In an era where AI is accelerating faster than most organizations can absorb, many IT leaders are grappling with how to move quickly without creating fragmentation. For Leigh-Ann Russell, BNY’s CIO and global head of engineering, the answer comes down to a single word: coherence.
For Russell, coherence isn’t a slogan. It’s a leadership discipline that connects strategy to execution, technology to trust, and ambition to sustainability. In a recent episode of the Tech Whisperers podcast, she discussed why coherence is so integral to the modern CIO playbook and how to leverage it to scale impact instead of chaos.
Russell’s perspective is shaped by a career defined by range and resilience, from her formative years in Scotland to leading complex, high-stakes transformations across industries and geographies. After the podcast, we spent more time exploring how that journey has informed her leadership operating system, how she translates coherence into enterprise-scale AI execution, and why IT leaders must learn to navigate the intersection of innovation, control, and reusability. What follows is that conversation, edited for length and clarity.
Dan Roberts: Are there experiences from your formative years growing up in Scotland that shaped how you lead today?
Leigh-Ann Russell: I credit my father as the biggest inspiration in my life. He worked seven days a week and had two jobs, yet he was always present. When I look back, I don’t know how that was possible, for him to have a 7-day-a-week job and still take me to the park and to ballet lessons, or even afford ballet lessons. He was this embodiment of a combination of work ethic and family, and that’s how I’ve led.
There was also a lot about my life growing up that I hid. I hid the fact that I was a single parent. I hid the fact that I grew up in a council estate, similar to public housing in the US. I hid a number of things about me. It wasn’t until I got to be a bit more mature in life that I realized these were not things to hide. These are the stepping stones that make me the person I am.
My father taught me to do more with less and the power of work ethic. My daughter taught me ninja productivity skills. These were not things you should be uncomfortable about. These are things you should celebrate. My whole virtuous feedback on that, as a leader, if you share what makes you human, then it will be much easier to connect with other leaders and other people in your team. And then they feel comfortable sharing what makes their human foundation.
When the environment is complex, fast-moving, and high stakes, like it is today with AI, what are the core operating principles you return to as a leader, when you’re tired, under pressure, or being watched?
My core operating model centers on two things: talent and clarity. My philosophy is, my job is to find great talent and help them be the best version of themselves. If you achieve that, then real, magical things happen, because it’s people who create magic, not technology.
The second part of my role is about creating clarity. Life is complex, leadership is complex, and what teams need is simplicity. It’s about trying to simplify the problem, understand the trade-offs, and align people. Take AI as an example: The technology can create enormous value while also creating friction at scale if we’re not redesigning the work thoughtfully around it. That’s why it feels like the next leadership challenge — it’s not just about deploying AI well but designing the system around it with clarity and consistency in mind.
During the podcast, we talked about how you were very intentional in choosing coherence as your word of the year. Can you give some examples of coherence applied as a leadership discipline?
Coherence is a hard thing to build and a fast thing to lose. It starts with humans. It’s something Robin Vince, our CEO, does really well in bringing our leadership team together. He talks publicly about the fact that we all have a coach, and we have the same coaches from the same company and come together around that. He’s very intentional about creating coherence as a leadership structure.
As you go vertically down to the different meanings of coherence, it also applies equally to technology. It’s very easy to chase the shiny thing, and there’s a very tenuous conflict between people being empowered to do great innovation but also doing it in a structured way so that you avoid lack of controls or duplication or issues with architecture and costs firing out of control.
That double meaning of coherence and being very tight on the balance between individual innovation and empowerment and leadership becomes critical.
Can you talk about what your AI strategy looks like across the enterprise?
We set up the AI hub in 2023, and when I came to BNY in 2024, we started thinking about adoption and enablement across the enterprise, guided by our mantra: AI for everyone, for everywhere, for everything. In 2025, we set the goal of having 65% of the bank trained on AI, but we made 100% as early as June, and we’ve had to rewrite the training program twice since then to enable our employees to continue deepening their proficiency.
That enablement was important and we’ve had an amazing uptake, with over 220 AI solutions now in production accessible in Eliza, our enterprise AI platform. Eliza is built on the premise of foundational, reusable capabilities and is designed to enhance client service and company operations and drive cultural transformation through the power of AI. We talk more about Eliza and how we are advancing responsible and ethical AI in financial services on our BNY website.
Over half the bank have built their own agents, and we also have digital employees at the bank — 140 autonomous agentic employees who work alongside our human employees and that have direct human managers who monitor what logic is applied to decision-making. This is truly agentic.
So, 2025 was about widespread adoption and literacy, and now we’re moving from AI adoption to AI at the core. Even in the most complicated use cases that we’ve put into production, I still think they’re somewhat at the edges — anomaly detection, pulling together client briefing documents, or looking at contract reviews. Very advanced use cases compared to most enterprises, but we are pivoting in 2026 to having AI at the core of everything that we do at the bank. That’s truly transformational, and it’s the next step in our journey.
