See show notes for this episode: S 02 | Ep 25 The Double-Edged Sword of AI in Financial Services
Alex: Today's guest is Luke Giancarlo, director of The New York FinTech Innovation Lab, a global incubator helping early growth-stage startups collaborate with major financial institutions. He is also an executive at Accenture, where he is leading Accenture's digital currency treasury offering and co-authoring the Digital Dollar Project.
Luke, welcome to the pod.
Luke Giancarlo: Ah, what's going on? It's good to see you again. You left out in your intro that you are also an alumnus.
Alex: We are very, very proud alumni of Accenture's FinTech Innovation Lab. I think when we got accepted, we were probably not qualified to do it. I don't know how it happened. It was two guys and a dog with an idea. And the lab has been absolutely tremendous at helping us validate our idea with large financial institutions. And Accenture, as you know, has been absolutely tremendous at actually taking some of that idea, because it was able to move way faster than some of those large financial institutions, helping us shape it. It was effectively one of our first customers, where we built a tech-enabled offering supporting Accenture and the teams. And it absolutely, positively could not have happened if it wasn't for the lab.
When I look back, I think we got the genesis of our idea of what is now related to AI. Slightly different focus and organization, but all the learnings came from the lab. So I'm a huge fan. That's one of the reasons why I wanted to invite you. It's a well-known program in certain circles, as well as large institutions, but I think a lot more startups and scale-ups should learn about it. Tell us more—what's your take on the program and the role it fits into the ecosystem?
Luke Giancarlo: Yeah, thanks. And honestly, that was an awesome intro for the program. I feel like you could do it for me.
Alex: But the smallest company working with one of the largest institutions in the world—where would that happen? Only at the lab, right?
Luke Giancarlo: Oh my gosh, the salesman in you—I see it. Great marketing mind. But yeah, thank you. So the FinTech Lab—I'll give the history of it—it's been around for 15 years. We, as Accenture, co-founded it with an organization called the Partnership Fund for New York City, and we founded it really after the financial crisis in 2009 as a way to compete with the West Coast and bring some of that fintech innovation back to New York City—to really be at the center and the hub for finance, right? With the Wall Street banks and the financial institutions that are based here in New York.
So 15 years later, we're really going strong. It's been an amazing program. For your viewers, the way it works is every year we sit down with executives from these financial institutions across payments, banking, capital markets, and insurance. And I know you don't want to single out some of these institutions—
Alex: Stand out some of these institutions, but maybe it will just help bring to life the Goldmans and the Morgans and whoever else you're working with. Not to treat anybody in a special way, but just give us some names of the institutions that you work with.
Luke Giancarlo: I mean, no—you named them. They're all tier-one organizations, right? The BlackRocks, the Goldmans, the JP Morgans, Bank of America. On the insurance side—New York Life, Travelers, TIAA. So really phenomenal organizations that we represent and help find startup companies.
And so, to your point, you get a really diverse spectrum of these financial institutions that are legacy organizations with a lot of red tape, but are really the big players in the room. And every year we sit down to understand what their innovation priorities are across the different parts of their business, the different technologies that they're really interested in. So we've gone through all the waves, right? We've gone through cloud, metaverse, sustainability, blockchain—now it's all AI, of course.
But every year we take that feedback, we go find startup companies that are solving those problems, and we bring them into the shark tank. It's a competitive program until we eventually have the top 10 companies. And what's unique about the lab is those top 10 companies then get paired up with those financial institutions. Over the course of three months, you get kind of three to seven dedicated financial institutions to really mentor you, help you refine that product-market fit, and really understand what is the sweet spot for you and your business.
And it works, right? I think you're even a testament to that—of being in the room, working with those financial institutions. You really get that experience to help refine your product. And I think you even mentioned that after the program, you were able to tweak or fine-tune the offering that you had.
Alex: Yeah, absolutely. And I think now we almost—
And you know, the startup journey goes in mysterious ways, obviously. So I think the challenge with supporting large financial institutions, or any very large and regulated enterprise, is obviously the velocity with which they can adopt new technology. So Accenture became a relatively more agile adopter and then helped us get feedback and get the technology working.
