Adobe, the global technology leader that unleashes creativity, productivity and customer experiences through innovative tools and platforms, today released the India findings from the Adobe 2026 State of AI Readiness Report. The study of 475 senior executives across India examines what separates organizations that scale AI from those that stall.
According to the findings, approximately 59% of organizations in the region are stuck in the “Frozen Middle”, piloting or deploying AI without the coordination needed to scale it. For agentic AI specifically, the figure is 40%. Only 6.7% of companies, or 30 organizations in the dataset, have scaled AI across multiple workflows and built the operating model to sustain it. These Leaders convert pilots to production at nearly four times the rate of other companies.
Investment is not the constraint. While 77% of companies are lifting AI investment year-on-year, almost two in three believe they are still underinvesting.
Jeremy Willmott, Senior Director, Digital Strategy Group Asia Pacific, Adobe said, “As AI investment grows, the gap between experimentation and enterprise-wide value is becoming harder to ignore. Organizations that establish clear ownership, shared measures of success and stronger collaboration between business and IT will be best placed to move beyond isolated pilots and achieve sustainable impact.”
Why AI stalls between pilot and production
- Approval bottlenecks: Approximately 35 % of AI proposals do not make it past IT evaluation, and a further 17% are rejected at security review, a rate that nearly doubles in highly regulated industries.
- Ownership vacuum: Only 18% companies have an AI owner with budget authority, compared with 93% of Leaders.
- Measurement gap: Only 10% measure AI return on investment comprehensively, with most focusing on usage rather than measures such as quality, rework or the cost of reviewing AI-generated output.
- Persistent skills shortage: 82% of businesses say their AI skills shortfall stayed the same or worsened over the past year.
- Long deployment timelines: Moving from experimentation to initial deployment takes at least six months for around two-thirds of organisations. For almost one in four, that time horizon is 12 months or more.
- Low conversion to production: Of every 100 AI ideas proposed by Indian organisations, only around about 15% make it to production.
What India’s AI Leaders do differently
- Structure and workflows first: Maturity in structure and workflows is 61% and 48% higher than the regional average among Leaders, respectively, highlighting the importance of dedicated ownership, accountability and deeper integration of AI into business processes.
- Failure treated as learning: Leaders maintain their destructive-failure rates below 1%; while over a third of companies repeat the same AI mistakes as patterns are not identified and flagged.
- Champions with real backing: Among Leaders, 53% consider identifying and empowering their champions as single most effective and the least expensive move.