“The most important question for CFOs is not how much can the organization spend on AI, but whether those investments are being deployed in ways that reinforce the business’s core growth and value drivers,” said Carlsen. “Moreover, the near-identical amount of use cases for efficiency and productivity use cases between efficient growth firms and control peers suggests that productivity-focused AI investments alone do not explain performance differences, and that automation by itself is increasingly becoming table stakes rather than a durable source of advantage.” … “For CFOs, the implication is to evaluate AI investments not only by the return of individual use cases, but also by how well those capabilities reinforce broader growth, product and decision processes across the enterprise,” said Carlsen.
I’m going to say this means: (1) use AI to improve how individual work, making them more “productive.” This get your bottom line improvements, but, (2) the way you’ll make money with AI is coming up with new things to sell in your business, features, products, markets you expand into, incremental improvements to your product that customer upgrade to, etc. that is where growth comes from.
The first is, or will, be commodity and required for all, the second likely more challenging and ignored by many.
On the finance department, there’s plenty of the first:
The clearest outcome so far has been efficiency. Among finance organizations that have adopted AI, 66% reported greater efficiency and productivity as a top benefit.
But people still have unrealistic expectations about quickly new technology and transformation can be rolled out:
63% of finance organizations said AI implementation was slower than expected in 2025. Analytics-related use cases also remain difficult to convert into high impact, with financial forecasting and insight generation among the lowest-rated use cases
Originals:
🔗 Gartner Says CFOs Must Stop Mistaking Finance AI Deployment for Value Creation
🔗 Gartner Says CFOs Gain a Competitive Advantages from Strategic AI Deployment, Not AI Spending Levels