As a pair of academics wrote recently in MIT Sloan Management Review, “The barrier to full automation isn’t raw capability—it’s a stack of human, legal and cultural constraints.”
Modern AI adoption is yet another example of a concept first described way back in 1987, called Solow’s Paradox. At the time, economist Robert Solow was studying how newly integrated computers were affecting worker productivity. His finding: They weren’t, at all.
In this productivity paradox, all that spending on shiny new computers and the digitization of work processes didn’t seem to make companies any more efficient or effective.
Years later, adoption of information technology did start to show up in economics statistics. It turns out that just handing people tech doesn’t do much—it might even slow them down. It takes time for the work processes inside of companies to be reorganized and refined around new information technologies.
For every tweet that says AI will demolish software engineers in X months I think bout the software that has been running for longer they’ve been alive quietly humming in the background. I think this take is most mature; that AI adoption is in its infancy and real gains will take years if not decades to materialize.
Quote Citation: Christopher Mims, “AI Adoption Among Workers Is Slow and Uneven. Bosses Can Speed It Up. - WSJ”, Nov. 28, 2025 at 5:30 am ET, https://www.wsj.com/tech/ai/ai-adoption-slow-leadership-c834897a