Krishna Cheriath is Vice President and Head of Digital and AI (CDAIO) for Biopharma Services at Thermo Fisher Scientific, where he leads digital and AI strategy across a $15 billion global division focused on transforming drug development. With more than 30 years of experience across consulting, technology, and executive leadership in life sciences and healthcare, Krishna brings a pragmatic, business-first perspective to data and AI leadership.
Krishna began his career in global consulting and technology services, building a strong foundation in enterprise systems, analytics, and operating model design. In these early roles, he worked closely with business leaders to address complex, cross-functional challenges and develop scalable technology-enabled solutions.
A pivotal phase of Krishna’s career came during his time at Bristol Myers Squibb, where he held several senior leadership positions, including Chief Data Officer and Head of Digital Strategy. In these roles, Krishna partnered with the CEO and board to define enterprise data, digital, and AI strategy, balancing innovation with governance and ethical oversight. His work delivered more than $100 million in measurable value across research and development, commercialization, and manufacturing. Serving as Data Protection Officer further reinforced his focus on trust and responsible data use.
Krishna later served as Chief Data, Analytics, and AI Officer at Zoetis, where he focused on industrializing analytics and AI by building global platforms, scaling teams, and embedding digital capabilities across the organization.
Across his career, Krishna has operated at the intersection of strategy, technology, governance, and culture, where lasting impact depends as much on leadership and trust as on technology itself.
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 is less about technical mastery and more about how leaders navigate complexity, uncertainty, and people. One of the most critical traits is comfort with ambiguity. Data and AI initiatives rarely come with perfect information or clear precedents, and leaders must make directional decisions, align stakeholders, and move forward while the answers are still evolving.
“Equally important is the ability to lead both from the front and from behind. At times, data and AI leaders must step forward to set direction, challenge assumptions, and advocate for change. At other moments, the greatest impact comes from empowering others, creating space for teams and business partners to lead, learn, and succeed. Leadership, ultimately, is about followership.
“Another defining skill is the discipline to play the long game of impact. It is easy to become consumed by daily skirmishes such as emails, meetings, process friction, and short-term wins. The most effective leaders consistently step back and focus on the lasting positive impact they can make in the work itself, in the organization, and in the people around them. This long-term perspective enables resilience, better decision-making, and sustained value creation.
“Finally, having a compelling vision and the ability to communicate it clearly has been especially influential in my organization. A shared vision aligns teams, builds trust, and sets others up for success, enabling data and AI to become a true enterprise capability rather than a functional specialty.”
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?
“The most successful Chief Data, Digital, and AI Officers are not defined primarily by their technical depth, but by their ability to span boundaries that most leaders avoid. They operate simultaneously as business strategists and digital, data, and AI strategists; as visionaries who can see what is possible and storytellers who can make others believe it is inevitable; as educators who raise organizational literacy and, at times, as informal therapists who help leaders work through fear, skepticism, and change fatigue.
“Data and AI transformations are rarely constrained by algorithms or platforms. They are constrained by misaligned incentives, unclear decision rights, cultural resistance, and unspoken anxieties about relevance and power. A CDAIO who cannot navigate these human and organizational dynamics will struggle to translate insight into impact, regardless of technical excellence.
“My advice to aspiring leaders is therefore to invest as much energy in understanding people, language, and context as you do in understanding models and architectures. Learn how the business really makes decisions, how executives process uncertainty, and how to reframe data and AI from ‘technology initiatives’ into narratives of growth, resilience, and competitive advantage. At the C-suite level, influence comes less from being right and more from helping others see, decide, and act with confidence.
“In short, the path to impact, and to the C-suite, runs through the boundaries between disciplines, functions, and mindsets. Learn to live there comfortably.”