And then, for example, now when we are building the world's first regulated content platform, guess what—we want to come back to the people we've met in the lab because we now actually have something that's working. And we don't need to wait for instant feedback that you could get maybe quicker in other ways. What we need is: how do we deploy this strategically inside your institution so this becomes a real game changer for you?
So there's this tension, I would say. And I'm curious about your take on this and how you help companies deal with it. If you're building a relatively horizontal solution, how do you get feedback quickly—as a startup, that's really critical—versus spending all your cycles in enterprise sales cycles? But then, if you don't have that option, and you're building something that is very much enterprise-only, how do you find the right partners to pilot your technology with so they can give you that feedback?
Those are some of the tensions that many startups underestimate. Maybe you could comment on that a little bit—on how you help them pick and choose which partners to work with, for example, and what areas to focus on.
Luke Giancarlo: Yeah, and it's funny, right? I'm sure your viewers are like, wait a second—RELAYTO is not a fintech. But our audience is really pure fintechs, pure insurtechs, but also horizontal plays, right? Data management, security platforms, marketing platforms, HR tools. But it's about how you help enable financial institutions as they go to market to be more effective and efficient. So the lab really has that flavor to it.
But to answer your question, a lot of it is the things you mentioned, right? It's not just having great technology, but really being able to solve a problem in the market and spending time with these financial institutions to understand what their pain points are, what they are struggling with. And not just saying, “Hey, look how cool my technology is,” but really asking, “How can it solve for you?” How can it be an enabler and help you be more effective in what you're doing?
And so that's been a big focus for us. The lab gives you time to really spend with their procurement teams to understand their DevSecOps requirements, their legal requirements, how they think about contracting—and to ask those questions openly and honestly to understand what it will take to get through those hurdles.
Then you spend time with their strategy teams and technology teams, asking: where does this fit on your roadmap? What are your priorities? How can this complement those? On the tech side—what is your current tech stack? What type of integrations do you need? What are you comfortable with? What type of data sharing are you okay with?
All of those questions really help startup companies refine their product and take a great idea and make it even better—so it is purpose-suited for financial institutions or large enterprises.
Accenture has been investing in startups for 15 years now.
Alex: And what—what's in it for Accenture in this journey? Right? We obviously know that Accenture is not going to make money servicing startups as customers. Their work is with the largest institutions. How does this work, and why are you investing?
By the way, for those of you who are startups—sometimes you have to pay equity and fees to participate in programs. This program is very generous in the way it sets up practical conversations and engagement. So how and why do you decide to sponsor and invest in this? Now, how many years has it been? This is 15? Yeah, 15 years, right?
Luke Giancarlo: Yeah, it's pretty amazing. And I laugh—I almost call the lab the best-kept secret, or the best word-of-mouth program out there. Because, you know, Techstars and Y Combinator—they're great. But what we really solve for is helping you get exposure to financial institutions.
But to answer your question—what's in it for Accenture? Truly, and this is rare, we founded it as a civic program with the New York City Partnership Fund, and we try to keep it that way. Everybody that's involved—it's pro bono. The financial institutions come to the table—they're not paying anything except their time commitment, which nowadays feels more valuable than cutting a check.
And for the startup companies, to your point—we're non-dilutive. You don't pay anything, we don't take any equity. We just really want you to get that exposure.
Luke Giancarlo: And so what we get out of it is, one, helping to keep New York a center for fintech and innovation and advancing the New York community.
Alex: And I think you've done a great job on that. It's definitely booming in that sense.
Luke Giancarlo: Yeah. And the other thing for us is—it’s a great way for us to understand what financial institutions are struggling with. What are their problems? What are the pain points? Especially as they think about how to adopt innovation or reinvent their processes—what are those challenges?
We get to be in the room alongside them as they think through those things. And then also—for the startups—there are a lot of great companies out there, and we can spend time with you to understand how you're solving for financial institutions, many of which are our clients.
And you've been a great success story—you come out of the program, and we can actually partner with you and bring you to our clients and say, “Hey, look, we know this company works because we've seen it with 40 other financial institutions. We think they'd be great for you and this specific project.”
Accenture is working with some of the largest financial institutions on AI initiatives.
So actually, Alex—maybe from me as well—let me talk about some of those projects you've done with Accenture, as much as you can, in terms of how you’ve collaborated and used your platform for some of our large financial institutions.
