Welcome to HRTech Cube, Karthik. To kick things off, could you share a bit about your professional journey and what led you to your current role as Chief Product Officer at Cornerstone?
Thanks for having me! Throughout my career, I’ve had the opportunity to lead product, technology, and operations teams across several transformative companies – from GE Digital and Paypal to Yahoo! and eBay. The theme of my career has been to turn sparks into wildfires, building scale, driving growth, and managing growth profitability – all of this on a foundation of an inspiring purpose.
Throughout my career, I have come to realize that when human potential is harnessed and technology is used responsibly, the world is a better place. Cornerstone’s mission to help organizations and people to thrive in a constantly changing world is what drew me to the company three years ago. The velocity of change has only grown exponentially in the past three years, and the need to enable a high-performing, adaptable, and future-ready workforce is more important now than ever!
AI has quickly gone from buzzword to business imperative. In your view, how can organizations effectively scale productivity using AI agents without overwhelming their teams?
Let me unpack this into three themes. First, organizations must recognize the change and disruption that is happening real time. While this realization needs to be intrinsic, tools like Labor Market Intelligence can help leaders understand both existing and emerging skills, solving for any skills visibility gaps.
Second, they need to build awareness, fluency, and mastery in short order. While the essentials for building skills are common, a tailored learning and development strategy for specific functions, roles, and industries is key. Part of skill building is learning by doing and hands-on experience to the point of mastery. As with any transformative technology, success hinges on securing trust and buy-in from teams. The key to securing trust is by empowering teams with tools that help them work smarter and more confidently.
Third, organizations need to be ready for today and prepared for tomorrow by advancing their existing business with the power of AI, reinventing whenever possible. As a workforce agility company, we have developed a framework where AI augments human potential without replacing human values. The framework establishes a comprehensive structure with interconnected components that support a truly symbiotic relationship between humans and AI agents.
What are some of the biggest misconceptions you’ve seen when it comes to adopting AI-driven tools in the workplace?
The first and most dangerous misconception is the “who moved my cheese” syndrome, where there is resistance to adoption, even when disruption is not evident in the workplace. Resistance could stem from a mindset, toolset, or skillset issue, but ultimately comes down to curiosity and confidence. This resistance to change demonstrates why upskilling the workforce and taking people through a journey of awareness and mastery is key to deliver the highest ROI and prevent the otherwise inevitable spiral of adapting to change.
The second misconception is at the opposite end of the spectrum and is the fear that AI will completely replace humans at the workplace. To quote Amara’s law, “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.” The maximum effectiveness from AI comes from a truly symbiotic relationship between human and machine learning processes, freeing humans to focus on higher-level creative rather than repetitive tasks that AI will absorb.
The third misconception that comes to mind is that human skills are becoming less important as digital skills take shape. The opposite is true, and our studies show that human skills are 3x more in demand than digital skills. In a world where knowledge is democratized, wisdom becomes key.
Lastly, there is a misconception that adopting AI with a “do it yourself” approach and casual prompts can replace sophisticated capabilities. To address this misconception, companies must distinguish between the toy and the tool. There are infamous examples of organizations embarking on this journey alone and needing to reverse course. Working with partners who are adept at what they do will help deliver real outcomes.
How do you see AI agents transforming the employee experience, particularly in terms of learning, development, and engagement?
AI agents will transform the workforce to be more productive, engaged, confident, and adaptable. We are seeing AI transform the employee experience by embedding learning and development directly into the flow of work to support real workforce needs, from strengthening specific skills to meeting compliance requirements. For example, an AI-powered coach can help an employee in their learning journey, from making career recommendations to helping practice a pitch. Many of us have had amazing managers and mentors that have helped shape our thinking and advance our career – AI is helping to democratize this advantage, making mentorship available to everyone!
Another way AI is transforming learning, development, and talent management is by automating a significant portion of administrative tasks. We have seen productivity gains up to 75% with AI freeing teams from time-consuming systems and workflows, allowing them to focus more on people, not on processes.
Finally, just like how we have Agents for learning, we also provide learning for Agents. As the digital workforce multiplies, we need to ensure that they have the same training, skilling, and guardrails as our employees. At Cornerstone, we are helping organizations skill and govern their agents just like they do with their workforce.
From a product strategy standpoint, how are you ensuring AI innovation at Cornerstone is both ethical and practical for enterprise deployment?
