India Inc loves AI but isn’t ready to spend big yet

Indian companies say AI will transform the way they work but their budgets tell a very different story. Even as firms deploy more AI tools than ever, most are still spending cautiously, raising an important question: can India turn enthusiasm into real enterprise-scale adoption?

Across India Inc, everyone is talking about AI. CEOs see it as the next big leap in efficiency, teams are experimenting with tools, and generative AI has become common at workplace. But when it’s time to sign off budgets, it doesn’t always translate into action. This mismatch is shaping how India moves into the next phase of AI adoption.

A new joint survey by EY and the Confederation of Indian Industry (CII), covering over 200 organisations across more than 20 sectors, shows that nearly half of Indian firms have already deployed multiple AI use cases in production. But at the same time, more than 95% of them continue to spend less than 20% of their IT budgets on AI initiatives. Companies may be convinced of AI’s transformative power, but they are far from committing money at the scale required to unlock that potential.

AI adoption grows but budgets remain conservative

The EY–CII findings suggest that India Inc. is eager to experiment and deploy AI in day-to-day operations. Close to 76% of business leaders said generative AI would have a significant impact on their business, reflecting a strong belief in its long-term value. But only a very small share of organisations  (about 4%) allocate more than one-fifth of their IT budgets to AI.

EY leaders noted that companies are now moving beyond pilot projects and early experimentation. They explained that the real value will emerge when AI systems begin working in tandem with human employees, rather than operating as standalone tools. But to get there, organisations will need to move faster and invest far more consistently.

This need for speed is shaping business decisions. Around 91% of tech leaders surveyed said deployment speed is now the biggest factor in whether they choose to build AI systems internally or adopt third-party solutions. Companies are prioritising operational use cases such as customer service, sales, marketing, and backend optimisation — where benefits can be demonstrated quickly.

Collaboration has also become a key theme. Roughly 60% of firms are partnering with startups for co-innovation, while nearly 78% are following a hybrid approach that mixes in-house development with external expertise. This reflects a shift toward practical, results-driven adoption rather than ambitious, costly overhauls.

Yet, several challenges persist. A majority of respondents cited a shortage of skilled professionals as a barrier to innovation. As many as 59% said they struggle to find talent that can support large-scale AI initiatives. This talent gap becomes even more relevant as 64% of routine business tasks are increasingly being reshaped or automated by AI.

ROI measurement is another hurdle. Many firms are moving away from traditional cost-saving metrics and shifting toward broader indicators such as time efficiency, strategic advantage, resilience, and long-term business potential. CII noted that companies are trying to integrate AI into their core strategy, but issues such as data readiness, governance, and workforce preparedness continue to slow momentum.

Why companies hesitate to spend

If optimism is so strong, why are investment levels so modest? Part of the answer lies in readiness. A recent report by Boston Consulting Group (BCG) highlighted that while nearly 80% of Indian companies now consider AI a strategic priority which is higher than the global average. Many feel their systems, processes, or teams are not yet equipped for large-scale implementation. As a result, they prefer to invest gradually rather than commit large budgets upfront.

Macroeconomic concerns add to the caution. Businesses remain wary of global uncertainties, slower growth cycles, and tightening regulations that could affect data privacy, cybersecurity, ethical AI practices, and compliance requirements. For many companies, the safer approach is to focus on small, measurable wins before scaling up.

This gap between confidence and investment, what EY describes as a “conviction-capital gap”, may slow down the pace at which AI delivers substantial business value. If companies remain stuck in low-budget experimentation, they risk falling behind global competitors who are moving more decisively.

Yet the outlook remains optimistic. India’s corporate sector has not lost its faith in the long-term potential of AI; it is simply steering its transition carefully. The surge in pilots and early deployments shows that organisations are laying the groundwork. The next challenge will be turning that groundwork into scaled, enterprise-wide adoption.

The coming year may prove to be crucial for India’s AI development. Companies have already identified the areas where AI can make the biggest impact – customer experience, operational efficiency, marketing, risk management, and supply chain optimisation. The real test is whether they are willing to back this potential with sustained investment.

India’s AI journey is about execution: building the right talent, strengthening governance, upgrading data systems, and integrating AI into the heart of business strategy. Whether Indian enterprises can close the gap between belief and investment will determine how quickly the country moves from experimenting with AI to truly transforming the way it works.

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