Alex: Well, look, Giancarlo—as you know—Mr. Luke—the first rule about Accenture is you don’t talk about Accenture.
One of the things I can talk about, though, is what we've done with the lab. And I think that's one of the things you could comment on as well. One of the things we loved from the very early days in the lab is that some people talk about innovation and invest in innovation, but don’t actually do it in particularly innovative ways.
The lab was very open to trying RELAYTO itself. And so we could show some of the results of that.
Luke Giancarlo: Yeah, you’ve got to eat your own dog food, right?
Alex: Well, we think of it as champagne.
Luke Giancarlo: Eat our own caviar, I should say.
Alex: Yeah, this is New York.
So here’s an example—a public version of a hub, which contains what we call a portal. This portal can contain videos—you can see a video, a scrollable site, and a bunch of presentations from the startups that participated. Then you have the videos of all these startups—all in one place.
You can ask it questions with AI chat—which is actually new. At the time it was launched, it wasn’t available yet. So now you can find the needle in the haystack.
Then there’s a landing page, which is what gets shared in press releases and announcements that you’ve done introducing the companies. For every company, there’s a video that plays immersively, and a deck that you can walk through. You can still download them, play them full screen, or go through them however you want.
That’s the simple idea. And the beauty of this is that you can do it in seconds with AI. But it’s an iterative process—because before you put AI into everything, you need to make sure the experience actually engages and works.
This is something we experimented with in the lab. It’s a very practical way to get the message out. And if you think about your corporate sponsors—they meet all these startups, and the people initially supporting them are often not the same people who will work with them during deployment. So they need to explain things clearly.
Here’s the startup, here’s what they do, here’s a quick introduction. You’re enabling your champions inside these corporates to be more successful. And that’s aligned with your mission—to bring practical innovation into reality, not just keep it as a project hypothesis.
Luke Giancarlo: Yeah, absolutely. It’s less innovation theater and more putting you in the room—in the shark tank—with some of the biggest financial institutions in the world.
They’re not going to take fluff. They will really challenge you and make sure it works. That’s the focus of the lab.
Alex: And on that note—one of the things, for example—we focus on content, and all of this is approved, right? The startups give you their formal decks, the videos are approved—you don’t want anything modified or lost.
One of the things you can see is engagement. You can see—this idea is getting traction, or everyone is booking meetings here. That’s an interesting indicator of what’s working and what’s not.
Even the format—the layout—matters. It sounds simple, but even in 2024–2025, people are still packaging PDFs in a very paper-first format and sending them out, hoping for results.
This is a simple opportunity to fix—but you need the mindset of someone who cares about impact and compliance. For example, this had to go through Accenture compliance—cookie settings, everything. It’s not as simple as signing up for a consumer tool and building something on your own.
Luke Giancarlo: Yeah, it’s funny. One of my first real roles was as a marketing director for a nursing home my family ran growing up. This was over a decade ago, when the big trends were SEO and geo-targeted advertising. We were trying to optimize our web presence across different channels.
It’s amazing how much marketing and technology have evolved over the past decade. And you’ve had an interesting journey as well—when you started in the lab, it was a very specific use case. Now you’ve incorporated AI.
To take a step back—every year we talk to financial institutions to understand their innovation priorities. For the past two years, no surprise, it’s been very AI-focused. But mostly for back-office use cases—how to make teams more effective, embed copilots, and improve efficiency.
Now we’re starting to see more attention on front-office AI applications. How do you create hyper-personalized experiences? How do you better manage customer data—both generating it and collecting and synthesizing it?
And I think you’ve had an amazing journey—from starting with a specific use case in the lab to scaling it and accelerating it with AI. It’s been interesting to see how marketing, and your platform, have evolved to be more purpose-built as well.
Alex: Yeah, very interesting. We even call what we're building “regenerative AI.” The idea is that, in regulated industries, part of it is about compliance, but part of it is that we are regenerating approved content.
And I think you used the phrase “hyper-personalized.” The world we live in with probabilistic models is very risky for regulated industries. That’s one of the reasons why adoption has historically been internal—because the risk is a bit lower for internal applications, outside of maybe accounting.
