TCS CEO: 95% of AI Pilots Fail; 5 Principles to Unlock GenAI Value

TCS CEO K Krithivasan highlights a critical gap, noting that 95% of enterprise AI pilots fail to deliver measurable value despite GenAI's transformative potential. He argues that realizing AI's value requires new frameworks for human-machine collaboration in organizational decision-making. Krithivasan outlines five core principles for success: building trust gradually, ensuring visibility, fostering open-mindedness, evolving decision hierarchies, and changing workflows. The future lies in "Intelligent Choice Architectures" where humans and AI systems work together to present better, data-backed choices.

Key Points: TCS CEO on GenAI Shift: 5 Principles for Success

  • 95% of enterprise AI pilots fail
  • Need human-AI collaboration in decision-making
  • Trust must be built gradually over time
  • Visibility and open-mindedness are key
  • Decision hierarchies and workflows must evolve
3 min read

Rise of GenAI represents a fundamental shift, says TCS CEO; highlights 5 core principles

TCS CEO K Krithivasan reveals 95% of enterprise AI pilots fail. Discover the 5 core principles to bridge the gap between AI promise and performance.

"We are witnessing the advent of a new form of organisational intelligence, where combinations of humans and machines shape how choices are developed, presented and discussed. - K Krithivasan, TCS CEO"

New Delhi, January 20

As generative artificial intelligence reshapes how organisations think and act, a stark gap has emerged between promise and performance.

The rise of GenAI represents a fundamental shift. It transforms how enterprises think, make decisions and act. Citing a study by MIT, K Krithivasan, CEO & Managing Director, Tata Consultancy Services, said in an article on the World Economic Forum (WEF) website that despite the enormous potential, research shows that 95% of enterprise AI pilots have failed to deliver measurable value.

To move beyond the promise of AI and turn potential into performance, leaders must rethink not only what decisions are made, but how decision-making itself is designed, and how humans and AI can collaborate most effectively.

For success to be achieved and AI's potential to be realised, new frameworks are required. Leaders must establish structures that enable continuous, informed dialogue with AI, while keeping humans in the loop, he said.

"As we look ahead to 2026, a clearer picture of AI's impact is emerging. We are witnessing the advent of a new form of organisational intelligence, where combinations of humans and machines shape how choices are developed, presented and discussed," the article read.

He said that to unlock AI's true value, businesses need to collaborate across ecosystems, apply deep domain insights, ensure rigorous governance and scale responsibly through co-innovation models. AI should improve organisational decision-making by presenting better choices backed by data.

The CEO & MD highlighted five core principles to build this new foundation.

"Trust must be built over time." He said that to manage risk and improve trust, implementation must be a gradual process. Stakeholders need to feel growing confidence in how decision environments are framed, not just in the correctness of decisions.

"Taking an iterative process that allows for incremental learning can help colleagues understand how to operate within new architectures successfully," he added.

"Visibility is key." Organisations must track how high-stakes decisions are made and take a holistic view of their business and the wider landscape. Intelligent Choice Architectures are dependent on accurate data and will fail - or even model the wrong choices - without it.

"Open-mindedness is essential." Intelligent Choice Architectures don't flatter intuition; in fact, they often challenge it. Organisations must build a culture where people are comfortable about getting things wrong in front of others. In the shifts to harnessing these systems, this is part of the journey to success.

"Decision-making hierarchies must evolve." To unlock true value from AI agents, decision-making-related barriers need to be removed. If only credentialled experts of legacy hierarchies can make decisions, Intelligent Choice Architecture insights may be dismissed, regardless of their quality.

"Workflows must change." If cultural shifts can be achieved, new workflows must also be developed to support them. Processes must be more flexible to allow better options presented by Intelligent Choice Architectures to be implemented. This is not a question of AI literacy, but of building internal systems that make these human-machine-cooperation-derived insights visible, understandable, and actionable.

- ANI

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Reader Comments

R
Rohit P
"Workflows must change" - This is the biggest challenge for Indian IT and services companies. We have decades-old processes. Integrating AI isn't just a tech upgrade; it requires a complete mindset shift. Hope our leaders are listening! 🤔
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Arjun K
The emphasis on human-AI collaboration is key. In a country with our demographic dividend, AI should augment our workforce, not replace it. Building that "organisational intelligence" he mentions could be India's big advantage if we get the skilling right.
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Sarah B
While the principles are sound, I find the article a bit abstract. As someone working in a mid-sized firm, the practical steps are missing. How do we start this "iterative process" with limited budgets? More concrete examples from the Indian context would help.
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Karthik V
Absolutely agree on the governance point. With AI regulation still evolving globally, Indian companies must be proactive. We can't afford another "move fast and break things" phase. Responsible scaling is the need of the hour. 👍
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Nikhil C
The point about decision-making hierarchies is so true! In so many Indian offices, only the senior-most person's intuition is valued. If AI challenges that, will it be accepted? We need a culture where data-driven suggestions from a junior engineer + AI are heard.

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