Shanthi Pudota is Senior Vice President and Chief Data Officer at BOK Financial, leading enterprise data, analytics, and AI strategy with a strong focus on measurable business outcomes. With a career rooted in data platforms and technology, she brings deep experience driving large-scale transformation across complex, regulated environments. Shanthi is known for bridging data, technology, and the business to simplify legacy ecosystems and scale trusted, responsible AI. A people-centered leader, she prioritizes empowerment, ownership, and accountability, building high-performing teams and cultures of experimentation that embed data-driven decision-making across the enterprise for long term organizational impact.
Recently, in an exclusive interview with CIO Magazine, Shanthi shared insights into her passion for driving business outcomes through data and AI, sparked by her experience bridging technology and business needs. Shanthi emphasized the importance of strong data foundations, governance, and responsible AI, and sees trends like decision intelligence and agent-driven workflows shaping the future of business. She also shared her personal hobbies and interests, future plans, words of wisdom, and much more. The following excerpts are taken from the interview.
Hi Shanthi. As a senior Enterprise Data, Analytics, and AI executive, what sparked your passion for driving business outcomes through data and AI, and how did you develop your expertise in this area?
I started my career on the technology side, focused on data and data platforms, and I’ve always enjoyed building the foundational capabilities that make data reliable and scalable. As I progressed, I became increasingly drawn to the business side, where I could see how data influences decisions, outcomes, and strategy.
What I enjoy most is working at the intersection of data, technology and business, bridging the gap between what’s technically possible and what the business truly needs. That experience shaped my expertise by forcing me to translate complex data and AI capabilities into practical, value‑driven solutions that leaders can trust and use every day.
As AI continues to evolve, that intersection has become even more important. My focus has been on ensuring strong data foundations and governance while enabling AI that is practical, responsible, and embedded into how the business operates, not as an experiment, but as a core capability.
What do you love the most about your current role?
What I love most about my current role is the ability to drive meaningful business outcomes by leveraging data and technology together. I’m able to bring years of transformation experience to help the organization move beyond technology adoption to real, measurable impact.
Having worked across both the technology and business sides, I’m in a position to connect strategy to execution, aligning data platforms, analytics, and AI with what the business is trying to achieve. That includes helping leaders reimagine how decisions are made, how risk is managed, and how customer experiences are delivered.
What’s especially rewarding is seeing data and AI become embedded into day‑to‑day operations, not as standalone initiatives, but as trusted capabilities that enable the business to move faster, make better decisions, and scale responsibly.
As data and AI continue to evolve, what trends do you see shaping the future of business and industry?
AI is rapidly moving from experimentation to execution, becoming embedded in core workflows like risk management, compliance, and customer engagement. As that happens, data quality, governance, metadata, and lineage become mission‑critical, not optional.
I also see strong momentum toward decision intelligence and agent‑driven workflows, where AI augments human judgment while operating within clear guardrails. The institutions that succeed will be those that anchor AI in strong data foundations and clear business outcomes, enabling innovation without compromising resilience or responsibility.
What are the key skills data and AI professionals need to develop to lead in a rapidly changing landscape?
To lead in this rapidly changing landscape, data and AI professionals need to develop a strong blend of technical depth, business acumen, and governance mindset. Technical fluency in modern data platforms, AI, and automation is essential, but it’s no longer sufficient on its own.
Equally important is the ability to connect data and AI to business outcomes, translating capabilities into decisions, risk reduction, and customer value. In regulated industries, professionals must also understand data quality, ethics, and governance to ensure AI is trusted, transparent, and scalable.
Can you share a book or resource that inspires you and why?
A book that continues to inspire me is Mindset: The New Psychology of Success by Carol Dweck, which explores the difference between a fixed mindset and a growth mindset. The core idea, that abilities can be developed through learning and effort rather than being fixed resonates strongly in the world of data and AI, where change is constant and learning never stops.
In my experience, a growth mindset is essential for transformation. It encourages experimentation, resilience, and continuous improvement, qualities that are critical when leading teams through data, analytics, and AI innovation. It also reinforces the importance of creating cultures where people feel safe to learn, adapt, and evolve alongside the technology.
What’s a favorite quote or mantra that guides you in your work?
A leadership mantra I anchor on is “Keep it simple.”
In our data and technology environments, especially in financial services, we operate with significant complexity driven by legacy systems and evolving business needs. As a leader, I believe it’s critical to maintain a continuous mindset of simplification, not by ignoring that complexity, but by intentionally managing it.
Focusing on simplicity helps create clarity for teams, reduces friction, and keeps everyone aligned on business outcomes rather than technology for technology’s sake. Strong leadership, in my view, is about cutting through complexity so the organization can move forward with purpose and deliver measurable impact.
How do you mentor and support emerging leaders in data and AI?
I focus on empowering emerging leaders by giving them real ownership, clear outcomes to drive, the authority to make decisions, and accountability for results. That ownership builds confidence and helps them grow from strong contributors into well‑rounded leaders.
I also work intentionally to create a culture of experimentation and learning. In data and AI, not every idea will work the first time, and that’s okay. I encourage teams to test, learn quickly, and adapt, while staying grounded in strong data foundations and responsible practices.
Most importantly, I stay closely engaged as a coach, asking questions, removing barriers, and helping leaders connect their work to business impact. When people feel trusted, supported, and accountable, they’re more willing to embrace change and lead through it.
What are some of your passions outside of work? What do you like to do in your time off?
Outside of work, I’m passionate about travel. Exploring new places and cultures helps me grow personally, it broadens my perspective, challenges my assumptions, and often gives me fresh ways of thinking about leadership and problem‑solving.
Family time is also incredibly important to me. No matter how busy things get, I try to be intentional about staying present and grounded with the people who matter most. That balance helps me recharge and show up more thoughtfully- both as a leader and as a person.
What is your biggest goal? Where do you see yourself in 5 years from now?
My biggest goal is to build and sustain data and AI capabilities that create lasting business value, not just short‑term wins. That means establishing strong foundations, modern operating models, and empowered teams that can continuously adapt as technology and business needs evolve.
Looking ahead five years, I see myself continuing to lead at the intersection of data, technology, and business transformation, helping organizations scale AI responsibly, simplify complex legacy environments, and embed data‑driven decision‑making into how the business operates every day.
Just as important, I want to be known for developing strong leaders and teams. Creating an environment where people are empowered, accountable, and confident leading change is a legacy that matters to me as much as technology itself.
What advice would you give to professionals looking to make an impact in data and AI leadership?
My advice is to lead with outcomes, not technology. The most impactful data and AI leaders start with the business problem and work backward, ensuring that analytics and AI are practical, trusted, and used.
It’s also critical to build strong foundations, data quality, metadata, governance, and operating models matter just as much as data and technology platforms. Without them, AI won’t scale responsibly or sustainably.
Equally important is to create space for experimentation and stay open to change. The landscape is evolving too quickly to rely on static skills or rigid thinking.
Finally, focus on simplifying complexity and communicating clearly. Great data and AI leaders operate at the intersection of technology and business, and their ability to bring clarity, trust, and momentum is what ultimately drives impact.