But when it comes to customer-facing communications—where you could misrepresent things or hallucinate in any way—the risk is much higher. The reputational risk is often not worth the effort to improve the experience.
So what ends up happening is actually something quite bad for customers in financial services, because they are bombarded with a lot of dense information. Everywhere else, they have short-form content—TikToks, sound bites—but when it comes to really important, strategic decisions like personal investments or insurance, it’s the opposite.
So we found applications in helping employees make benefits decisions. In the US, about half of families worry about going bankrupt due to a healthcare emergency. And ironically, all that information comes from insurance carriers and ends up as a mess of downloadable documents that are barely readable.
So people just default, and they resent it—because about 25% of employee costs go toward benefits in the US market, and nobody really understands them. Sometimes even the brokers who sell these products struggle to understand them. They have call centers of people trying to answer questions. Employees certainly don’t understand it.
And HR is overwhelmed with answering the same questions, while also being at risk—because the CEO also enrolls in benefits, and if that experience is poor, it reflects badly.
So we see this situation where something very important—healthcare costs, which are rising—is held back by the fact that the way it’s explained hasn’t changed, while complexity and regulation have increased.
It started with health insurance, but it extends to 401(k) retirement plans and beyond. So we see a huge need for innovation. But even with us being very careful—regulated-first, taking minimal risk in how content is segmented and using AI for that—the moment you mention AI, people can become concerned because of the regulatory context.
So this is a disconnect we see in the ecosystem. I’m curious—is that aligned with what you’re seeing as well, especially with startups working on B2C applications?
Luke Giancarlo: Yeah, I mean B2C and internal use cases as well—it’s pervasive. And I think part of the double-edged sword of AI is hallucinations.
We’re seeing a lot of success with companies focused on guardrails—how do you ensure compliance? Last year, we had a company called Palki, and their platform, Palki Prisma, is focused on sitting alongside large language models to ensure compliance. It looks at global regulations to make sure those systems don’t hallucinate and stay on task within established frameworks for financial institutions.
So that’s one example of how companies are solving these challenges. But you’re right—it’s not just about customer engagement and making sure communications are accurate and on-brand. It’s also about enabling employees.
How do they become more effective, more informed, and more secure in their roles—especially as we go through a major shift in HR and the future of work with AI?
If you think about it, after the pandemic, we saw a wave of tools for remote work and collaboration—ways to bring people together digitally. Now AI is reshaping that again. And there’s another shift coming in talent management.
What does work look like when much of it can be automated? How do people fit in? These are real challenges we’re trying to address.
And I think the way you’re approaching it—using AI to inform and educate people on complex topics like financial decisions, healthcare, and insurance—is a great application of the technology.
Alex: Yeah, it’s interesting. Historically, HR has been seen as a compliance function. But people don’t go into HR just for compliance—they want to connect and help people.
I was early at a company called SuccessFactors, which Accenture implements and which was acquired by SAP. And we saw that the people drawn to HR want to support others.
But to your point, the workflows and processes required for compliance meant that compliance had to come first—nobody wants to go to prison—so connection became secondary. And I think we got too comfortable with that mindset.
In some ways, AI can make this worse. When people are overloaded with information and stop reading, you lose context and trust.
So combining context, trust, and connection—while staying compliant—is a very difficult problem.
Accenture, in particular, has done a strong job here. They’ve used RELAYTO internally—for HR training and executive communications—and won awards for it. They’ve been willing to try new approaches in a large, global organization.
Luke, what’s the latest number of employees at Accenture?
Luke Giancarlo: It’s close to 800,000.
Alex: 800,000—so still growing. And even at that scale, it’s relatively centralized in terms of playbooks across regions. It’s been interesting to see that appetite for innovation.
But I don’t think many organizations have done this historically. HR has a lot of catching up to do. Even with platforms like SuccessFactors—some parts are modern, but a lot of it is still quite traditional. You log into an intranet, download PDFs, and don’t get a differentiated experience.
We believe employees need better support in the age of AI.
And the insurance example I mentioned—it’s both employee communication and B2B2C. Insurance carriers can’t sell products if people don’t understand them or don’t see the value. Brokers struggle with that too.
So there are interesting entry points—benefits can lead into healthcare, insurance, retirement products. And these are bought by both HR and finance teams.
