AI Transformation’s Slow March, and One Giant Rewiring Itself

Good morning. Years into the boom, AI’s potential hinges on two parallel timelines—one technological, one organizational—and the endpoints on both are hotly debated. When, exactly, “recursive self-improvement” becomes real is a hot topic in Silicon Valley and, increasingly, Washington, D.C. More on that below.But in the C-Suite and fireside chats worldwide, the focus is on true AI-powered enterprise transformation.

From the reams of surveys and reports on the topic, it would seem like the task of transforming a business to take advantage of AI—and make those investments pay off—is far, far more complex than cracking the Navier-Stokes problem.

Success, so far, is uneven. Over the past 12 months, Deloitte found that 34% of companies were using AI to transform their business, while a Publicis Sapient survey found 42% admitting that their organizations weren’t ready to capture AI’s value. Operations leaders surveyed by PwC were just as candid, with only 27% saying they had fully embedded an AI strategy across business units.

A major obstacle to enterprise AI adoption, according to those reports, isn’t technology capability, but the sheer velocity of organizational change hitting employees.

Panelists at this week’s WSJ Technology Council Summit added to the chorus.

“This is a massive amount of change coming at them way faster than they’re comfortable with,” said Janelle Sallenave, chief operating officer of fintech firm Chime. “And so I think as leaders there is a thing that we often maybe diminish because we’re so focused on the tech side of how do we make the right culture change so that we are able to lean in to and use and get the ROI and get the change we are looking for.”

Finding an Exception

Coding is where generative AI has found the most uptake, and it’s within software firms—especially smaller, AI-native startups—where AI-powered workflows and processes have found the most traction.

The WSJ Leadership Institute’s Steven Rosenbush today looks at a similar transformation at another coding-forward firm—but this time it’s tech giant Microsoft, founded decades before ChatGPT’s debut. A revolution in software development there, spurred by generative AI, has accelerated a broader one in its business processes. The company is now rethinking traditional organizational structures and roles, he reports, and using AI to design end-to-end workflows across its organizations, from software engineering to sales.

Charles Lamanna, executive vice president of Copilot, agents, and platform, tells Rosenbush that the days of coding as we once knew it are over—and with it, the traditional, vertically aligned structure of his 20,000-person unit.

Microsoft is releasing a “Frontier Playbook” today, drawing on lessons from its own experience. Read our story.

The fight over AI’s risks and whether Washington should do anything about them has only intensified this week. A few notable threads:

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Follow Isabelle Bousquette on LinkedIn, Instagram, X, and TikTok for more behind the scenes on her tech and AI coverage, and lately, her contributions to the WSJ Leadership Institute’s new Executive Resilience series, where she’s profiling America’s top execs about their fitness and wellness habits.

Follow Belle Lin on LinkedIn and X for her latest reporting on enterprise technology and AI.

Steven Rosenbush is chief of the enterprise technology bureau at the WSJ Leadership Institute. He also has a column. You can follow him on LinkedIn.

Tom Loftus is the editor of The Morning Download. He suggests following Isabelle, Belle and Steve on their various social channels. But if you insist, here’s his LinkedIn.