Infosys Research: The AI ROI Gap: Turning Bold AI Investments into Measurable Enterprise Value

The race to invest in AI is accelerating, but companies are facing difficulties with proving its immediate value. Infosys released its new report, The AI ROI Gap: Turning Ambition Into Enterprise Value, revealing the growing disconnect between executive expectations for AI and the return on investment organizations are realizing today.

While enterprise leaders continue to increase AI investments and overwhelmingly view the technology as critical to future growth, many are struggling to demonstrate returns. The research found that while 80 percent of executives believe AI is a critical driver of new revenue opportunities, one in four say the ROI from AI investments has fallen below expectations.

Infosys surveyed more than 1,000 U.S. senior executives at large companies to better understand how organizations are evaluating, scaling and governing AI initiatives. The findings suggest that the challenge is not a lack of value creation. Rather, many organizations may be looking for value in the wrong places. While leaders often evaluate AI through a revenue lens, the technology's greatest impact today is in accelerating speed to market, improving operational efficiency and reducing costs.

The report identified several key findings:

• AI is generating value, but primarily through operational performance. Three-quarters of respondents say AI's overall value to their organization has been net positive. However, the strongest measurable gains are appearing in speed to market and cost savings rather than revenue growth, suggesting AI is currently acting more as an accelerator of internal performance than a direct engine of top-line growth.
• Organizations struggle to measure AI success effectively. Two-thirds of executives say their organizations have difficulty measuring AI ROI. Nearly half lack a centralized KPI framework, and only a quarter formally track speed to market, despite it being one of AI's strongest areas of impact. This suggests many companies may be undercounting the value AI is already creating.
• Scaling remains one of the biggest barriers to realizing returns. Nearly three-quarters of respondents say fewer than 25 percent of AI pilots have successfully scaled to enterprise-wide deployment while delivering their intended ROI. Executives most often cite unclear business cases and poorly defined ROI targets as the primary reasons AI initiatives fail to progress beyond experimentation.
• Workforce behavior and governance are emerging as critical ROI factors. As AI adoption expands, organizations are increasingly concerned about employee overreliance on AI tools, unapproved AI usage and security risks. The findings suggest that governance, training and human oversight are becoming as important to AI success as the technology itself.

To close the AI ROI gap, organizations should focus on defining business outcomes before implementing technology, expand measurement frameworks beyond revenue-based metrics, and strengthen governance practices that align leadership, workforce behavior and AI adoption. As AI moves from experimentation to enterprise-scale deployment, the organizations most likely to realize lasting value will be those that pair ambitious investments with disciplined execution.

For more information about the Infosys report The AI ROI Gap: Turning Ambition Into Enterprise Value, visit here.