So I’m curious—how do you see patterns of where innovation is happening? Beyond front office and back office, are certain sectors further along than others across your portfolio? Or are some still lagging?
Luke Giancarlo: Yeah, I mean, I’ll start with maybe some of the technologies that we think are hot. I can also talk about more industry-specific areas, but for technologies, I mean, again, AI is just sucking the air out of the room. But I think it is shifting a little bit, right? In the past two years, it was very much, “Okay, I want to find a use case and I want to start solving it with AI.”
And I think now companies have gone through and actually implemented real AI applications, and they’re now thinking about, “Okay, one, how do I now empower those agents to be more agentic, to actually give them authority to make decisions within a business, and not need as much of a human in the loop in order to execute some of those activities?”
And so I think agentic AI is really going to be the next wave that we’re going to see around AI in real applications, right? Not just deploying agents, but really stringing them together and having more of an agentic infrastructure.
And I think the drive for that is also going to have a lot of ripple effects for other innovative areas, like what I’m calling AI ops. So in the same trajectory that cloud went through—where everybody migrated to the cloud for data storage and data processing—and then all of a sudden they said, “Okay, now I can figure out what the use cases are in the cloud, how do I manage the cost in the cloud, how do I manage who’s got access to these different systems?”—you actually went through this compression around cost and operations for cloud.
I think you’re going to see that for AI as well. Now that all these agents have been deployed, you’re going to have a bit of a reaction around your AI estate management. How are you managing the governance around all these tools, the access controls, and the costs associated with the processing and compute power of these AI agents?
And so I think all those wrapper elements are going to be really innovative territories for how a startup can help financial institutions manage their portfolio of AI tools, very similar to what cloud went through.
Another interesting area that I think is also agent-to-agent is payments. So, similar to agentic AI, but think about it specifically in payments. We think about agentic commerce—how are your agents making payments on your behalf or paying other agents?
I spent a lot of time in the digital currency and digital asset space before running a lab. I actually founded an organization called the Digital Dollar Project that advocates and explores tokenized versions of the dollar. And I think that’s a really interesting space for AI—how stablecoins can be the instrument for agents and how they make payments.
I was at a Stripe conference last week for the New York tour, and they were talking a lot about how they’re deploying stablecoin solutions focused on commerce for agent-to-agent commerce. So I think that’s another interesting area.
Companies need to be more present with AI to help customers make insurance decisions.
And the last one that I’ll touch on is actually insurance. So people are actually going to ChatGPT to say, “Hey, what are my best insurance policies?” And ChatGPT will give them better insights in terms of, “Okay, this is your best option cost-wise for auto, home, life, or health.”
And I think customers are using these generative AI tools to make decisions on their insurance portfolio. So insurers need to figure out how to address this and how they can be more present so that their products can be embedded or informed by these AI agents that are being used publicly.
So I think being present and helping to get your products and services in front of people who are using AI is going to be another interesting frontier, especially for marketers as they think about how to tap into these tools and how to meet customers where they are, where they’re looking for services.
Alex: Yeah, it almost feels like if you’re too slow to adapt, then customers will go find other ways to answer their questions, right? And if you’re running old-school ways of doing things, you’ll miss the opportunity.
It feels like there are two issues. One is discovering customers, right? And I think that’s more relevant in B2C businesses. In B2B, you may already know who your customers are, but then it’s the question of engaging and retaining them and having them continue to think of you as a trusted advisor.
And it feels like a slow pace of innovation is risky if you’re waiting too long to figure this out. Someone is likely to disrupt you. Is that what you’re seeing?
Luke Giancarlo: I think the pace of innovation is happening faster than ever right now.
Alex: So actually, is it the pace of innovation or the pace of real adoption?
Luke Giancarlo: I think it’s the pace of innovation. You’re seeing that it’s way easier nowadays to create a company. It’s way easier now to create a product. With vibe coding and all the tools out there, you can stand up a product or an MVP in a matter of weeks or even days.
And so I think you’re seeing even more companies flooding the market trying to solve problems. I also think we’re in a regulatory environment right now that’s really embracing or trying to spur innovation across AI, digital currency, and digital assets.
So there are so many companies coming out, and so many innovative topics that are being driven forward.
