Chandra Shukla is an AI & Data Consultant at Ernst & Young (EY), where he helps Fortune 500 clients leverage advanced AI, machine learning, and optimization for critical enterprise applications. He has also developed Agentic AI solutions for the private equity (PE) sector to drive sustained business advantage for investors and portfolio companies. Chandra has a long history of applying AI across financial services and multiple other industries prior to joining EY. He enjoys advising startups dedicated to harnessing AI for the strategic and competitive advantage of the industry.
He attended an Ivy League MBA program as a Merit Scholar, earned a master’s degree from the University of Michigan, serving in academic leadership roles, and graduated at the top of his class from IIT in India. He is an IEEE Senior Member and also advises academic programs in universities focused on AI. He mentors at UC Berkeley’s Big Ideas Contest and was a Data Science for Social Good Fellow during his time at Michigan. His contributions have been recognized by his previous company leaderships and at the industry level for critical roles. He collaborates with corporate leaders, consulting firms, and venture investors to advance AI adoption and innovation.
“Views expressed in this interview are personal and do not reflect the views of EY or its affiliates.”
Recently, in an exclusive interview with CIO Magazine, Chandra shared insights into his career journey, the transformative power of AI, the secret mantra behind his success, personal hobbies and interests, future plans, words of wisdom, and much more. The following excerpts are taken from the interview.
What inspired you to pursue a career in technology, and what were some early challenges you faced?
I was naturally good in science and math since childhood, and there was also a strong cultural preference for engineering in the environment I grew up in. So, in many ways, both internal and external forces converged toward a career in technology. It felt like the most logical and empowering path.
Another significant factor in shaping my journey was the rapidly changing environment I grew up in. My father had a transferrable job, so we changed schools and cities every few years. It was a bit like a slash and burn civilization where nothing was accumulative, and I had to restart each time. That taught me resilience, adaptability, and how to stay on my toes. At the time, it felt like constant disruption, but now I see it as essential training. Each move forced me to rebuild, to reestablish myself, and to grow sharper socially and intellectually. These early resets helped me become a systems thinker, someone who doesn’t just survive complexity but thrives in it. Now, I realize that those very disruptions mirror the essence of the tech world I work in. Technology is about constant change and reinvention-and I genuinely enjoy operating in such dynamic environments.
What do you love the most about your current role?
My current role allows me to empower people, teams, and organizations through the transformative power of AI and ML. We help increase productivity, optimize decision-making, and create measurable impact on both the top and bottom line. What excites me most is seeing how data and technology can unlock hidden potential, whether it’s enabling smarter operations, faster innovation, or deeper human insight. I also love working across disciplines, bridging the gap between strategic intent and technical execution. And finally, I take great satisfaction in mentoring others and contributing to a culture that values continuous learning, experimentation, and ethical innovation.
How do you see AI transforming industries in the next 5–10 years, and what role do you think data scientists will play?
In the time to come, the pace of technological innovation will accelerate even further, reshaping industries across the board. AI will become not just a support tool, but a dynamic driver of value creation, automating decision making, reimagining customer experiences, and enabling real time adaptability in operations.
At the same time, the barrier to entry into the field of data science will continue to lower due to widespread availability of tools, models, and platforms. This democratization will lead to more participation, but also more noise-so the true differentiators will be those who can deliver lasting, human centered value. Skills like emotional intelligence, empathy, systems thinking, and ethical foresight will become crucial for data scientists to lead with impact.
In that future, data scientists won’t just be coders or analysts, they’ll be designers of adaptive ecosystems, facilitators of trust in intelligent systems, and translators between humans and machines. The ones who can combine technical expertise with deeply human skills will shape the next era of AI transformation.
What qualities do you believe are essential for effective leadership in AI and data science, and how do you embody those qualities?
Effective leadership in AI starts with having a clear sense of purpose, keeping the bigger goal in mind and treating AI as a supporting driver, not the destination. Leaders must know how to align technology with meaningful outcomes. Beyond that, clarity of vision, adaptability, and an ethical mindset can take leaders very far.
