Forrester flags AI execution gap: only 10–15% AI pilots scale in Indian IT services
A Forrester report has raised questions about how successfully AI pilots are turning into production deployments within Indian IT services. The study suggests that while AI experimentation is widespread, only a small share of pilots mature into scaled, long-term solutions—pushing firms and enterprise buyers to focus more on governance, measurable outcomes and integration readiness.
What the report says
Research firm Forrester has pointed to a major execution gap in AI adoption by Indian IT services, arguing that the industry’s AI narrative often looks stronger than results on the ground. According to the report, only about 10–15% of AI pilots ultimately scale into sustained, production-grade deployments.
The finding suggests a familiar pattern: companies run multiple proofs-of-concept, but struggle with the harder stage—integrating AI into real workflows, ensuring data quality, maintaining model performance over time and aligning business ownership. For customers, this gap matters because it affects ROI timelines and raises the risk of vendor overpromises.
Why pilots fail to scale
Scaling AI typically breaks down on operational issues rather than ideas: fragmented data systems, limited change management, unclear accountability and weak governance. Many pilots show impressive demo results, but face friction once they must comply with security, auditability and reliability expectations in live environments.
The report also feeds into a broader shift in enterprise tech: buyers are increasingly demanding measurable outcomes, tighter controls and transparency around AI systems—especially when AI is used in customer-facing workflows or sensitive decision-making.
What enterprise leaders may do next
- Cut the number of pilots and fund fewer projects with clear business ownership and success metrics.
- Strengthen model governance: monitoring, explainability, audit logs and risk review before launch.
- Prioritise integration work (data pipelines and process redesign) over “quick demo” deployments.
- Negotiate outcome-linked contracts with vendors instead of paying mainly for experimentation.
For Indian IT services firms, the message is blunt: AI credibility will depend less on the volume of pilots and more on the ability to industrialise AI—at scale, with reliability and repeatable delivery in client environments.