Luke Legos: I like the distinction between innovation and adoption.
I think financial institutions and a lot of large enterprises need to figure out how they can be more agile and actually explore and make decisions on innovative tech more quickly.
A lot of the work that I do at Accenture is helping financial institutions think through how to adopt, where to adopt, what the impacts of innovation are, and being a partner with them as they speed up their decision-making while evaluating all the solutions coming out.
Alex: So when you look at companies and startups that break through the noise—the ones you’re selecting in the lab and seeing succeed, not just showing up with another “agent, agentic, whatever is the flavor of the month”—but actually getting mindshare, real deployment, and moving beyond pilots (besides RELAYTO, of course), what patterns are you seeing?
What do successful companies do to deploy for real, build longevity, and continue introducing new innovations after initial adoption?
Luke Giancarlo: Yeah, and if you’re listening to this podcast, you’re going to get Luke’s tips and tricks for applying to the program—so consider this the inside scoop.
But I think a couple of things. One, there’s a lot of great technology out there, but you really need to clearly communicate what problem you’re solving. People buy solutions; they don’t buy technology.
So being able to clearly explain what your solution is and why you’re differentiated matters more than just having creative or advanced tech.
Actually, one of the financial institution partners in the program last year said, “I’m looking for solutions that solve one thing perfectly, as opposed to trying to do a lot of things.”
Luke Giancarlo: …of things, potentially. And I really like that mindset—really choosing a problem, nailing it, and showing how you can solve that problem perfectly. Then you can scale from there, as opposed to saying, “Hey, my platform can do it all—you tell me what you want to do.”
I think being really clear in communicating that problem statement is how you differentiate.
Alex: I would agree with that. In retrospect, if I had to rethink how I would go about building RELAYTO, we definitely started out with a very strong point of view: the most important information is locked in formats nobody wants to consume.
But we didn’t have as strong of a hypothesis about which particular application we wanted to focus on at first. So we were in an exploratory mode. And that exploratory mode led to a lot of people being interested in this.
I think the real traction came once we said, “Okay, we have this narrow application in financial services—let’s focus on this benefits example,” where everybody spends a lot of money and nobody gets value out of it. There’s personal tragedy, companies wasting money, insurers not growing.
Once we figured that out and had a consistent set of deployments, life became much easier to replicate and scale.
I feel like, as a second-time founder, I was probably being greedy—wanting to build a decacorn right away, going for a broad set of applications, saying we could conquer everything. And I think we will eventually. But we had to consolidate, prove the thesis in a specific area, do it really well, and know what we’re doing—get enough at-bats—rather than saying, “We’ll mold our way.”
Otherwise, you end up being the startup that pretends to be Accenture. And even Accenture doesn’t do everything—it has its own playbooks. But a lot of tech people think their product is like a bunch of Legos. And I think you don’t get as much value from Legos as from more tailored solutions.
Am I thinking about this correctly?
Luke Giancarlo: Yeah, definitely. I think the Legos are important, but what really matters is figuring out how they solve a problem and being very clear about that. So yes, I fully agree with you.
Alex: So all you startups—learn from Chevalo mistakes. I think you look back and reflect, but there’s always this question: are you picking the right problem?
Maybe the lab is a place where people should come in with one or two hypotheses and then test them out. What’s your advice on that?
Luke Giancarlo: Yeah, I mean, there’s so much information out there. Applications are open—you can look at the application details. We actually announce what the top 10 themes are across industries.
From all of our conversations, we identify the key pain points—what’s topical in terms of technologies and priority areas. We ask about hundreds of topics, but we try to distill them down to the top 10.
So as you’re looking to apply, you can review those themes year to year and understand what problem statements organizations are wrestling with. Then go deep. Really try to understand how you can be helpful in that area and work with financial institutions to solve a real problem.
Alex: Got it.
What about horsepower in terms of execution and follow-up in enterprise sales?
Getting back to the broader tips—narrow down and solve one problem really well. But what about execution and follow-up? Selling to large institutions isn’t easy. What’s your perspective?
Luke Giancarlo: I’m amazed by some of these founders. They respond at two in the morning, all weekend long—any time of day. Being “on” like that is almost required to be an entrepreneur today.
