AI in Your Corner Office – But Who’s Really In-Charge?
A Kingsley Gate Perspective on Leading Through the AI-Talent Transformation based on our recent executive roundtable
In boardrooms across India, conversations are unfolding, which most leaders acknowledge privately but few discuss openly. There is considerable celebration of the promise that the computational capabilities of AI offers, but the real disruption is happening in an unexpected place: The widening gap between the evolution of technology and organizational transformation. 70% of the Indian workforce is unaware of the full potential of AI and what it can achieve, while companies continue to invest three times more in technology advancements than towards equipping their employees to adapt to this rapid digital transformation.
We brought together sixteen senior leaders with diverse backgrounds across technology, financial services, healthcare, manufacturing, and consulting to confront and deconstruct these issues, address ground realities, and offer their expertise to pave the way forward. Given that technology is advancing faster than our ability to use it optimally, the agenda evolved into discussing how to overcome some prevalent adoption challenges.
When polled about the top concerns that have emerged since the advent of AI, ‘reskilling speed vs. business transformation pace’ emerged as the most pressing issue.
Moderated by Avnish Sabharwal, the MD at Accenture Ventures & Ecosystem, and Umesh Ramakrishnan, the Co-founder & Chief Strategy Officer at Kingsley Gate, with support from Noam Eisenberg, Senior Partner and Head of Global Business Services, and Arushi Bhattacharya, Partner APAC at Kingsley Gate, the conversation addressed uncomfortable truths through mindful, well-thought out questions that cut to the heart of workforce anxiety. Through the course of discussion, leaders addressed the fear of talent obsolescence, the guilt of workforce displacement, and uncertainty about autonomous leadership impact and relevance in an AI-augmented future.
The Great Resistance: Why Change is Hard
A paradox was identified early in the discussion: Everyone wants change, but no one wants to change. This observation was substantiated by a sobering realization: While organizations are implementing ‘Ask Me Anything’ AI modules across platforms to fundamentally alter how knowledge flows through corporate hierarchies, the human element is still frozen in time.
Umesh probed deeper into this paradox, trying to understand what happens when human resistance becomes an impediment to organizational survival. The financial services sector was an initial example discussed, delving into the human response to systematic enterprise-level automation of trade settlements, basic AML checks, and routine compliance work, all of which were once foundational to entry-level finance careers.
Vivek Kadal, the Strategy and Transformation Leader at Bosch Software & Digital Solutions, addressed this human element when he asked the room whether global capability centers should be measured on KPI efficiency or empathy. He posed caution, stating that as AI phases out roles, it brings up fundamental questions of value that organizations are yet to fully answer.
This complexity runs deeper than individual roles, with Avnish highlighting the concerning imbalance between India’s young and diverse workforce, and companies investing 300% more in technology than in upskilling people. In an ever-charged and dynamic sociopolitical landscape, he advocates a framework where the leadership that sits at the intersection of technology and people develops a robust, considerate balance between these emerging technologies and those using it.
A key obstacle to striking that balance was framed succinctly by the head of business strategy, planning, and governance at a leading financial services and bank holding multinational company, who stated, “As leaders, the real challenge is adapting to change. How can AI and humans collaborate instead of competing?” She reflected on a paradigm shift, where there is a resistance to turning to ChatGPT instead of doing personal research. This realization was telling of how deeply AI challenges individual professional identities, and therefore, the workforce.
Another concern that was addressed through the course of the conversation was the shared experiences with AI’s limitations. The head of strategy & innovation at British banking and insurance holding company leads a team that spends significant time checking AI-generated research, elaborated on one common challenge: Hallucination. She acknowledged “the genuine strengths AI brings in putting things in a structure, while highlighting that it cannot be fully relied on for specificity.”
This nuanced understanding of the values and the setbacks emerged as a critical focal point for conversations between organizations that were struggling with AI and those that were making it work. It led to an interesting question: How do you build systems to leverage AI capabilities while retaining human insight where it matters most?
