Key Takeaways
- 47% of Indian enterprises have multiple AI use cases in production.
- Over 95% of firms allocate less than 20% of IT budget to AI.
- 76% of leaders believe in AI’s impact, but only 4% commit significant funds.
Nearly half of Indian enterprises are now running multiple artificial intelligence (AI) applications in live production environments. However, a significant funding gap persists, with over 95% of organizations spending less than 20% of their IT budgets on AI initiatives, according to a joint survey by EY and the Confederation of Indian Industry (CII).
Belief vs Budget Reality
The survey of 200 organizations across more than 20 sectors revealed a stark contrast between corporate conviction and actual capital commitment. While 76% of business leaders expressed strong confidence in generative AI’s potential business impact, only about 4% have allocated more than 20% of their overall IT budget for AI and machine learning investments.
This belief-funding imbalance is becoming a critical factor determining how quickly companies can achieve measurable returns from their AI deployments, the report noted.
Production Deployment Gains Momentum
Despite conservative budgeting, implementation momentum is accelerating. The data shows 47% of Indian enterprises now have multiple generative AI use cases operating in production, while 23% remain in the pilot testing phase.
“Corporate India has moved beyond experimentation. Nearly half the enterprises already have multiple use cases in production,” said Mahesh Makhija, Partner and Technology Consulting Leader at EY India. “For enterprises, the focus must now move from building pilots to designing processes where humans and AI agents collaborate seamlessly.”
Deployment Speed Drives Strategy
Implementation velocity has emerged as the dominant factor shaping AI strategy, with 91% of business leaders identifying rapid deployment as the primary influence on their “buy versus build” decisions.
Over the next year, organizations plan to concentrate GenAI investments in three key areas: operations (63%), customer service (54%), and marketing (33%).
Collaborative Execution Models Dominate
The execution approach is increasingly partnership-driven, with nearly 60% of organizations co-innovating with startups and 78% adopting hybrid models that blend in-house development with external collaborations.
Workforce Transformation and Talent Gaps
AI’s impact on workplaces is already evident, with 64% of enterprises reporting selective transformation in standardized tasks. However, 59% highlighted a persistent shortage of skilled AI talent, even as mid-office and innovation-focused roles expand rapidly.
Evolving ROI Measurement
Companies are refining their assessment frameworks, moving beyond traditional cost reduction and productivity metrics. They’re adopting a five-dimensional ROI model that evaluates time savings, efficiency gains, business growth, strategic differentiation, and organizational resilience.
“While challenges around data readiness, governance and measurement persist, India’s AI journey is moving from pilots to performance,” said Chandrajit Banerjee, director general of CII.
