Companies Struggle to Measure AI's Return on Investment as Spending Cuts Begin
Business leaders at New York Tech Week are grappling with measuring AI's return on investment as companies begin cutting back on spending amid what IBM's Gary Cohn called "massive over-investment" industry-wide. The challenge stems partly from the difficulty of quantifying AI's value in software engineering workflows, where most corporate AI costs are concentrated. Resolving measurement issues could determine which AI applications succeed commercially and how much companies ultimately invest in the technology.
Companies are reassessing their artificial intelligence spending as executives struggle to demonstrate tangible returns on investment to their boards. IBM Vice Chairman Gary Cohn stated that while the world will need AI, current ROI has "not been nearly as high as people might think," though some startup leaders attribute spending cuts to measurement difficulties rather than lack of utility. The software engineering market for AI coding capabilities surged sevenfold from 2024 to 2025 to reach $4 billion, representing the largest category of corporate AI costs, yet ROI in this sector has historically been difficult to quantify. Industry observers suggest that AI companies will benefit most in the near term by automating measurable work in areas like sales and customer experience. The ability to develop better metrics for evaluating AI's impact on engineering productivity could be crucial for sustaining investment levels and determining which AI applications prove most valuable.
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Companies struggle to measure AI's ROI
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