Indian Enterprises See AI Investment Returns But Readiness to Manage Risks Plummets by 8%

Indian Enterprises Report Growing AI Investment Returns Amid Declining Risk Preparedness

Indian organisations are beginning to extract tangible value from their artificial intelligence investments, but their ability to manage the accompanying risks is deteriorating rapidly, according to Kyndryl's 2026 Readiness Report1

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. The findings expose a widening gap between AI adoption momentum and enterprise readiness to navigate the complexities that come with it. About 60% of Indian business leaders reported positive AI investment returns, marking a three percentage point increase from 57% in 20252

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. Yet average readiness to manage external risks fell eight percentage points from 35% to 27% over the same period1

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. The Kyndryl report, based on a survey of 3,700 senior business leaders across 21 countries including 200 respondents from India, highlights mounting challenges around cybersecurity, infrastructure limitations for AI, and organizational misalignment as companies attempt to scale their AI initiatives2

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AI Cyberattack Preparedness Drops to 35% as Security Concerns Intensify

For the third consecutive year, cybersecurity concerns topped the list of external risks and contributed most significantly to the overall decline in enterprise readiness3

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. Only 35% of Indian organisations said they were completely prepared to manage cyberattacks, representing a 10 percentage point decline from 20251

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. Globally, AI cyberattack preparedness stood at just 26%, marking an 11 percentage point drop2

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. The data reveals a troubling disconnect: while three in four leaders acknowledge that AI helps their organisations identify threats faster, confidence in their ability to respond to cyberattacks has weakened considerably1

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. This paradox suggests that while AI enhances threat detection capabilities, the velocity and sophistication of AI-powered attacks are outpacing defensive measures. The findings point to an urgent need for enterprises to strengthen their cybersecurity frameworks and risk management protocols as AI adoption accelerates.

Scaling AI Pilots Remains Critical Challenge Despite 85% Deployment Rate

Indian organisations are making measurable progress in moving AI adoption beyond experimentation, with 85% deploying AI in workflows beyond pilot projects1

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. The share of organisations still in the experimentation stage has declined 15 percentage points to 56%3

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. However, scaling AI pilots presents a significant bottleneck. Around 70% of leaders reported their organisations have more AI pilots than they can realistically scale, while 58% said innovation often stalls after the proof-of-concept stage1

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. The struggle to scale reflects deeper systemic issues. Half of the surveyed Indian organisations have significantly changed their AI strategy over the past year, while 31% have experienced an AI investment failure2

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. Martin Schroeter, Chairman and CEO of Kyndryl, noted that "AI ambitions are moving faster than the systems needed to support them, and the bar for readiness keeps moving as AI becomes more integrated in enterprises"1

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Organizational Misalignment Between CHROs and CTOs Hinders AI Strategy Execution

A striking 37% of Indian organisations experience disagreements between their CHROs and CTOs or CIOs over AI strategy, pointing to organizational misalignment as another critical challenge to scaling AI1

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. This disconnect between human resources and technology leadership suggests fundamental gaps in how organisations approach AI transformation. The tension likely stems from differing priorities: while CTOs focus on technical implementation and infrastructure, CHROs grapple with workforce implications, skill development, and cultural change. Without alignment between these critical functions, even well-funded AI initiatives risk stalling. The data suggests that successful AI adoption requires more than technological capability—it demands coordinated organizational transformation that addresses both technical and human dimensions simultaneously.

Infrastructure Limitations for AI Persist Despite 71% Modernization Rate

For the third consecutive year, upgrading IT infrastructure remained the top action Indian organisations are taking to mitigate external risks3

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. While 71% of Indian leaders consider their IT infrastructure mostly or fully modernized, 59% acknowledged that significant re-architecture is required to support AI at scale1

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. This gap reveals that modernized infrastructure doesn't automatically translate to AI-ready infrastructure. Leaders are making a clear distinction between having a modern IT estate and possessing one capable of supporting artificial intelligence at enterprise scale3

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. The findings suggest that infrastructure upgrades alone may not be sufficient—companies also need to address governance, cybersecurity, and organizational capabilities2

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AI Agents and Workflow Automation Challenge Established Business Models

The second-largest drop in enterprise readiness came from concerns about competitive disruptions outside traditional industry boundaries, falling 10 points to 23% globally3

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. This decline coincides with widespread deployment of AI agents, with 80% of Indian organisations using them to automate workflows that previously required coordination across multiple teams or systems2

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. The shift is forcing organisations to question established business models across sectors. Retailers are weighing how to benefit from AI shopping assistants without sacrificing direct customer relationships. Software companies face uncertainty about SaaS models as AI rebalances the build-versus-buy equation. Financial institutions confront emerging lending models powered by AI3

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. These developments suggest that AI adoption isn't merely about operational efficiency—it's fundamentally reshaping competitive dynamics and industry boundaries. Organisations must prepare not just for technological change but for business model disruption that could redefine their markets. Watch for continued volatility as AI agents become more sophisticated and autonomous, potentially accelerating the erosion of traditional industry structures.