Tarun Sood is Chief Data and AI Officer at American Century Investments, where he leads enterprise data and AI strategy to drive business growth, operational efficiency, and better decision-making. His leadership has been defined by a focus on building scalable, trusted data capabilities that deliver measurable outcomes.
Throughout his career, Tarun has concentrated on establishing modern data platforms, strengthening governance, and designing operating models that balance innovation with reliability and risk management. In senior leadership roles, including his current position, Tarun has led enterprise-wide data and AI transformations, aligning strategy, technology, and talent closely with business priorities.
A key element of Tarun’s approach is building high-performing, product-oriented teams with clear ownership, shared accountability, and fast decision-making. He has worked extensively with executive stakeholders to ensure that data and AI initiatives are embedded within core business processes rather than operating as isolated technical functions.
Tarun’s perspective reflects a pragmatic understanding of what it takes to scale AI successfully. He believes that organizational design, trust, and change management are just as critical as the underlying technology. His leadership philosophy centers on empowering teams, avoiding single points of failure, and creating resilient data and AI ecosystems that can scale effectively over time.
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?
“Effective data and AI leadership requires a balance of strategic, technical, and human‑centric skills. First and foremost is business acumen or the ability to anchor data and AI initiatives to real business outcomes and make clear trade‑offs on where to invest. Without this, even strong technical capabilities fail to deliver value.
“Equally important is organizational leadership: designing operating models, clarifying ownership, and building empowered, cross‑functional teams. Data and AI efforts succeed at scale only when leaders can foster collaboration, avoid single points of failure, and create shared accountability across technology and business partners.
“Trust and credibility are also critical traits. This includes establishing strong data governance, responsible AI practices, and transparent decision‑making, all of which are essential for sustained adoption and executive confidence. Alongside this, effective communication, such as the ability to translate complex concepts into clear, actionable insights, enables alignment at every level of the organization.”
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 non‑traditional piece of advice I would give aspiring data or AI leaders is to invest as much in organizational fluency as in domain expertise. Advancing to the C‑suite is less about being the smartest person in the room and more about understanding how decisions are really made, like what incentives drive behavior, where power and influence sit, and how trust is built over time.
“In my experience, the most effective data and AI leaders learn to navigate ambiguity, build coalitions, and influence outcomes without relying on formal authority. This includes knowing when to push, when to simplify, and when to let others take ownership. Developing strong judgment, patience, and credibility across functions is often more impactful than any single technical achievement.”