Learning in the flow of work, talent redeployment, and ethical AI

In this episode of The Intuition Finance Digest, we speak with Peter Gargone, CEO of n-Tier, about learning in the flow of work, redeploying talent in real time, and building confidence around AI in modern financial environments.

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Introduction and early career influences

Ruairi: Peter, thanks very much for joining us on the Intuition Finance Digest today. I am going to jump straight into it with our first question. Looking back at your career, from Goldman Sachs to founding n-Tier, what were the key moments of growth that shaped how you lead today?

Peter: I do not know how much you know about Goldman, but I was there in 1990 when it was still a private firm. It was very hands-on. Managers were not abstract in how they managed people. What I took from that, and applied when I started n-Tier, is a very hands-on management style. We do not hire managers who cannot do the jobs their people do. It creates a lead-by-example culture. Across industries people shifted to more abstract management, but things are swinging back to smaller teams and leaders who can do the work. That has carried through to today and it has served us well.

Continuous learning and learning in the flow of work

Ruairi: How has continuous learning influenced your own career development?

Peter: Continuous learning is tough. When we hire people, and for myself, we do not expect people to know everything in advance. You do not know where you will be or what you will work on. When I started n-Tier and in roles at Goldman and DLJ, I had to learn on the fly. It is less “I need these ten skills” and more “learn how to become an expert quickly,” figure things out while doing them, and still meet a high standard. The idea of picking a fixed skill list and devoting yourself to it feels obsolete today.

Ruairi: That is something we talk about at Intuition as well. Learning in the flow of work means learning is part of the job. Roles and work are intertwined.

Peter: Yes. It has evolved. Roles are not as well defined now. We expect people to do a lot of different things, which means learning on the fly. And role definitions are changing slower than the work itself, so work changes faster than roles can keep up.

Building and developing teams

Ruairi: As a CEO, what is your approach to ensuring your team keeps developing professionally?

Peter: We create an environment where people are challenged but not tortured. We expect hard work and learning as you go. People are given things a bit beyond what they know, but we surround them with deep support from people with strong knowledge in our areas. It is a solid support system and an open environment where they can ask and get help, coupled with a challenging environment. It drives the team to deliver more. People move into different roles over time.

Internal talent mobility and redeployment

Ruairi: If you have a skill need or a gap, are you more likely to reskill someone in-house or look externally?

Peter: We tend to be internal and have repurposed people. The tools available today put expertise at your fingertips in a way you never had before. It becomes more about qualitative judgment and attention to detail than underlying years of experience. We will hire experts on a consulting basis and train our internal people if it is an equal choice. We are busy, so we do a bit of both.

Ruairi: What business benefit do you see from that approach?

Peter: It is hard to find someone who is both an expert and a good fit for us. We value qualitative traits a lot. If someone works well, is hardworking and smart, we value that more than whether they know a specific Linux or AWS detail. The qualitative side is the main part of hiring. The other stuff can be learned. It keeps people engaged, offers career growth, and allows movement without a rigid structure.

The data challenge in finance

Ruairi: What is the data challenge in finance? Why is it critical, and what skills do professionals need?

Peter: Data and data accuracy underpin almost everything in a financial company, and in other industries like medical and insurance. It was long neglected. People used to rely on QA to test only what changed. It is a technology and data fabric issue across the organization. When I started n-Tier in 2000, no one was talking about data. Today almost every finance and regulatory conference talks about data. Our technology stack was built to solve that problem.

AI adoption and responsible use

Ruairi: Changing topic a bit. AI is a major challenge in the industry right now. What are your thoughts, what are you working on, and how are you integrating it?

Peter: I look at AI as raw compute power. At a fundamental level it is massive compute most people have never seen. From our side it gives us the ability to process data exponentially more times for clients and reduce the work they have to do. Our analytics layer, using AI-like processes, helps them figure out where data is broken and why, instead of paying people to find it. On the employee side there is hype and fear. Some clients say 90 percent of their AI projects failed. AI becomes a vague concept, and it is hard to know what people mean. People worry it will take their jobs, but it is like moving from the abacus to the computer. You still need to figure out where it fits. People should embrace it and figure out how it helps them be better.

Ruairi: We launched a poll on LinkedIn asking if people are not going to be replaced by AI, but by people who use AI. Most agreed.

Peter: I think that is right. We do not hire people who use abacuses anymore. If you cannot use a computer, it is hard to get a job. The hard part with AI is you need a rationale for what is right and wrong. If you do not have any basis for understanding results, you put yourself at risk. We are opening it up in some regards, but we need employees to disclose what they pulled from AI versus what they did, so we can police it. Otherwise you might not review enough and end up with wrong results because you think it is thinking for you when it is not.

Ruairi: There is an ethical implication too. Clients want to develop ethical knowledge around AI and how to use it.

Peter: A big part is disclosure. It is easy to pass AI work off as your own, which is risky in a technology company. You see news stories calling out large firms for using AI in the wrong way. It is an ongoing problem.

Integrity, trust, and leadership values

Ruairi: You have built and grown n-Tier from scratch. What lessons about leadership and development have you learned?

Peter: We have been in business for over 25 years and continue to grow. The qualitative side is misunderstood and undervalued. We are adamant about honesty, integrity, and hard work. If we have a problem with a client, we tell them. We expect honesty and integrity from our people. Over years that pays off. It gets you respect from clients and your team. We do not ask people to lie. That builds a culture and a reputation where clients know they can trust you. It adds value and makes relationships sticky, not short term. From a career perspective, people need to understand that. It starts at the first interaction. If a candidate is not honest, it does not matter how smart they are. We will not hire them.

Ruairi: Day to day, how do you ensure that honesty is present? Any practices you use to grow that approach in the company?

Peter: Lead by example. Any major questions come to my desk. If there is a question about disclosure, my default is to be honest. People know we will not ask them to lie. We may collectively manage the communication, but we set the example from the top. I am not involved in everything, but we expect that standard within the team. If we find people not being fully honest or transparent even within the team, we shut that down quickly. Honesty can be hard, but making tough calls builds trust. We have clients who have been with us for 15 to 17 years who know that if something is not right, we will tell them. That links to communication skills and empathy.

Advice for future finance professionals

Ruairi: Last question. If you were advising a finance professional today, what is the most important thing to focus on to future-proof a career?

Peter: You cannot learn everything, but you need to embrace the toolkits available, including AI, and know how to use them effectively. People who do not will be at a disadvantage. Use tools in a controlled way, understand weaknesses, and you position yourself well. Stay positive. The news is negative by design, but leaders need to focus on opportunity. Fear of being replaced by technology is misplaced. Embrace it.

Ruairi: Our last guest, Melissa Watras, had a similar answer. She talked about curiosity. What you are describing sounds like strategic curiosity.

Peter: Yes.

Ruairi: Peter, we are just about at time. Thank you very much for your time today. That was a really interesting conversation. Best of luck with everything at n-Tier.

Peter: My pleasure. Great speaking with you.

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