It’s time for AI to start making money for businesses. Can it?

A survey released today by professional-services firm KPMG shows that revenue generation has overtaken productivity as the primary gauge businesses use to measure AI’s return on investment. KPMG surveyed 100 U.S.-based C-suite and business leaders representing organizations with an annual revenue of $1 billion or more.

The shift in focus comes amid a period of AI-generated turbulence within IT organizations worldwide, marked by hiring slowdowns in some areas, shifting C-suite dynamics and investment in a technology that many CIOs are finding to be a heavy lift to implement.

Organizations are expected to spend $38.8 billion on generative AI in 2024, according to market research firm International Data Corp.

CIOs have extolled AI’s efficiency savings, such as a 20% boost in productivity for software developers that use an AI coding tool. But as companies increasingly move from pilot to production with the pricey technology, they’re putting a bigger and bigger spotlight on where it will have a financial impact.

“I really want to start driving use of AI at scale,” said Luke Gee, head of analytics and AI at TD Bank. “I think now is the time.”

For technology companies that can either integrate generative AI into their products and services or offer stand-alone AI products, the trajectory is simpler. “Because we sell software with AI in it, it by definition is driving revenue,” said Aaron Levie, chief executive of cloud company Box.

For companies in other sectors, measuring the increase in revenue due to AI investments is a little tougher and might take longer.

“Usually you need a couple years for a new technology to bake,” Levie said. He added that for these types of companies, revenue from AI use cases could start showing up in earnings reports next year or the year after.

That revenue may come in the form of more dollars spent by customers as a direct or indirect result of AI investments that improve customer experience, CIOs say. And as a result, they’re looking to AI tools that drive a better, more personalized experience or that can better equip salespeople and customer service to engage with customers.

Generative AI’s ability to supercharge sales and service workers is one of the primary ways companies can use it to drive more revenue, according to Stephen Chase, vice chair of artificial intelligence and digital innovation at KPMG. A tool like Copilot for Microsoft 365 could generate more revenue in the hands of a salesperson than it would in the hands of a human-resources employee, for example, he said.

TD Bank’s Gee said generative AI will be able to drive more revenue by personalizing product recommendations for customers, but that it’s still too early. Currently the bank is more focused on trialing out the technology on employee-facing use cases before getting it in front of customers, he said.

At Swedish furniture retailer IKEA Retail, according to Chief Data and Analytics Officer Francesco Marzoni, putting AI-powered experiences in front of customers is a priority. On the IKEA app, the company introduced an experience called IKEA Kreativ that lets users capture visuals of their rooms, delete existing furniture and then visualize what IKEA furniture would look like in that space.

Marzoni said he’s now working to enhance that experience with generative AI-powered features that supply personalized recommendations based on information about users’ lifestyle and style preferences. For example, he said, if a user has two kids and a cat, generative AI can present child-friendly furniture or kitchen surfaces that aren’t susceptible to cat scratches.

Better digital experiences will drive increased revenue, Marzoni said. On the initial version of Kreativ, customers who engaged with the experience were four times more likely to make a purchase than those who simply used the app, and seven times more likely to make a purchase than those who only went on the website.

Kathy Kay, executive vice president and CIO of financial-services firm Principal Financial Group, said the types of generative AI tools that will drive revenue and business growth are harder to get right and also take longer to drive returns than those that provide quick efficiency boosts.

Kay said she’s developing tools in this category that will be differentiating. She declined to be more specific on what they were, but said she’s planning to start deploying them in months rather than years.

Write to Isabelle Bousquette at isabelle.bousquette@wsj.com