Over a freewheeling conversation, TCS’ Chief Technology Officer, Dr. Harrick Vin, talks to Devina Joshi, Editor - @tcsmagazine about the latest tech innovations, real-world applications of AI and quantum computing, and advice for young professionals adapting to rapid tech changes.
How can we fuel sustained growth for our customers and ourselves in this rapidly shifting tech landscape? Is a mindset change needed?
Winners don’t just anticipate the future accurately; they possess the ability to adapt faster than everyone else. The mindset of driving proactive and swift changes is essential for fuelling sustained growth in a rapidly shifting technology landscape. In fact, with an accelerating pace of change, only the dynamic will survive: those organizations and individuals that master the art of inventing and adopting next practices, not just use best practices. Becoming dynamic requires every organization to master two critical skills. First, one must become good at foresighting—tracking and anticipating technology trends. Second, one must build perpetually adaptive enterprises–organizations that are designed for implementing changes swiftly. Let’s understand the need for foresighting. Every technology lifecycle follows an S-curve: an introductory phase, a long road to maturity, a rapid improvement phase, and then stagnation. Think of the trajectory of GenAI; it's the same story. It took many years of research to get to, and then in the last two years, we are in that hockey stick, the rapid rise phase. Eventually it, too, will plateau and then a new wave of technologies will emerge. The world of technology is really a collection of S-curves. At any given point in time, lots of things are at the beginning of the S-curve, some are in the rapid rise phase, while others are at the tapering end. Foresighting requires every organization to master the art of understanding these S-curves, so that they can decide when and how to redefine their work to best leverage technology trends.
Quantum computing is gaining traction but still feels distant for many industries. How do you see its practical impact unfolding for our clients?
I think quantum is probably three to five years away for large-scale deployments. At the moment, experimental-scale quantum machines are available. In fact, TCS has partnered with IBM to set up the Quantum Valley in Amaravati, which will bring the first quantum machine to India—that's a fantastic start for us. Quantum machines are well suited for search space exploration problems. These include problems such as finding the best-suited drug molecule from among a very large number of possible combinations for a target disease or even finding an optimal strategy for equity portfolio optimization, by selecting the best combination of available stocks to achieve the desired returns, while minimizing risks. These ‘what-if’ and ‘if-what’ types of questions are computationally intractable on today’s computational architectures. Currently, it could take months or years to find good answers at a large scale. With quantum processors, that will happen in minutes or hours. Therefore, it could redefine many industry domains.
Like healthcare?
Like healthcare, particularly precision medicine. We have ongoing research in precision oncology, which is about personalizing drugs for cancer patients, maybe even 3D printed on the spot, for each patient. In another 5-10 years, we will see such personalized treatments of patients dramatically improving treatment effectiveness, eliminating trial and error or side effects. It is important to note that in addition to quantum computing, we are also witnessing significant advances in quantum sensing and communication technologies. We are working with India's National Quantum Mission as well as many academic institutions on these emerging technologies. With IIT Bombay, for instance, we are working on quantum sensing technology that could detect a defect in a semiconductor chip.
How is technology reshaping the energy value chain, and what strategic steps is TCS taking to help clients lead the energy transition?
Energy transition isn’t just about moving from fossil fuels to renewables, but it is also about mastering the art of managing a complex energy ecosystem, with heterogeneous energy sources with different cost- performance and variability trade-offs. Till date, we have used linear energy networks: an energy producer, a distributor, a utility company dealing with the last mile and the end consumers/ homes. With renewable sources, every household or organization becomes a prosumer. For instance, many enterprises and even TCS campuses are prosumers, because we have solar panels on our rooftops producing our own energy, but we also consume energy from the grid. So now, the linear chain is becoming a fully connected network, almost like the information internet where today each one of us is both producing and consuming content. Tomorrow, we will have an energy internet which will connect prosumers of energy, and that is going to be the biggest transition. With energy production in every home, neighbourhood, and enterprise, there will be the question of storing and managing energy like a network of sources to meet demand. For example, if my solar panel is producing electricity, should I store it, use it, or pump it out and make money? Or if I am to buy energy, when is a good time? How do we discover an energy source and arrive at a value exchange? The future will be about answering such questions, about managing the ecosystem of producers, consumers, and sources. At TCS, we are building an energy internet platform to help manage this transition.
Which tech development are you personally most excited about?
Building what we call ‘genius partners’ for every person is exciting to me. If we can build technology that will make every person supercharged or superpowered, it will turn people into superhuman beings. That is the Nirvana… intelligent machines empowering everyone to punch well above their weight and become the best they can be. A world where we will have a genius partner for every person, for every aspect of their life, whether it is personal finance, health and wellness, or their career, is only a matter of time. Let’s take the example of a genius partner for career management. As we know, the infusion of AI will not only redefine work across domains but will also change the roles of people. As machines become more intelligent, the roles of people and the skills required will change constantly. Can we imagine a genius partner for every person who can provide personalized nudges to build the required skills for the future, as well as help shape her career trajectory? With an increasing pace of change, the current best practice is not likely to work in the future. A choice, whether of skill or career, that someone made several years ago that served them well then, may not be the right choice today. When the world around you is changing fast, one can't really drive by looking at the rearview mirror. So, how do you do this looking forward? That's where an intelligent machine can become an incredibly powerful partner.
How does TCS approach issues such as regulatory compliance, responsible innovation, and the safe, equitable scaling of AI?
