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Julie Hyman: A new study says that 90% of companies are increasing AI budgets without seeing the desired returns. Research from consulting firm Bain shows 50% of companies are seeing savings of only 0 to 10% and they were actually expecting a lot more, about double that figure.
Michael Heric: First of all, I don't think it's just about cost. So I think when when many companies are looking at AI, they're looking at benefits beyond productivity. So for example, it could be like speed. So let's say you're forecasting revenue or something, and you're a CFO, you want to get those results faster. It could be working capital improvement, it could be a better customer experience. So it could be a broad range, but clearly, productivity is part of it and cost savings is one element of that. And you are right that returns typically are lower than what people expected.
Hyman: And is that just a matter of it being early, do you think? Why is that happening?
Heric: Well, I think some of it is, if you look at past cycles, let's say, AI's very, very quick adoption has been very, very rapid. But if you go back in history, and, let's say, you look at the internet for example, the internet was adopted pretty quickly. Let's say about 50% adoption within 10 years, but it's taken 20, 30 years, even now, to really transform business models and reinvent retail and financial services. That's all ongoing. And it's sort of similar here. AI is in the hands of a lot of different people, a lot of different companies, and it's sort of like, 'What do I do with this new technology? How do I actually make it deliver returns?' And that takes time.
It's like taking a look at your actual business processes themselves. So it's just like that internet example. It's great. I can go online, I can do different things, but until companies fundamentally changed the business model and how they work due to the internet, then basically, they're not getting the full benefits from it. It's the same thing with AI as well. People are kind of going out there, they're trying lots of different things, but at the end of the day, the business process hasn't fundamentally changed.
That's for some companies, Julie. There are other companies that are actually fundamentally changing their processes. There are CFOs, for example, using traditional machine learning, generative and even agentic AI that are getting returns and are seeing the benefits, but they're really addressing these business processes head on.
Hyman: And they're still the minority.
Heric: They're still the minority today, which is not surprising. I mean, a lot of the earlier adopters, one thing that we noticed, for example, in our study is that it's not by accident that those companies that have had more experience in these prior technology adoption waves, so let's say, deterministic automation like RPA, or before that with Cloud as an example, are now many of them are actually leading the charge here.
So if you figure that out in your organizations, you figured out how to harness those technologies in your business processes, and now you're going to do the same thing again with AI and those tend to have a leg up.
Your AI Budget Is Growing. Your Returns Aren't. Here's Why.
AI keeps underdelivering on its promise. The fix is organizational, not technological.