The return on investment (ROI) of Artificial Intelligence (AI) is increasingly becoming one of the most critical concerns for enterprises worldwide. The discussion has gained further momentum following reports that Microsoft scaled back access to certain AI coding tools due to rising operational costs, even as companies continue to invest heavily in copilots, chatbots, and generative AI integrations.
After nearly two years of aggressive experimentation, organizations are now entering a more demanding phase of the AI adoption cycle—focused on proving measurable returns. This shift is becoming evident across the consulting and enterprise technology landscape, where CFOs are increasingly reluctant to approve large-scale AI investments without clear and quantifiable business outcomes.
“We’ve reached a point where clients are no longer interested in experimentation alone. They want a proven roadmap to ROI,” said Andy Baldwin, Senior Vice President, Offerings & Growth at IBM Consulting, in an interaction with Business Today.
According to Baldwin, enterprises initially approached AI through proof-of-concept projects, investing in multiple pilots to identify high-value use cases. However, this approach is now evolving into outcome-driven deployment strategies, particularly across functions such as finance, human resources, procurement, and software development.
“We’re increasingly seeing clients say: help us reduce the cost of our finance processes or improve sales effectiveness—and we’ll pay for the outcomes delivered,” he added.
This shift represents a significant transformation for the consulting industry. Traditionally, technology consulting firms operated on input-based models where clients paid for manpower and execution hours. AI is now reshaping that structure, pushing firms toward shared accountability for productivity gains and efficiency improvements.
Baldwin noted that large enterprises are increasingly pressuring consulting partners and hyperscalers such as Microsoft and AWS to adopt contracts linked directly to business outcomes. “That is a profound shift because we’re no longer providing people; we’re providing outcomes,” he explained. “CFOs are unwilling to approve investments unless there is strong confidence in the expected ROI.”
The growing demand for AI-driven efficiency is also impacting revenue models across the IT services industry. Traditional segments like application management and BPO, once stable revenue streams, are now being delivered more efficiently through automation and AI-powered workflows. While AI transformation is creating new opportunities, legacy services are experiencing slower growth as enterprises seek to share in the productivity gains enabled by automation.
Ultimately, the AI race is no longer just about adopting cutting-edge tools—it is increasingly about proving tangible, measurable business value.
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