AI, especially GenAI, is still an emerging technology— lots of unknowns, and that means we must tread carefully. Most certainly, matters like ethics, data privacy and regulatory compliance must be given the highest attention, and we are doing so. And beyond these, AI presents challenges we have never experienced before. Take, for example, agentic AI solutions that are self-evolving. These systems continuously change their behaviour as they learn from data, making them inherently both non-deterministic and adaptive. If we look at all traditional IT systems that we have been dealing with until today, they have all been deterministic and fixed, so functional testing was easier. Self-adaptive systems are challenging to assess, as they change over time. Traditional one-time testing is insufficient; instead, an ongoing monitoring of functionality is critical to ensure they don’t deviate or drift and remain aligned with intended behaviour. As these systems become more intelligent and autonomous, new questions arise in terms of ethical use, regulatory requirements as well as assurance that the system or machine won’t do something unintended or harmful. These are all difficult problems, and the entire industry is grappling with them. They are part of the growing pains of any transformative new technology. That is why our academic partnerships are so important as they help us tap into diverse expertise and gain fresh perspectives. Ultimately, responsible AI isn’t just about following regulations — it’s about building the vigilance, adaptability, and collaborative learning needed to scale it safely and equitably.
Speaking of academic partnerships, TCS COINTM has over 50 such. How are we leveraging them to access leading tech talent?
Our academic partnerships are more than collaborations; they are gateways to the world’s best minds. We leverage academic relationships to identify world-class researchers to partner with, as well as to provide our talent opportunities to engage in collaborative research with them and thereby grow. We identify leading people, universities, and organizations that match our areas of strategic investments. For example, when extensive work on data privacy was needed 15-20 years back, we had partnered with Stanford. Today, we are working with MIT on the future of agentic networks, and with Carnegie Mellon University for AI assurance. Once we establish strategic partnerships, our research and innovation teams engage with students and faculty members at the institutions on a bidirectional exchange of ideas, which helps both organizations. Through these exchanges, we expose industry challenges to our partners and bring innovative ideas from our partners back to construct novel industry solutions. In effect, we create an applied innovation bridge between real world challenges and academic excellence.
You are among the ‘Top 30 Indians Leading the AI Revolution’ by Forbes India and one of India’s 100 Most Influential People in Technology and Innovation’ by MIT Sloan Management Review India. What does this mean to you?
Being recognized by Forbes and MIT Sloan is both humbling and energizing. It is not only a personal milestone, but also a recognition of the collective journey we have undertaken at TCS. Let me reflect upon some of the key highlights of this incredible journey. Since I joined TCS in 2005, I have been intrigued by the possibility of using machine intelligence to deal with the complexity of large systems. In fact, over the years, we have explored three types of complex systems: engineering systems, people systems, and, of course, technology systems. In large engineering systems, for example, we contributed to the design of intelligent control systems for some of the most complex engineering projects of recent times, including the International Thermonuclear Experimental Reactor (ITER) project which is like developing a 'Sun in a box' using fusion technology, in France; and the Square Kilometre Array (SKA) project developing the world’s largest radio telescope, in collaboration with the National Centre for Radio Astrophysics (NCRA). For large-scale people systems, we studied TCS itself with over 600,000 employees – we’re one of the largest universities, as I like to say. We started by leveraging machine intelligence to drive personalized talent development at scale. In the case of technology systems, in 2007, we built eTransform, an AI tool for intelligent planning and execution of IT infrastructure transformation programs for our large customers. This led to the rapid growth of the IT infrastructure services business. In 2015, we launched ignio™, the world’s first cognitive automation platform. ignio™ can be seen as an early version of GenAI; it had the ability to auto- generate context-specific procedures (code) to resolve IT incidents or handle service requests autonomously, driving significant improvements in productivity. With the advent of modern GenAI models, over the past couple of years, we are asking the question: how best can machines and people coexist to build a hybrid workforce, each assisting and augmenting the other? What is the future of work in the presence of such a hybrid workforce? And the exciting journey continues. So, to sum it up: It is, indeed, an honour to be recognized among an esteemed and eclectic group of people — from across academic institutions, startups, large companies, and research labs — known for their innovation in AI globally. The recognition reaffirms the significance of our contributions over the past two decades.
As our CTO, how do you view the significance of cultivating a culture of innovation in the organization?
Building a culture of innovation requires instilling people with skills, such as creative dissatisfaction, the ability to deal with ambiguity, being proactive and not reactive, having conviction in one’s belief, and finally the ability to persist and persevere through failures. Let me elaborate on ‘creative dissatisfaction,’ which can be best described as the relentless pursuit of self-betterment. This often requires people to step out of their comfort zones and do something different or do the same differently. For great innovation to happen, you must not stop at the first right answer; keep looking for the next best. This holds true across all domains. In today’s world of AI and intelligent machines, I believe these soft skills are going to become even more important. As machines become increasingly intelligent, the role of people shifts from doers of work to trainers and interrogators of machines, reviewers of work done by machines, as well as owners of creativity and critical thinking. People will need to focus more on the ‘why’ and the ‘what,’ and a lot less on the ‘how,’ because the ‘how’ will be handled by the machine. It is also important to note that innovation shouldn’t be seen as an occasional activity; it is something that one does every day. More often than not, however, many organizations and teams tend to outsource innovation, or track innovation as a compliance requirement. Ideally, innovation culture must be part of an individual’s and an organization’s DNA.
Finally, what would you advise young professionals looking to make a difference through a career in Research and Innovation?
My advice would be to remain hungry to learn and nurture the habit of creative dissatisfaction. Additionally, I recommend mastering at least one functional domain, as the most significant innovations of the future will occur at the intersection of functional and technological domains. For example, the future of energy management will blend AI with the fundamentals of energy production and distribution; for precision oncology, one would need to combine computational methods with knowledge about biology and chemistry. A multidisciplinary approach is essential for future breakthroughs.