But I think AI tools are helping. You have better CRM tools, note-taking tools, and follow-up tools. Being scrappy and savvy with these tools helps you be more effective.
But you’re right—even in the lab, we bring in startup teams that are two people and a dog, and we pair them with five or six large financial enterprises, each with their own demands. It’s a very tailored experience, and it’s sink or swim.
You have to figure out how to keep up with the volume of questions, follow-ups, and expectations, and how to properly serve those companies. So there is a certain level of horsepower, as you put it, that you need to work with tier-one financial institutions and meet their level of sophistication.
That said, there are many great tools that can help you be more nimble and effective. You’re a great example of that. We’re a small incubator, and we use tools like RELAYTO to improve customer engagement.
So tools like that can help startups scale, break into the market, and deliver a more differentiated experience for their clients.
Alex: Got it.
You’ve been in Accenture’s incubator program for three years now.
What are some things you wish you knew earlier—before Accenture, when you were in a more entrepreneurial environment—now that you’ve seen patterns across a couple of years in the program? What advice would you give to help people get ahead?
Luke Giancarlo: Great question. In a previous role, I worked for a startup in an incubator, so I’ve seen both sides—being in a startup and evaluating incubators. It’s interesting to now be on the other side of the table.
What would I have done differently? Probably leaning more into the network. There are so many great people out there who genuinely want to help entrepreneurs and founders—and who want to support strong ideas and technologies.
Building relationships is key. Alex, you and I have known each other for over a year now, and that kind of connection matters. Leaning on your network and building a community around you helps you be more effective.
It helps you find problems, work through solutions together, and share learnings. It also helps you move forward—people pulling each other up.
That’s one of the things that makes the lab unique. It has a civic-minded nature. Everyone comes together to help startups and drive real innovation. It’s not just for show—it’s about solving real problems and creating meaningful solutions.
So finding those people, leaning into them, and building your cohort—your “army”—is something I wish I had done earlier in my career.
Alex: I would strongly echo that. There’s a tendency to assume everyone is the same—but they’re not. There are people who are high-energy creators, people who support others, like yourself and the program. They’re also just more enjoyable to be around.
Energy matters, and people underestimate how important positive energy is—not blind optimism, but a “can-do” mindset directed toward real outcomes.
In enterprise environments, there are a lot of rejections. Things don’t always work out. There are ups and downs all the time. So having people around you who understand that process and still push forward is crucial.
Not everyone—even in so-called innovative companies like Google or AWS—is actually driving innovation. That’s true everywhere.
And from a go-to-market perspective, AI is also creating challenges. It’s removing nuance. We’re seeing automated outreach, mass messaging, constant noise on LinkedIn.
If I’m getting flooded with that as a CEO of a relatively small company, I can only imagine what others are dealing with.
So finding ways to build real connections, using your network, and keeping interactions human and authentic really matters.
And I’m grateful you joined—so people can get a sense of the program and experience it firsthand.
Alex: You know, Accenture has these amazing, talented leaders like yourself who are promoting innovation—really leading it and making concrete progress. It’s a lot more fun to have co-conspirators on the journey.
Luke Giancarlo: Yeah, and it should be fun, right? Innovation should be fun. For some financial institutions, this is the best part of their week. They get to spend time with young, creative founders and talk about AI, quantum, blockchain, and crypto—it’s a fun space. So lean in.
Alex: All right, so we’re basically on vacation.
Luke Giancarlo: Yeah, yeah. I feel like I’m on vacation right now.
Alex: Yeah.
Luke Giancarlo: We’ll do this over drinks next time.
Alex: Yeah, over drinks.
So, what are the themes that we’ve talked about? We’ve covered some of the innovation themes you’re focusing on this year. But let’s look five years into the future.
In the areas where you’re a pioneer—especially around digital currencies—what are you envisioning? What are some things you’re seeing from both startups and larger institutions that may still be unclear today but, in your view, will become inevitable trends we should be paying attention to?
Luke Giancarlo: Yeah, we touched on a couple of them. Agentic commerce is one I find fascinating, but honestly, I think it’s still years away from being fully realized in the market. It will take smart innovators, strong security, and probably thoughtful regulation to make it work.
But I think we’re moving toward a future where it’s agent-to-agent—payments, shopping, even choosing insurance policies or helping personalize what makes the most sense for you.
