This is a story of how leadership, as shown by pioneers like Shalini Kapoor, will decide the future of agentic AI. Agentic AI systems are context-aware, adaptive, and independent. They can plan, make decisions, and carry out multistep workflows with little or no supervision. They are not just tools; they act as digital coworkers and active participants in the enterprise. Unlike earlier automation systems, which focused mainly on speed, accuracy, and reducing routine errors, Agentic AI changes how work gets done.
Even with its promising capabilities, Gartner’s latest report offers a reality check: more than 40 percent of Agentic AI projects could be abandoned by 2027.
The AI Winter Within
At first glance, that number looks discouraging. On closer inspection, it shows that the real challenge is not the technology itself but how prepared organizations are to guide it. We often think of AI winters as times when funding dried up because technology failed to deliver. Gartner is pointing to a different kind of winter, one that arises from within companies themselves.
The problem is not that the models are weak. Many companies simply lack the strategy and structures needed to let agentic systems succeed. The next major hurdle in AI adoption will not be faster chips or better code; it will be leadership that is unready to manage autonomy.
The Hype–Reality Paradox
Agentic AI is often promoted as the ultimate coworker, a solution that promises lower costs, faster decisions, and greater efficiency. Many enterprises approach it expecting a quick fix.
Yet autonomy is not about replacing work. It is about rethinking how work is designed. Agentic AI encourages organizations to reconsider how teams operate, how decisions are made, and how responsibilities are shared.
Without that shift, projects risk failure. Gartner’s “40 percent” is not a verdict on AI’s capability; it is a warning that companies chasing hype without real transformation will fall behind.
The Trust Gap as the Next Productivity Gap
In the 1990s, the digital divide shaped which companies and countries gained the most from the internet. Today, the same dividing line is trust. Enterprises that treat governance, transparency, and accountability as optional will find it hard to scale agentic systems. By contrast, those that embed trust into their foundations, through practices such as auditable decision-making, explainable AI, and strong safeguards, will secure a lasting advantage. Trust is no longer optional; it has become the new productivity infrastructure. Without it, agentic AI will remain a prototype in the lab rather than a partner in the enterprise.
Inclusive Leadership Beyond Algorithms
The most important takeaway from Gartner’s analysis is that the future of agentic AI will be shaped less by algorithms and more by leadership.
Models will keep advancing and tools will continue to improve. What will separate the 40 percent of projects that fail from those that succeed is leadership that strikes the right balance: ambition with accountability, autonomy with oversight, and enthusiasm with real human value.
Agentic AI calls for leaders who can deal with complexity, avoid chasing short-term trends, and keep adoption grounded in long-term enterprise needs.
Case Study: Leadership in Agentic AI – Shalini Kapoor
One leader who brings these principles to life is Shalini Kapoor, India’s first woman IBM Fellow and CTO for AI Applications. Her career reflects the qualities Gartner’s report highlights as essential for the future of agentic AI.
Organizational Readiness — “The AI Winter Within”
Kapoor has led AI infusion and skills transformation across IBM’s AI Applications unit, helping enterprises build the culture and expertise needed for sustainable adoption.
From Buzz to Business Value — The Hype–Reality Paradox
She launched IBM’s Watson IoT and AI Lab, focusing on client-driven solutions and workflow redesign rather than hype.
Trust as Infrastructure — The Trust Gap
Kapoor supports IBM’s “Good Tech” initiatives and advocates diversity and inclusion, making trust and ethics central to innovation.
Leadership Beyond Algorithms
As CTO, she shapes IBM’s AI strategy and translates technical depth into organizational outcomes.
Inclusive Leadership
She founded the Equal Council at IBM India and the Ankurit Foundation, promoting STEM education and ensuring diverse voices play a role in shaping technology’s future.
Her career is a case study in how agentic AI succeeds when guided by leadership that is responsible, practical, and inclusive.
Agentic AI marks a major change in the enterprise, moving from automation to collaboration and from tools to colleagues. But as Gartner warns, not every project will succeed.
The lesson here is not despair but clarity. Agentic AI will not fail because the technology is weak. It will fail when leadership does not evolve. The 40 percent that fall short will do so because of hype without strategy, autonomy without governance, and ambition without accountability.
The projects that endure will be guided by leaders who understand that AI is not here to replace us but to work alongside us. Leaders such as Shalini Kapoor show that autonomy and accountability can grow together.
The future of AI will not be defined by algorithms. It will be defined by who leads them, who shapes them, and whose values they represent.
What do you think?
Will leadership truly decide the success of agentic AI, or will technology itself play a bigger role?
Share your thoughts in the comments. I’d love to hear your perspective.