Perhaps the most relevant take on human insight and oversight came from an industry where these questions become a matter of life and death. Sathish Balakrishnan, the VP and Head of Global R&D for Philips, shared an insight from the med-tech domain that directly addressed the need for human intervention. He stated, “In medtech, Copilot integration has become a standout example – we have trained it so well, it delivers results at Nobel-level precision. That said, AI is a methodology; it is a tool to augment humans, not to replace them. Even if 90% of the work is done by AI, humans are required to review and sign off.”
His statement addressed the emerging perspective transformation across sectors: It is not human vs. AI, it is human-verified AI – a model that requires rethinking and optimizing traditional workflows and accountability structures.
This perspective was backed by another med-tech leader. The senior director at a global medical technology company, offered a strong example, saying, “In joint surgery, body scans that previously took over two weeks can now generate physician reports within minutes. This acceleration is dramatic, and it is ‘life-and-death.'” He emphasized that improved velocity cannot compromise accuracy, nor can it come at the cost of removing human judgment from critical, high-stakes decision-making.
Another interesting insight came from the manufacturing sector, traditionally seen as the sector most ‘vulnerable’ to automation. Gopikrishnan Balijepally, the former SVP and India Leader for Hitachi Digital, had an unconventional story, sharing, “An AI agent was used to check the hand-finishing on capacitors. It reduced the rejection rate by 50%.” While the efficiency enhancement alone would justify the investment, he shared that “it came with a positive development for the workforce. Initially, the union was concerned about redundancies, but having transitioned from repetitive visual inspections to data analysis and process improvement, workers have been happier with the integration. This level of engagement came from better utilizing their experience and judgment in their work.”
While the outcomes are promising, the transition into achieving collaboration and employee satisfaction is not without its challenges. With key forward-thinking leaders in attendance, a cornerstone of the discussion was to address that challenge by talking about the future: The need for continuous innovation.
Highlighting a critical changemaker, the organizational mindset, Manasvi Sharma, an independent senior technology leader, reiterated, “Historically, organizations were designed to be delivery-centric. AI can now take over that layer. Human contribution must pivot to critical thinking and creativity. While AI takes on delivery-focused work, humans excel at innovation.”
The formula to measure this contribution goes beyond updating KPIs: It requires fundamentally rethinking how organizations create, assess, and capture value. Pointing to structural barriers, Amit Kalra, the MD & Head of Global Business Solutions at Swiss Re, noted, “With large organizations remaining siloed, genAI can help redesign workflows, drive transformation and reduce bottlenecks.” Still, he observed, “Most solutions might not come from within,” questioning the traditional internal innovation model relied upon for decades.
Echoing this, Sourabh Gupta, the APAC Digital Platform Leader for Raytheon Technologies, had a practical answer, offering, “Most of the solutions might not come from within. Do a short ‘bullet-pitch’ reflecting a new reality where rapid experimentation beats lengthy planning. Traditional strategic planning cycles would struggle to keep pace with AI’s evolution. Organizations need new approaches that balance speed with thoughtfulness.”
Identifying the opportunity within the task ahead, Amit also shared, “This is not ‘doomsday’ for fresh graduates. The new generation is AI-savvy, with the capacity to start businesses with minimal resources.”
This democratization of capability, where a small team with AI can compete with established enterprises, represents both a degree of existential threat to traditional organizations and a multitude of avenues for those willing to adapt. Even for the latter, the pace of this transformation has been so unprecedented, it has caught the most prepared leaders off guard. Sourabh reiterated, “The speed of the change was the most surprising factor, and while some jobs may face redundancy, the focus should be on managing that uncertainty constructively.”
Noam brought a global context to relate to this evolution and the urgency of enterprise-level adoption. Drawing from his experience across markets, he noted that multinational competitors were already moving from implementation to integration. “The question isn’t whether AI will transform your industry,” he observed, “but whether you’ll be leading that transformation, or scrambling to catch up.”
Vidya Munirathnam, the VP HR at Lowe’s India, demonstrated what equipping the workforce for success in the digital age looks like in practice. She shared, “At Lowe’s, we view AI as a way to transform how we shop, sell, and work. When it comes to how we work, we gave everyone organizational access to ChatGPT through our enterprise system to maintain internal control and protect data.” She added, “We also leverage GenAI through Mylow Companion to empower our store associates to deliver a richer, more connected shopping experience. It enables them to confidently answer product questions to support customers across categories, breaking barriers between departments and creating a seamless, informed in-store experience.” Knowledge silos that took decades to build dissolved in months, with technology breaking the barriers to information, rewarding proactivity and self-skilling initiative.
