Managers and employees alike have gotten the message: AI is part of their job and it’s time to embrace it. That’s the good news. The bad news is that, even as AI adoption is supposed to create efficiency, it can also do the opposite as dozens of teams and individuals stand up AI initiatives that are never finished or that serve no strategic purpose.
“An executive knows there are three things that will move the needle for their business—not 300 things—but if you ask everyone how many use cases they have, they all have 300. But they’re not all equally important,” said Brett Greenstein, the Chief AI Officer at the consultancy firm West Monroe.
Greenstein made the remark at Fortune’s Brainstorm Tech in Aspen earlier this month as part of a roundtable that examined the benefits and pitfalls of rapid AI adoption across different corporate sectors.
Sean Bruich, SVP and CTO of pharmaceutical giant Amgen, described himself as “a card carrying data scientist” and is deeply familiar with AI. He made the case that some companies may need to focus less on the technical dimensions of AI, and more on the business and political challenges of implementing these new tools.
“The explosion of pilots around AI inside a company can become an incredible drag on your ability to move quickly, because each one of those has a champion and a team and a set of KPIs and a data engineering squad,” said Bruich, who said too many pilots can obscure which elements of AI are delivering business value, and that some firms are too slow to kill the ones that don’t.
Dan Gill related that he has learned similar lessons as Chief Product Officer at Carvana, a logistics heavy firm that arranges vehicle purchases between millions of buyers and sellers, and runs a massive financing operation.
“Getting one thing all the way done is much more valuable than five things progressed to 20% each,” he observed. “[AI means] prototyping is cheap, and documentation is cheap, and code generation is cheap, and suddenly it’s so easy to do things—but the reality is getting that number one thing all the way done and iterating on it really tightly is much, much, much more valuable than just advancing lots of stuff.”
The upshot is that, even as AI offers tantalizing promises of massive productivity gains, the reality is that too many companies are expending valuable resources on projects that lower productivity because they don’t accomplish anything useful. The solution said Nizar Trigui, who is Chief Technology Officer at the logistics giant GXO, is to ensure company leaders focus as much on the business dimensions of AI as they do teaching the tech angles.
“We all found what we’re doing is no longer just a technology-led transformation. This has to be a business led transformation, it has to be led from the top. It has to be from the board, it has to be from the CEO, the entire executive team, and they need to be engaged in that entire transformation,” he said.
This is easier said than done, noted the panelists, because there is a tension between adopting AI efficiently and the metrics that have historically signaled success as a leader—headcount size, spreadsheets, KPIs and so on. Despite these challenges, though, leaders no longer have the option of
“I think we’ve crossed the Rubicon … The ships are burnt,” said Gill. “There is no going back but the future is bright.”
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