Infosys has released new research, “The AI ROI Gap: Turning Ambition Into Enterprise Value,” revealing a disconnect between executive AI expectations and realized returns. While 80% of executives see AI as critical for growth, one in four report lower-than-expected ROI. The study found that AI’s strongest impact is in accelerating speed to market, improving operational efficiency, and reducing costs, rather than direct revenue growth. Challenges include scaling pilots and measuring success effectively.
Infosys Research: AI ROI Gap and Value Creation
Infosys has published a new research report titled “The AI ROI Gap: Turning Ambition Into Enterprise Value.” The report highlights that while companies are accelerating their investments in Artificial Intelligence (AI), many are struggling to demonstrate its immediate value. A significant disconnect exists between executive expectations for AI and the actual returns organizations are currently realizing.
Key Findings on AI Investment and Returns
The research indicates that although enterprise leaders are increasing AI investments and view the technology as critical for future growth, a substantial portion are finding it difficult to demonstrate returns. Specifically, 80 percent of executives believe AI is a crucial driver for new revenue opportunities. However, one in four executives reported that the ROI from their AI investments has fallen below expectations.
Infosys surveyed over 1,000 U.S. senior executives from large companies to understand their approaches to evaluating, scaling, and governing AI initiatives. The findings suggest that the core challenge is not a lack of value creation, but rather that organizations might be focusing on the wrong areas for value realization. While many evaluate AI through a revenue lens, the technology’s most significant impact today is in accelerating speed to market, enhancing operational efficiency, and reducing costs.
Reported Key Findings
- AI is Generating Value Primarily Through Operational Performance: Three-quarters of respondents stated that AI’s overall value to their organization has been net positive. The most significant measurable gains are observed in speed to market and cost savings, positioning AI as an accelerator of internal performance rather than a direct driver of top-line revenue growth.
- Struggles in Measuring AI Success: Two-thirds of executives find it difficult to measure AI ROI effectively. Nearly half lack a centralized Key Performance Indicator (KPI) framework, and only a quarter formally track speed to market, a key area of AI impact. This suggests potential undercounting of the value AI is already delivering.
- Scaling Remains a Major Barrier: Nearly three-quarters of respondents reported that fewer than 25 percent of AI pilots have successfully scaled to enterprise-wide deployment while delivering their intended ROI. Unclear business cases and poorly defined ROI targets are frequently cited as reasons for AI initiatives failing to progress beyond the experimental stage.
- Workforce Behavior and Governance as Critical Factors: As AI adoption grows, concerns about employee overreliance on AI tools, unapproved AI usage, and security risks are increasing. Governance, training, and human oversight are emerging as crucial elements for AI success, as important as the technology itself.
Recommendations for Closing the AI ROI Gap
To effectively close the AI ROI gap, organizations are advised to focus on defining clear business outcomes before implementing AI technology. Expanding measurement frameworks beyond solely revenue-based metrics and strengthening governance practices that align leadership, workforce behavior, and AI adoption are also critical. As AI transitions from experimentation to enterprise-scale deployment, organizations that pair ambitious investments with disciplined execution are most likely to achieve lasting value.
For more comprehensive details, the full report “The AI ROI Gap: Turning Ambition Into Enterprise Value” is available on the company’s website.
Source: BSE
