As enterprises double down on agentic AI, success will depend not on isolated experimentation, but on a deliberate, long-term playbook
Indian enterprises are accelerating their efforts to experiment with and deploy AI at scale. Over the past few years, organizations across sectors have launched a wave of initiatives to stay ahead of the curve. But as enterprises move from experimentation to operationalization, the real challenges are beginning to emerge: stretched infrastructure, performance bottlenecks, unclear ROI, and growing resistance from both customers and employees.
According to Gartner, by the end of 2025, at least 50% of generative AI projects were abandoned after the proof-of-concept stage, undermined by poor data quality, weak risk controls, escalating costs, and an inability to demonstrate tangible business value.
This marks a critical inflection point. As enterprises double down on agentic AI, success will depend not on isolated experimentation, but on a deliberate, long-term strategy. That means investing in robust data and storage foundations, enabling enterprise-wide change management, and embedding strong guardrails around safety, privacy, accountability, and fairness. Equally important is the ability to define and rigorously measure clear business outcomes.
As Ninad Raje observed at the CIO Playbook Conference: “If you have a Ferrari but are driving it on Mumbai’s pothole-ridden roads, it won’t work—it will crack open.” The analogy captures a broader truth: AI failures are rarely caused by the models themselves. More often, they stem from weaknesses in data, infrastructure, and organizational readiness.
Notably, startups and digital-native companies appear to be navigating this transition more effectively by leveraging cloud-native architectures, agile operating models, and a sharper focus on measurable outcomes from the outset.
In this edition, we bring you highlights from the CIO Playbook Conference, where some of the country’s leading CIOs shared candid perspectives on what it truly takes to move AI from promise to performance—and to deliver sustained business impact. I look forward to hearing your views on what it will take for enterprises to deploy AI successfully at scale.
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