Surendra Bashani, the Head of Best Buy India, offered a striking example of value-creation in this new ecosystem. He shared the story of a young entrepreneur who used AI and built a company that was acquired for $80M in 6 months. Yet he also noted the flip side, “The pace of change differs from previous technology adoption. One person now replaces five in certain functions.”
This concentration of capability raises profound questions about employment, opportunity, and social stability.
The Skills That Matter When Machines Can Think
We turned to these leaders to answer some of those questions, and the results of our polling data challenged conventional wisdom about the future of work.
When asked which human capabilities become more valuable in an AI-driven future, leaders didn’t point to technical skills. Instead, they identified a constellation of distinctly human capabilities:
This distribution suggests the future does not offer an ‘AI-proof’ skill, but a diverse portfolio of capabilities that require human judgment, creativity, and emotional intelligence.
The educational implications of this are foundational and monumental. Arvind Rathore, the MD and Acting Site Leader at Ferguson, expanded on the educational implications with a sharper observation, “For the first time, the rate of technology development has outpaced human adaptability. Things are changing so fast that leaders need to provide the means and guidance for their teams to learn and adapt faster.” He also recommended reframing the skilling conversation, sharing, “Most organizations are thinking about what skills current roles will need in the AI era. The reality is that we need to think about how the ‘future of work’ will look – how work will be organized, what roles will be required, and therefore, what skills will matter, in that order.”
The challenge goes beyond adding AI courses to existing programs. It requires cultivating adaptability itself, including teaching students how to learn continuously rather than mastering fixed bodies of knowledge. Gopikrishnan offered a metaphor that resonated with everyone: “The continuous improvement of a candle did not help in the invention of the light bulb. With the help of Gen AI, we should make more candles, not build a light bulb.”
Suvarcha Arora, VP, Chief of Staff, Strategy and Transformation at FIS, offered different advice: “Use it for personal use, don’t use it for strategy.” Her deeper message talked about using AI to enhance thinking, not replace it, thereby establishing critical boundary rules.
Strategic thinking, with its requirements for intuition, values-based judgment, and long-term vision, remains fundamentally human. AI can inform strategy, but AI cannot create it.
The most resonant takeaways from the discussion coalesced around several themes. Leaders emphasized viewing AI not as a tool to replace, but as a catalyst to reimagine work and unlock human potential. They stressed focusing on change management at the human level, with a human-first approach that leverages both technological power and human creativity. The need to stay open to and up for what is coming next, while working to augment AI skills with domain skills, emerged as a critical success factor.
The Path Forward: Five Imperatives for Leaders
Drawing from the collective wisdom of these discussions, five clear imperatives emerged for organizations navigating this transformation:
The Choices That Will Define Our Future
The irony was not lost on anyone in that room: While discussing artificial intelligence, every conversation circled back to deeply human concerns. Purpose, dignity, growth, and meaning are not technological problems, but human questions that technology forces us to confront with new urgency.
As Arushi summarized, “Today’s discussion revealed that we’re not preparing for an AI future; we’re already living in it. The organizations that thrive will be those that stop debating whether to transform, and start experimenting with how.”
The question is no longer whether or not AI will significantly transform work, as that transformation is already underway, accelerating regardless of our readiness. The question now is whether we can shape that transformation to amplify human potential or allow it to diminish what makes us human.
These sixteen leaders, representing thousands of employees across India’s most influential companies, demonstrated something valuable: The courage to admit uncertainty and the wisdom to know that navigating this transformation requires both technological sophistication and deep humanity. With the era of practical transformation underway, the window for deliberate, thoughtful transformation narrows daily. The organizations that wait for perfect clarity will find themselves overtaken by those willing to learn through action.
The process starts with a simple acknowledgment: Ours is not a technology problem, but a human problem. The organizations that understand this distinction and act on it will define the future of work.
