Ankit Goel is Chief Data and Analytics Officer at KeyBank, where he leads enterprise data and analytics strategy to support sustainable, profitable growth. His career has been defined by a consistent focus on delivering business value through a combination of advanced technology, process improvement, and practical execution.
Ankit began his career at Goldman Sachs, where he spent eight years building a strong foundation in data, analytics, and financial services. He later joined Freddie Mac, where he led several large-scale transformation initiatives. During his tenure, Ankit oversaw a multi-year cloud transformation of the company’s data ecosystem and developed strategies spanning business intelligence, machine learning, business rules, and enterprise data architecture.
In 2022, Ankit joined KeyBank to lead data and tools strategy for Enterprise Analytics. He was appointed Chief Data and Analytics Officer in November 2023, with a mandate to unify data and analytics strategy, governance, and execution across the organization.
Throughout his career, Ankit has maintained a clear guiding principle: data and AI initiatives must be anchored in business value. He emphasizes the importance of understanding the “why” behind every initiative, ensuring that technology investments are aligned with real business needs rather than pursued for their own sake.
Ankit’s leadership reflects a balanced, outcome-driven approach, focused on translating data capabilities into tangible impact.
As a data and AI leader, which traits and skills do you think matter most, and which of those have been most influential for you in your current position?
“Beyond the required technical and business skills, I strongly believe that an effective data and AI leader is a connector across the organization as well as someone who is an influencer without direct authority.
“Regardless of whether it is a centralized or federated operating model, data is a team sport, and leaders have an obligation to bring different parts of the organization together to ensure not only that consumers and producers of data are connected, but make certain that data is clear, high quality, and appropriate for the desired use. These traits become even more important as you look to scale analytics and AI, because success depends on fostering collaboration and driving alignment on shared goals.
“By building relationships and empowering others to see the value in data-driven solutions, a leader can break down silos and accelerate innovation. Ultimately, the ability to connect people and influence outcomes without relying on formal authority enables the organization to maximize the impact of its data and AI initiatives.”
Reflecting on your career, what is one non-traditional piece of advice (outside of technical skills) you would give to an aspiring data or AI leader aiming for the C-suite?
“One piece of non-traditional advice I would offer to aspiring data or AI leaders is to remain open to change and be willing to take personal risks.
“Early in my career, I chose to pursue a role in financial services, even as many of my peers were following more conventional engineering paths. In fact, some friends thought I had chosen a career in retail at Saks Fifth Avenue when in reality I was joining Goldman Sachs. This willingness to step outside the norm and enter new territory set the stage for my future growth.
“Similarly, about a decade ago, I volunteered to lead a data and BI team at a time when few truly understood what such efforts would involve, and most of my colleagues were hesitant to take on the challenge.
“These experiences, along with numerous other instances where I embraced change and placed a bet on myself, have been instrumental in shaping my career. While hard work and technical skills are clearly important, it has been my openness to new opportunities and my readiness to take risks that have shaped my professional journey.”