Hopefully, that future creates more time for humans to connect in real life—to focus on what we do best: creativity, relationships, and engagement—while agents handle bureaucracy and operational tasks.
There are already interesting startups working on agentic shopping, embedding products and payments directly into AI experiences. We’ll see more of that. But I think it’s about five years away from real market adoption at scale, with fully developed agentic commerce.
Another interesting area, a bit further out, is quantum computing—or more broadly, accelerated data processing. Quantum may still be quite far away, but there are interim solutions we may see sooner.
Some companies I talk to are worried about what they call the “ChatGPT moment” for quantum.
Alex: When something suddenly comes out and everyone says, “We have to catch up”?
Luke Giancarlo: Exactly. After what happened over the past two years, there’s a sense of urgency. If someone achieves a breakthrough in quantum, companies don’t want to be caught off guard and have to rush into the space.
So there’s growing interest in staying closer to innovation—understanding what’s coming and identifying promising companies early.
Alex: Nobody wants to be caught off guard, so to speak.
Luke Giancarlo: Exactly.
Alex: To use Warren Buffett’s analogy—you don’t want to be caught unprepared when the tide goes out. You want to be ready for disruption.
And speaking of megatrends—on the topic of digital currency, the current administration is pushing innovation. David Sacks is coming from the venture community and driving things forward quickly.
Based on your experience, having been in this space for years and leading initiatives at Accenture, where do you see digital currency going?
Luke Giancarlo: It’s probably my favorite topic—it’s near and dear to my heart. I’ve been in the space for a while, and I’m still very curious to see where it goes.
Even within the lab, we’ve had success with early companies in this space—digital assets, distributed ledger platforms, and others.
If you look at the trajectory of digital currencies, you had the first generation—exchanges, foundational layers, and private networks. Then the next generation included stablecoins, NFTs, and tokenization—more like tokenized money market funds and assets.
I’m curious about what the next generation will look like. I think it will be a blend of technologies—especially AI working alongside digital currencies.
Blockchain and AI are a natural fit. One of the challenges with AI is data management and provenance, and blockchain is a strong tool for that. At the same time, blockchain relies on smart contracts, which need logic—and AI is very good at handling and generating logic.
So I think these technologies will increasingly work together, and that combination will define the next frontier in the Web3 space.
One area I find particularly interesting is automated treasury—using agents to search for yield. For example, moving between stablecoins, tokenized deposits, and yield-bearing assets like tokenized funds or crypto exposure.
Agents could manage that process—optimizing for returns across different instruments. There’s still a lot to be built, especially around connectivity between these systems, but that’s where I see the market heading.
Alex: Great. Let’s wrap up with a broader introduction to the Partnership for New York City and how people can apply to the lab.
It’s a unique structure—a partnership model—so it would be helpful for people to understand how it works.
Luke Giancarlo: The Partnership for New York City is phenomenal. It’s a civic organization that represents the 300 largest employers in New York City. It helps mobilize time, attention, and capital to support the city and state communities.
The lab is one of its initiatives, but they also run programs in areas like public works and transportation. It’s an extremely well-connected and respected organization that brings strong partners to the table.
They work alongside Accenture, which acts as the operational and technology partner, while the Partnership brings its civic network and connections within New York.
Together, they run the lab.
Applications are open right now. We’re looking for great startup companies. If you’re an early- to growth-stage founder looking for exposure to large financial institutions in New York, there’s really no better program than the FinTech Innovation Lab for that level of access and connectivity.
Alex: Luke Giancarlo from the FinTech Innovation Lab—where can people find you personally?
Luke Giancarlo: LinkedIn is the best place. I try to stay off Twitter—I tend to scroll too much there. LinkedIn is my main platform right now.
Alex: Luke, amazing. I’m really excited to have you as a leader of the lab in New York and to see you building the future of fintech.
Thank you for supporting RELAYTO’s journey—we started before AI and evolved into RELAYTO AI in collaboration with the lab. Your organization has been an important part of that journey.
I highly recommend the program to any startup that wants to work with enterprises and build real innovation.
Luke Giancarlo: Alex, thank you so much. It was great chatting with you, and thanks for all the work you’re doing as well.