The AI Return-on-Investment Debate - A Reality Check

The tech industry has been rocked by reports of feeble ROI from the stratospheric investments by companies in artificial intelligence.

Per an IBM Business Value report , “The AI ROI Rest” Enterprises are no longer reporting stratospheric ROI from generative AI pilots; as pilots scale, those returns have fallen back to earth. Projects that once boasted spectacular short-term gains have settled into a more pedestrian 7% ROI—notably shy of the approximately 10% cost of capital that serves as a typical capex hurdle rate.

High Performers in AI

Nevertheless, there are a handful of organizations that stand out for their ability to extract value from AI investments. A McKinsey survey, “The state of AI in 2025” find that there are high performers which stand out most by  their level of ambition. According to

Tara Balakrishnan, associate partner, “their AI agendas go beyond driving incremental efficiency gains: High performers are setting out to fundamentally reimagine their businesses. This level of ambition becomes a key differentiator and catalyst for change in the organization. When leaders articulate a transformative vision for AI, we see that it galvanizes the organization in terms of alignment, investment, and overall energy. As a result, leading organizations are not just seeing improved automation results; they are redesigning workflows and customer experiences to capture new forms of value.”

Redirecting Investments Towards Core

The IBV report finds that organizations also are redirecting their AI investments toward core functions, which now command 64% of AI budgets compared to 36% for non-core activities . This reallocation suggests a growing sophistication: a recognition that AI delivers its most compelling value when applied to central business operations rather than peripheral processes.

AI automation is capturing a significant share of digital budgets relative to everything else: more than half of respondents now allocate between 21% and 50% (an average of 36%) of their digital initiative budgets to AI. This equates to about US$700 million for a company with US$13 billion in revenue. This was found in a Deloitte’s 2025 tech value survey of nearly 550 leaders across five industries draws on four years of research, leveraging longitudinal data, cluster analysis, and predictive modeling to reveal distinct patterns in technology spending and value realization.

Working at the core is much more complicated than grabbing low-hanging fruit around the periphery, which may help explain why the pivot to core functions is concurrent with a decrease in ROI. Long term, the core should deliver far more scale and sustainable returns, but it requires more coordination to get moving. Across organizations, experience has brought wisdom. Only 6% now pursue AI in an ad hoc fashion, down from 19% a year earlier.

Scattered Pilots Fritter Resources

This shift toward investing in core functions reflects a broader trend toward strategic implementation across horizontal functions, industry vertical workflows, products and services, and even business models. Companies have begun to recognize that scattered pilots, while sometimes instructive, cannot deliver the systematic benefits that come from coordinated, enterprise-wide approaches and trusted data.

However, a recent MIT study found that only 5% of gen AI pilots deliver sustained value at scale. This gap suggests that organizations may be overestimating success and should shift from pilots to learning-capable systems—AI systems and tools that learn from interactions and context, continuously improving over time—integrated into core workflows, with ROI tied to measurable impact.

The Innovation Impact

Organizations seeing the greatest impact from AI often aim to achieve more than cost reductions from these technologies. While most respondents report that efficiency gains are an objective of their organizations’ AI use, high performers are more likely than others are to say their organizations have also set growth and/or innovation as an objective of their AI efforts.

True Value From Blended Metrics

The ROI from AI debate often overlooks the fact that different lenses are used to measure value from AI, which creates the confusion.  While CFOs, CIOs, and CTOs prioritize divergent metrics like ROI, EBITDA, or KPIs, fragmenting organizational impact. Analysis reveals four leadership archetypes: Strategists (31-40% enterprise value attribution), Tech Builders (74% tech ROI but low enterprise ROI realization), Digital Mavens (93% tech ROI yet weak EBITDA), and Profitability Masters (61-70% enterprise ROI with balanced KPIs/EBITDA).

Predictive insights show leaders’ functional roles shape value outcomes—CSOs drive KPI, ROI, CTOs enhance technical ROI, and CFOs boost EBITDA. True value emerges when organizations align these lenses through a shared scorecard, blending metrics and incentivizing leadership via compensation tied to holistic performance, transforming fragmented gains into exponential impact.