According to the India insights of Deloitte’s State of AI in the enterprise report for 2026, Indian enterprises are moving beyond experimentation and are leading global peers in at-scale AI adoption across most functions. The report finds at-scale deployment is strongest in Product development (62 percent), Strategy and Operations (56 percent), Marketing and Sales (55 percent) and Supply Chain (48 percent), signaling that AI is increasingly embedded into functions that drive growth, efficiency, and competitive advantage.
This operating momentum is also reflected in the extent of AI usage in the enterprise. Forty percent of Indian respondents report significant or full usage, compared with a global average of approximately 28 percent, indicating that Indian organisations are not only piloting AI, but are increasingly operationalising it to unlock near-term productivity and business outcomes.
“Indian enterprises are entering a defining phase in their AI journey, where ambition is translating into enterprise-wide execution. The momentum we are seeing reflects a strategic shift from experimentation to embedding AI into the fabric of how organisations create value and compete. The next chapter will be shaped less by access to technology and more by the ability to build institutional capability, strengthen governance, and align people with new ways of working. Organisations that invest in trust and skills today will be better positioned to convert early gains into sustained advantage,” said S Anjani Kumar, Partner, Deloitte India.
However, the pace of adoption is running ahead of depth in capability building. When it comes to high level of AI expertise, Indian organisations ranked lower than their global counterparts, with Indian companies at 0 to 4 percent compared to a global average of 2 to 8 percent, demonstrating a near-term imperative to strengthen specialist AI expertise skills as adoption scales.
Even as expertise catches up, investment intent remains strong. The report shows 94 percent of Indian organisations expect AI spend to increase over the next year, reflecting sustained commitment to scaling AI initiatives and expanding deployment across the enterprise.
As organisations push toward enterprise-grade deployments, concerns around data security, privacy, and regulatory compliance are shaping where investments are being directed. Leading investment priorities for enabling AI scale include security and compliance controls (68 percent), data storage and management (61 percent), and scalable infrastructure and compute capacity (54 percent).
In parallel, many organisations prefer renting AI infrastructure and application services to capture near-term value. Respondents indicate a preference for off-the-shelf tools (31 percent) and blended buy-build strategies (49 percent) compared to custom, in-house solutions (19 percent), suggesting that speed to market and faster time to implementation are guiding factors as complexity and cost considerations remain material.
As adoption expands, execution frictions remain real, especially where regulated environments and organisational change intersect. The report finds that regulatory and compliance requirements are the top AI integration challenge (39 percent), followed by resistance to change (34 percent). At the same time, organisations report relatively lower pressure from cost (12 percent) and infrastructure (5 percent) constraints, indicating that governance readiness and operating-model change are the more immediate limiting factors for scale.
To address these constraints and support broader adoption, organisations are leaning on workforce measures that build AI fluency and encourage usage in day-to-day work. The most common responses include upskilling and reskilling programs (61 percent), incentives to drive AI adoption (59 percent), and broader workforce education (53 percent). These measures signal a shift from isolated AI projects toward organisation-wide capability building, despite specialist expertise being uneven.
Despite these frictions, Indian organisations expect tangible near-term value from AI. Nearly all respondents anticipate productivity improvements, with 97 percent expecting productivity to increase. Most organisations are pursuing pragmatic transformation paths, with 44 percent redesigning select processes while keeping the business model intact, compared with 17 percent pursuing fundamental reinvention of core processes and business models. This indicates that the dominant playbook is incremental change targeted at measurable operational gains, rather than structural reinvention.
