Around 2015, the U.S. auto industry was making bold predictions about EVs. If you attended any conference or read industry news back then, the conversations weren’t about whether full electrification would happen, but just how fast it would occur.
At Trupropel, we've spent years building software through waves of emerging technology, and at the same time, working deeply with automotive industry clients. We have a unique perspective about the parallels we're seeing with AI - not about whether it will change how we work, but about how much work we’ll eventually hand over to it.
The EV transition is an important lesson. It shows us what happens when the possibilities of technology get ahead of the realities of people who adopt it.
Back then, those bold EV predictions were made in good faith. Battery costs were falling, range was improving, and major OEMs made serious electrification pledges. Then, they retreated and softened their commitments. (The EV transition is still happening, mind you, just not on the schedule people once predicted.)
At the time, Toyota was treated as a contrarian. While competitors made sweeping, full-EV goals, Toyota kept investing in hybrids and argued the world wasn't ready for a rapid all-electric shift.
Toyota wasn't arguing that EVs were the wrong answer. It was arguing they weren't the only answer because the world is large, diverse, and unpredictable. Real-world constraints still mattered.
Rural charging gaps, apartment dwellers without overnight charging, cold-weather performance, fleet range requirements, and developing markets where the economics simply didn't work all shaped adoption. Toyota built its strategy around those realities instead of assuming technology alone would change customer behavior, and it paid off.
In 2024, for example, U.S. sales of the RAV4 Hybrid alone climbed nearly 30%, and in Q2 of this year, it achieved an all-time sales record. Toyota's decision to keep hybrids in the mix hasn't held it back. In fact, its success suggests there's real value in meeting customers where they are.
At the time, Toyota's strategy looked like a failure of nerve. In retrospect, it was an accurate read of how change actually happens – inconsistently and on its own timeline.
The bigger lesson here is about predictions. Back then, an EV-only future felt so certain that questioning it wasn't always easy. But markets don't make decisions. People do. And they have different incomes, live in different places, and have different priorities.
This lesson applies well beyond automotive. It's being tested right now in every organization trying to figure out how much of its work to hand over to a machine.
There’s no denying that AI will reshape businesses across the globe. But progress rarely arrives in a straight line, and it almost never arrives on predicted schedules.
At Trupropel, this isn't theory for us. We build software and staff people who put AI to use every day, so we watch this tradeoff play out in our work.
Just like the auto industry didn’t crown a single EV winner, AI is unlikely to produce a ‘one-size-fits-all future.’ It’s not about how much work we hand over to AI, and it’s not about chasing bold predictions.
The companies most likely to succeed will be the ones who know their customers, their people, and their business well enough to apply AI where it actually creates value – and recognize where human insights still matter most.
I’m always up for a discussion about the auto industry, AI, and software development. Feel free to shoot me a note at chris@trupropel.com. I’d love to hear from you!