As the landscape evolves rapidly, the ability to simplify complexity, bring diverse teams together, and stay grounded in the human impact of AI is what sets true leaders apart. I aim to lead by example, using systems thinking to solve root problems, creating frameworks others can build upon, and always driving toward long term, sustainable impact.
What trends or advancements in AI are you most excited about, and how do you see them impacting your work?
AI is empowering people across the globe by unlocking access, insights, and capabilities that were once limited to a few. As the cost of development and deployment continues to decrease, the playing field is becoming more level. Individuals, startups, and organizations of all sizes can now tap into cutting edge tools. This is both exciting and humbling.
However, AI is also a double-edged sword. Its misuse can lead to ethical, social, and economic consequences. So, it must be used with responsibility and intention. In my work, I try to channel these advancements to create systems that are not only intelligent but also aligned with human values.
I’m especially excited about foundation models and agentic systems that are moving us from automation to co-creation, where AI doesn’t just respond but collaborates. These innovations shift how we think about workflows, impact, and the role of human agency in technology led transformation.
You were recently recognized among The Top 25 Artificial Intelligence Consultants and Leaders of 2025. Our readers would love to know the secret mantra behind your success.
There are a large number of people who are far more capable but may not have made it to the list, and that makes me feel both humbled and grounded. Recognition is meaningful, but I always remind myself that it’s not the full measure of someone’s journey or contribution.
If I had to distill the core of my approach, I’d say: persistent learning, strategic patience, and showing up where others hesitate. I’ve learned to be comfortable operating at the edges, between business and tech, strategy and execution. That mindset has helped me consistently bring structure to ambiguity and build resilient systems that adapt and scale. And I never stop refining the systems I build, whether it’s for clients or for myself.
Is there a particular person you are grateful for who helped get you to where you are?
I’m deeply grateful to mentors who believed in me at times when I didn’t have the pedigree or credentials others expected. One former manager in particular pushed me to think not just about solving problems but about solving problems in ways that scale, evolve, and invite others to build on them. That mindset changed everything for me.
With every winning match, there are many others that came before it, moments of loss, mistakes, and setbacks. They all contributed. I’m thankful for those experiences because they made me harder, stronger, and more grounded. I’m also deeply appreciative of the people, resources, and opportunities that came along the way and helped me discover my path.
What are some of your passions outside of work? What do you like to do in your time off?
Outside of work, I enjoy long meditative walks and reflective thinking. I’m drawn to systems, whether in nature, philosophy, or strategy. I often write, sketch out frameworks, or study how different disciplines intersect. It’s not just downtime, it’s how I recharge and realign.
What truly brings me joy is having free flowing, unstructured conversations with friends who are far more brilliant than I am. There’s something magical about wandering through big questions with no agenda, it’s intellectually nourishing and emotionally grounding. These dialogues keep me connected, inspired, and curious.
I’m also deeply interested in Ayurveda and Vedic thought, which keeps me rooted and offers a timeless lens on balance, purpose, and wellbeing.
What is your biggest goal? Where do you see yourself in 5 years from now?
In five years, I want to be leading an innovation unit at the intersection of AI, strategy, and system design, either within a global enterprise or through my own firm. I see myself building platforms that not only transform businesses but also enable more ethical, sustainable, and human aligned growth. I want to be known for the systems I built and the leaders I helped shape.
But more than titles or roles, my biggest goal is to make a humble attempt to leave the world better than I found it. I aspire to give back to society far more than what it has given to me, in both tangible and intangible ways. Whether through the technologies I help build, the people I mentor, or the systems I influence. I want to contribute to something larger than myself.
What advice would you give to aspiring data scientists and AI leaders looking to make a similar impact?
Don’t just chase skills, chase systems. Learn how decisions are made, how incentives are designed, and how change really happens. Build fluency across domains business, behavior, and data.
And most importantly, don’t get caught up in chasing technology for its own sake. Try to see the world more holistically and understand where technology fits within the broader objective. When you operate with that clarity, technology becomes a powerful means, not the end.
And finally, don’t wait for permission to lead. Start designing, start building, and bring others along. Your impact isn’t just in the models you build, it’s in the change you make possible.