Only 6.7% of Indian Firms Successfully Scale AI Across Workflows
A new Adobe report reveals only 6.7% of Indian firms have scaled AI across workflows, while 59% struggle to move past pilot projects.
Despite a massive surge in interest and funding, the transition from experimenting with Artificial Intelligence to implementing it across entire business operations remains a significant challenge for Indian enterprises. A recent report by Adobe has revealed a stark reality: while investment is climbing, widespread adoption is lagging far behind.
The Great AI Gap: Investment vs. Implementation
According to a survey of 475 senior executives in India, there is a massive disconnect between how much money companies are pouring into AI and how much they are actually using. While 77 per cent of companies are increasing their AI investments year-on-year, only a tiny fraction—just 6.7 per cent—have successfully scaled the technology across multiple business workflows.
This gap is further highlighted by the fact that 59 per cent of surveyed organizations are struggling to move beyond simple pilot projects. Instead of seeing large-scale transformations, many businesses are stuck in a cycle of testing without ever reaching full production.
Why AI Ideas Fail to Reach Production
The report paints a challenging picture for innovation within Indian corporations. Out of every 100 AI ideas proposed by organizations, only about 15 reach the production stage. The journey from a concept to a functional tool is fraught with technical and administrative roadblocks:
- IT Evaluations: Approximately 35 per cent of AI proposals fail to pass internal IT assessments.
- Security Hurdles: Another 17 per cent of ideas are rejected during security reviews. This rejection rate is nearly double in highly regulated industries.
- The Pilot Trap: About 44 per cent of companies are either still working on their very first AI use case or have abandoned their efforts after an unsuccessful attempt.
Major Obstacles: Accountability and Skills
Beyond technical failures, the report identifies structural and human resource issues as primary reasons for the stagnation in AI deployment.
Lack of Leadership and Ownership
One of the most surprising findings is the lack of dedicated leadership. Only 18 per cent of companies have an AI leader who possesses actual budget authority. This stands in sharp contrast to the "AI leaders"—the companies that are actually succeeding—where 93 per cent have such leadership in place. Without clear ownership and budget control, AI initiatives often lack the momentum needed to move from the lab to the boardroom.
The Widening Skills Gap
The talent war is also intensifying. A staggering 82 per cent of businesses reported that their AI skills gap has either stayed the same or worsened over the last year. This shortage of expertise makes it difficult for companies to manage complex deployments or optimize existing tools.
Difficulty in Measuring ROI
Even when AI is deployed, many companies struggle to understand if it is actually working. Only 10 per cent of organizations measure the returns on their AI investment comprehensively. Instead of looking at high-level metrics like output quality, the cost of reviewing AI content, or the reduction in rework, most firms focus solely on how much the tool is being used.
The Path to Success
The report suggests that the companies finding success are not necessarily those with the most money, but those with the best integration. Successful firms tend to have clearer responsibilities and better-integrated workflows. In fact, their organizational maturity and workflow integration were 61 per cent and 48 per cent higher, respectively, than the regional average.
"As AI investment grows, the gap between experimentation and enterprise-wide value is becoming harder to ignore," noted Jeremy Willmott, Senior Director, Digital Strategy Group Asia Pacific at Adobe. He emphasized that success requires stronger collaboration between business and technology teams, along with shared measures of success to move beyond isolated pilot projects.