Executives hyped for AI revenue, but unclear how

Enterprise executives have faith their AI bets will pay off by 2030, but few have any idea where that income will come from, according to a new study.

Expectations for AI run high among the C-suite executives surveyed for the IBM Institute for Business Value’s The Enterprise in 2030 report, with 79% of respondents saying they expect their AI initiatives to produce positive revenue results in the next four years. But less than a quarter surveyed can identify the source of that revenue.

Successful C-suite leaders will figure out how to meet their AI goals while managing potential roadblocks, IBM says.

“That gap between expectations and outcomes presents the leadership challenge of this decade,” Mohamad Ali, senior vice president of IBM Consulting, writes in the report.

While the survey may suggest unrealistic hype over AI, IBM urges executives to make big bets on the technology. In 2030, business success will be measured by how much an enterprise disrupts its industry quarter by quarter, not by steady progress toward long-term targets, IBM predicts.

“The biggest risk won’t be making the wrong bets — but making bets that are too small,” the report says.

Executives see an AI future even if predictions about the specifics are still a bit cloudy, notes Salima Lin, managing partner for strategy, transformation, mergers and acquisitions, and thought leadership at IBM Consulting.

“It’s clear that executives see the destination, but they’re uncertain how to get there,” says Lin, a coauthor of the report. “There is this realization and understanding that that is where the market is headed, and those companies that can close that gap are going to be the winners.”

AI hype hangover

Other AI experts see the survey as evidence of executives still buying into hype. “It sounds to me like blind faith,” says Danilo Kirschner, managing director of cloud consulting firm Zoi North America.

While Kirschner sees great potential for AI, he predicts 2026 will be a year of the AI hype hangover. AI initiatives will still move forward, he says, but with more realistic expectations, including revenue projections.

“CIOs will be praised not for launching the biggest AI, but for shutting down the most wasteful ones and proving tangible ROI,” he adds.

Kirschner also sees a pivot toward small AI initiatives, with projects moving toward highly specialized, efficient, and cost-contained models focused on specific business automation. “Smaller models are cheaper to run and easier to train with clean, accessible data,” he adds.

Company shareholders appear to be growing impatient with multi-billion-dollar AI experiments that don’t generate ROI, he says.

“Enterprises are in an arms race, investing billions into massive, ‘do-everything’ foundational LLMs and launching countless generalized AI experiments,” Kirschner adds. “The ROI simply isn’t materializing fast enough to justify the immense costs of compute power, complexity, and data management.”

The survey shows a lack of strategic thinking about AI, adds Magnus Slind-Näslund, CTO at language translation technology vendor Lokalise.

“Too many leaders are going all-in on AI with no clear strategy for how it will actually pay off,” he says. “Everyone wants in on it, but not everyone knows what they’re actually building toward. You can believe in the tech, but you still need a solid reason to adopt it.”

Revenue gains from AI will only happen when organizations apply AI to specific and friction-prone problems, Slind-Näslund adds.

“The gap between excitement and execution is how most companies fall short,” he says. “It makes sense to expect revenue from AI eventually, but expecting it when you don’t even know where it’ll come from doesn’t, and that mindset is more optimistic than strategic.”

Can’t afford to wait

But other AI experts see a bright future for AI, even if some early experiments haven’t worked out.

Gain Servicing, a financial services company focused on personal injury claims, has seen real benefits from AI, including faster software development with coding assistants and streamlined claims processing, says Farah Hirth, director of AI and technology at the company.

Smart organizations looking for AI advances will look thoroughly at their workflows and identify-specific bottlenecks, she says.

“It makes sense that executives expect revenue gains from AI, though some do overhype it as a cure-all,” she adds. “The organizations that will truly benefit are those that treat AI as a tool for targeted problems — not a strategy unto itself.”

However, organizations moving too slowly will miss out on the benefits of AI, Hirth says.

“I don’t think you can afford to be pessimistic,” she adds. “People might say you’re hyping it up too much, but I’d rather overhype it and see what could be done with it than under hype it and fall behind because I didn’t want to try it.”

IBM’s Lin urges CIOs to keep thinking about ways to advance their businesses by using AI in innovative ways. The most successful organizations will figure out ways to use AI in ways that no one else has, she says, and the most successful CIOs will understand their organizations’ business strategies and incorporate AI.

“You’ve got to start now because you can’t wait,” she adds. “AI is getting smarter, it’s getting better, it’s producing tasks, and if you wait, you’ll be left out.”