As AI advances, we believe it must be used responsibly and purposefully. Our AI engine is ethical, in that it is built on a foundation of fairness and privacy to empower and protect our customers and their people. Our AI is responsible, in that it is designed for accountability and safe, impactful outcomes guided by rigorous governance and human oversight. Our AI is explainable because it is transparent by design to deliver clear insights into its decision-making, so you always know how it works. And our surrounding applications always have/can default to human-in-the-middle.
From a product strategy standpoint, three core tenets guide our approach to AI:
Use AI to augment experiences in moments that matter
Help enable excellence in the future of work
Promote leadership and responsibility in AI design and use, setting a positive example across the industry
We prioritize ethical AI along with the security and integrity of our models. Our AI systems operate within guardrails designed to prevent issues like hallucination, bias, or prompt injection.
Practically speaking, ensuring AI is enterprise-ready means rigorous testing, continuous monitoring, and clear compliance protocols to meet security and privacy standards. For over a decade, Cornerstone has integrated AI and machine learning into our platform with a continued focus on responsible innovation.
What advice would you give to leaders who are hesitant to embrace AI due to concerns around disruption or change management?
My first piece of advice is that the most dangerous strategy for leaders in the face of AI is to do nothing. AI is the most significant technology disruption we have seen in the last two decades and it is not a fad or hype that will fade away. I would urge leaders to first reconcile with that thesis and lead with curiosity.
Secondly, urgently develop your own AI fluency and invest in mastery, and ensure your organization does the same. Educating the entire workforce on AI is critical – even for roles previously considered “physical” or less likely for disruption. Don’t just play defence from becoming irrelevant, harness AI to unleash the potential of your business. Starting with curiosity and leading with clarity instead of fear will ensure your strategy is anchored in business value versus tech flashiness.
Lastly, don’t go at it alone. Platforms are rapidly evolving and offering out-of-the-box capabilities that can be leveraged successfully. A strong focus on your domain augmented with the foundational capabilities offered by commercial partners will remove upfront investment, shorten the learning curve, and provide the opportunity to move at pace without too many irreversible decisions.
As the demand for AI continues to grow, the whole world is learning and evolving. Experimentation in this rapidly shifting environment is key. An overengineered, over processed approach will become stale by the time it sees light of day.
How do you personally stay ahead of fast-moving trends in AI and apply those insights to your leadership and product decisions?
I am a glutton for information, and I read extensively, listen to podcasts, and try to absorb as much as possible. I also have some reverse mentoring mechanisms in place where I prioritize connecting deeply and learning from early career talent that are AI native. Surrounding myself with founders who have been in the AI space for a while, both within my staff and in informal advisory roles, helps to challenge my own thinking and inform product decisions.
I also believe supporting cross-functional collaboration across product, design, engineering, and QA ensures that teams can work together quickly and keep up with the latest trends.
Striving for continuous experimentation means understanding that innovation is an ongoing practice. To evolve, we must create regular opportunities to test new ideas and emerging trends. Doing so fosters a culture that drives fresh thinking and faster iterations, making it easier to keep up with the evolving AI landscape.
Looking ahead, which industries or business functions do you believe are most ripe for AI-powered productivity gains?
I truly believe every industry is ripe to achieve AI-powered productivity gains. In fact, Cornerstone’s 2024 Global State of the Skills Economy Report reveals that the demand for technological skills isn’t solely concentrated in traditional tech sectors like IT consulting and software development. Rather, we’re seeing a rising demand for digital and AI-related skills in industries like financial services, healthcare, pharmaceuticals, and banking, sectors that are increasingly interested in using technology to drive greater productivity.
What’s one piece of advice you’d offer to professionals or organizations just starting to explore the role of AI in their workflow?
I’d recommend viewing upskilling as a critical first step in integrating AI into the workflow. As AI continues to change how we work, professionals need to prioritize developing the skills required to work with AI tools effectively.
For organizations, investing in upskilling isn’t about keeping pace with technology; it’s about unlocking the full potential of your existing workforce. By equipping employees with the capabilities needed to work alongside AI, companies can ensure their teams are ready to meet evolving business demands.
Before we wrap up, any final thoughts on how companies can remain agile, people-first, and innovation-ready while navigating the ongoing evolution of AI?
The World Economic Forum projects that nearly 40% of skills will become outdated within 5 years, underscoring the criticality of tools and strategies that support reskilling and enhance workforce agility. To remain agile amid rapid AI innovation, companies must focus on closing the workforce readiness gap through continuous upskilling and reskilling. By leveraging real-time data and AI-powered analytics to address emerging skill gaps, organizations can build a flexible workforce capable of adapting quickly as technology and business needs evolve.