You have 140 digital employees, an idea that wasn’t even on the radar at the beginning of 2025. How did your organization move and adapt to scale that up so quickly?
It goes back to the philosophy that leadership is all about having talent and enabling them. We have an amazing team in engineering — and across the bank, because this is not just an engineering piece. If you look at our first digital employee, it was in the payment space, looking at reconciliations, and that was born out of a collaboration between engineering and operations. Our first human manager of a digital employee was in the operations side of the business.
Reimagining how work gets done can’t just be an engineering issue. It has to be in partnership with the business. Those individuals in the businesses and in engineering who can think back to first principles about how work gets done are leaping ahead on their AI journeys because they’re not just thinking about adding in AI as an afterthought; they’re thinking about redesigning their workflows with AI at the core.
A great recent example of that is in our onboarding process. We now have a multi-agentic model that has taken the research part of the process down from double-digit hours to single-digit minutes. This partnership and ability for our people to reimagine how we work with AI now at the core is foundational.
The strategy you’ve laid out really is a journey, and it seems there are some key foundational steps that many organizations are trying to skip, which is creating all sorts of problems for them.
In the podcast, we talked about the flip side of coherence being chaos. If you have chaos, AI will just amplify that chaos. That’s at a stack level or a leadership level. As the pressure is on companies to go out and adopt, this is where Eliza, our platform, has been truly instrumental to us because everything AI-related at the company is centralized in Eliza. It’s our tech stack; it’s our governance framework. Having one place for AI so you’re not chasing multiple tools and multiple companies, and having that very clear AI strategy embedded in a single platform, has been really differentiating for us.
In truth, there has been no single silver bullet in our AI journey. We have a tech-enthusiastic CEO in Robin Vince, who realized very early on that AI would be transformative for our company and has been determined that BNY remain at the forefront. With his leadership from the top, we invested early in our people to cultivate the AI-literate workforce we have today. So the fact that it’s a CEO-led strategy, plus the platform, plus the enablement has really helped us get to the speed of having 220 AI solutions in production supporting the enterprise.
Considering the strategic priority you’ve placed on AI adoption, how do you balance innovation and control?
Our goal is to enable innovation across the firm, which speaks to this mindset that being “AI first” is more important than just control. Obviously, we need control from a risk, compliance, legal, resilience, and cyber point of view, but from a financial and leadership perspective, we’re not trying to control and damp down and make everyone justify every single use case. As a result, we’ve said no to a lot less than I think most other companies would have done.
When I think about the trade-offs of that, it’s understanding “what is innovation?” and making sure there’s a reusable core. Because people have in their mind, “If I just hire my own engineers, and I have my own architecture, and I have my own software, I’m really innovative.” People tie innovation to having the new shiny thing, and it’s very hard to shift to a mindset that understands sometimes innovation is reusing what other teams have already developed and building on that. So, sometimes the more painful conversations involve trying to help people reground in reusability, common architectures, and common data platforms, understanding that isn’t hampering their innovation, it’s providing a solid foundation they can build on to go faster.
That intersectionality of innovation and control and reusability is the difficult thing we have to get right, because if you have too little control, you have the chaos we spoke about, and we know that AI amplifies chaos. If you have too much control and too much centralization, then you do hamper innovation. It’s something I’m very conscious of, that we don’t want to do either.
Great leadership often comes down to managing those tensions. What is the central tension you’re learning to navigate right now and how is it shaping the leader you’re becoming?
It goes back to a quote I mentioned in the podcast about Atticus Finch: How do you maintain your convictions without being rigid? Because one thing I know for sure, there are no right answers right now. Does one discipline shift left and one discipline shift right? What is the role of engineering in the future? There is absolutely no right answer to that. There’s only a set of choices that’s right for your institution, and what might be right for a marketing company will not be right for a regulated bank.
I use my digital twin to make sure I’m not too over-convicted, because I have that tendency, in my past growing up in the oil field and it’s a slightly Scottish tendency. So that’s the thing I’m really pushing myself on: How do I retain my conviction, but not become rigid, and stay really open to what is coming at us, because the change is like we’ve never seen — in a very positive way as an engineer, but we have to remain convicted, not rigid.
In world of “double VUCA,” where the impact of external volatility, uncertainty, complexity, and ambiguity is being compounded by fragmented AI journeys, a lack of clear AI strategy, and ineffective leadership internally, Leigh-Ann Russell shows us why coherence is an essential strategic discipline. In the age of AI, it can spell the difference between leaders who scale impact and those who simply scale chaos. For more insights from Russell’s leadership playbook, tune in to the Tech Whisperers.
Read More from This Article: Coherence: Where leadership and AI success intersect
Source: News