Where companies should place their AI bets

After several years of pushing organizationwide AI adoption, companies are now confronting the cost. As boardroom conversations shift to return on investment, business leaders are taking a harder look at which AI bets to fund and scale.

To understand what questions executives should be asking ahead of AI investments, Meredith Mazzilli, The Information’s finance editor, spoke with three experts approaching AI from different perspectives.

• Karen Young, chair of the U.S. board of partners and U.S. sales leader, PwC
• Mimi Carsley, chief financial officer and treasurer, Jack Henry & Associates
• Heidi Rhodes, global director, enterprise GTM customer success and sales enablement, Meta Platforms

Resetting Priorities

At Meta Platforms, Mark Zuckerberg has taken an experimentation-first approach, making AI adoption a priority across the company.

“He basically said, ‘This is going to be the year that everyone is going to adopt AI.’ We told our employees, ‘Figure out what works and go fail,’” recalled Heidi Rhodes.

That freedom to experiment helped Meta identify which workflows benefited from AI and standardize around them. Initially, token consumption wasn’t a concern, a luxury Rhodes acknowledged not every organization can afford.

“In 2023, it was: Any single problem that you have, rub some AI on it. Then we got our token bills,” she said. “Now organizations are saying, ‘Unless you can show me real ROI, we can end the conversation there.’”

Other companies took a more cautious route. Jack Henry & Associates, which operates in the highly regulated financial services industry, started with governance, establishing guardrails for assessing and approving AI tools and determining what data employees could access, said CFO Mimi Carsley.

At PwC, the challenge is less a shortage of ideas than deciding which ones are worth pursuing. Employees across PwC are embracing AI and exploring new ways to integrate it into their work. Karen Young said the deciding factor in funding ideas remains the client, much as it did before AI.

“We think about the solutions our clients are looking for and how we can scale [our AI tools] for their benefit,” she said.

Controlling Spend

At Jack Henry, providing Microsoft Copilot licenses to all 7,300 associates could add $3 million in costs, said Carsley. The company therefore regularly reassesses who needs access.

“If someone’s not using their license, we’ll go talk to them and coach them up. If they’re still not using it, we actually seize it back and redeploy it elsewhere in the organization,” she said.

Young said PwC has also shifted to training employees to be more efficient with their usage.

“We lead them to use the right tool for the right model for the right reason,” she said.

Measuring What Matters

One way organizations can prioritize AI spending is to look beyond efficiency gains to how those gains are put to use. By way of example, Young cited a client that transformed 14 finance processes, cutting forecasting and scenario planning from weeks to minutes.

“The real question is: What are those employees in finance now doing to be more strategic with their time?” she asked.

Carsley said companies also need to consider how they are using those time savings and whether they can redeploy investment elsewhere.

“If someone’s gonna use AI to draft an email and you save five minutes, like, did you go get a cup of coffee or did you do something with the five minutes?” she said. “If you’re not redeploying that savings to another productivity or efficiency, did you really gain anything by the spend?”

Rhodes, meanwhile, cautioned against treating efficiency gains as an excuse to reduce headcount. She cited a client whose sales team became 20% to 30% more productive after AI took over hours of research.

“Do you make a reduction in humans? Or now that you have one of the world’s most efficient salespeople, do you go out and hire more?” she asked, adding that her vote is for the latter.

Ultimately, though, AI prioritization comes down to a company’s unique advantage.

“Ask yourself, what do you have an advantage in? Then apply AI to that as an accelerant,” advised Carsley. “Do the thing you do best as an organization, then turn it up 10% to 20%.”