Bank: a reduction in complexity. What was previously 140 applications working together to protect the bank’s data has been reduced to seven on the cloud system. “So many people are underestimating the impact of complexity in terms of environment stability and cost. Program simplification is probably one of the best ways to achieve cost-efficient operations,” says Fejes.

It might seem counterintuitive that such a complex transformation could result in such simplicity, but that’s exactly how this project played out. Now, with the stage set, let’s raise the curtain on this episode.  

Host: Michael Nicholls  
Engineer: Kyp Pilalas 
Producer: Scott MacAllister 
Executive Producer: Ken Gordon

The Resonance Test 99: Balazs Fejes and Boris Chave on Syz Bank's Digital Transformation

<description>AI is not as new as we think, says Gary Rivlin, author of *AI Valley: Microsoft, Google, and the Trillion-Dollar Race to Cash in on Artificial Intelligence.* 

As our non-artificial guest on *The Resonance Test,* Rivlin tells host Barry Briggs that back in the 1950s, it was thought that AI was always right around the corner. There would be a gathering of technologists who said: “Give us 10 years and we'll have this thing largely solved.” Which meant, says Rivlin: “AI was ‘a decade away’ for about 70 years.”

Rivlin notes that recommendation engines and Google Translate have been operating for a while. “Google Translate has been around since 2015. That's AI, but no one really thinks of it as AI.”  However, when ChatGPT strutted onto the scene, it was something else. Rivlin says: “We were talking to it. Suddenly: AI that you could converse with. It's a whole different beast.”
The builders of that beast are his topic in *AI Valley.* 

Rivlin, who was a reporter for *WIRED* in the dot-com days, returns to his old beat to document the onset of the recent, fast-blooming AI spring. He and Briggs, a former CTO at Microsoft IT, bring years of history into the conversation to offer an assessment at this moment of peak AI in Silicon Valley. 

They talk, for instance, of Reid Hoffman. Briggs says, “He’s the exception to the rule of nice guys finish last.” Rivlin zings back, calling Hoffman: “A billionaire you can root for” and adding “this lonely kid who wanted friends created LinkedIn, which connects the world.”

Together they remember the dot-com days of irrational exuberance, getting-rich-by-selling-dog-food-online. “The problem was we tend to overestimate the short-term impact of a technology and underestimate the long term,” says Rivlin, adding we’re seeing a similar sort of thinking with AI today.  

The pair reflect on how people used to joke about autocomplete. “I should have started thinking, ‘this could turn into sentences, this could turn into paragraphs, this could turn into dialogue,’” says Briggs.

Rivlin notes that agents aren’t “trustworthy” yet. He says that if an agent is going to “make material decisions, it really needs to be trustworthy.” In two, five, 10 years from now, “AI agents are going to be central to the work life of many, maybe perhaps most of us.”

We trust that you’ll be informed and entertained by this episode. Click on!

Host: Alison Kotin
Engineer: Kyp Pilalas
Producer: Ken Gordon

</description>

AI is not as new as we think, says Gary Rivlin, a…

AI is not as new as we think, says Gary Rivlin, author of *AI Valley: Microsoft, Google, and the Trillion-Dollar Race to Cash in on Artificial Intelligence.* 

As our non-artificial guest on *The Resonance Test,* Rivlin tells host Barry Briggs that back in the 1950s, it was thought that AI was always right around the corner. There would be a gathering of technologists who said: “Give us 10 years and we'll have this thing largely solved.” Which meant, says Rivlin: “AI was ‘a decade away’ for about 70 years.”

Rivlin notes that recommendation engines and Google Translate have been operating for a while. “Google Translate has been around since 2015. That's AI, but no one really thinks of it as AI.”  However, when ChatGPT strutted onto the scene, it was something else. Rivlin says: “We were talking to it. Suddenly: AI that you could converse with. It's a whole different beast.”
The builders of that beast are his topic in *AI Valley.* 

Rivlin, who was a reporter for *WIRED* in the dot-com days, returns to his old beat to document the onset of the recent, fast-blooming AI spring. He and Briggs, a former CTO at Microsoft IT, bring years of history into the conversation to offer an assessment at this moment of peak AI in Silicon Valley. 

They talk, for instance, of Reid Hoffman. Briggs says, “He’s the exception to the rule of nice guys finish last.” Rivlin zings back, calling Hoffman: “A billionaire you can root for” and adding “this lonely kid who wanted friends created LinkedIn, which connects the world.”

Together they remember the dot-com days of irrational exuberance, getting-rich-by-selling-dog-food-online. “The problem was we tend to overestimate the short-term impact of a technology and underestimate the long term,” says Rivlin, adding we’re seeing a similar sort of thinking with AI today.  

The pair reflect on how people used to joke about autocomplete. “I should have started thinking, ‘this could turn into sentences, this could turn into paragraphs, this could turn into dialogue,’” says Briggs.

Rivlin notes that agents aren’t “trustworthy” yet. He says that if an agent is going to “make material decisions, it really needs to be trustworthy.” In two, five, 10 years from now, “AI agents are going to be central to the work life of many, maybe perhaps most of us.”

We trust that you’ll be informed and entertained by this episode. Click on!

Host: Alison Kotin
Engineer: Kyp Pilalas
Producer: Ken Gordon



The Resonance Test 98: Gary Rivlin, Author of “AI Valley”

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