Artificial Intelligence Didn’t Sneak Up On Us. It Jumped Us.
I was on a conference call recently where four different A.I. note-taking bots joined the meeting. Not one. Four. Each there so their respective humans didn’t have to take notes and/or were too busy to join the meeting. At a certain point, will we start to wonder who the meeting is actually for.
How long until the bots don’t just attend meetings—they run them? No host. No participants. Just a handful of A.I. tools exchanging updates, aligning on next steps, and sending everyone a summary afterward. (But honestly… if that eliminates half of all recurring meetings, it might be the most popular application of A.I. yet…)
Three years ago, artificial intelligence was something you read about. Now it’s something you work with. And not in a futuristic, Jetsons kind of way. In a very real, very practical way. It’s writing first drafts. It’s summarizing long reports you don’t have time to read. It’s helping people get through their inbox faster. It’s sitting quietly in the background of a lot more work than anyone is willing to admit out loud. Including this piece.
A.I. helped with the organization and editing of this post. Not because I had to use it—but because it would have been inefficient not to. That’s the reality now. The dividing line isn’t between people who use A.I. and people who don’t. It’s between people who use it well… and people who pretend they don’t.
What changed wasn’t just the technology. It was the speed.
How This Happened So Fast
You’ve likely seen the adoption curve chart by now, but it’s still worth pausing on. Television took decades to spread. The internet took years. Smartphones felt fast. A.I. made all of that look… slow.
ChatGPT reached 100 million users in about two months. That’s not just a record—it’s a signal. People didn’t adopt it because they were curious. They adopted it because it was immediately useful. It saved time. It reduced friction. It made work easier. And once something does that, it doesn’t stay optional for long.
Five years ago, most people assumed A.I. would hit manual labor first. Factories. Warehouses. Transportation. Instead, it went straight for laptops. Research, writing, coding, analysis—tasks that were supposed to be relatively insulated—are now some of the most exposed. Not eliminated, but fundamentally changed.
To be fair, some predictions were directionally right. A.I. is augmenting more than it is replacing. Routine work is being automated first. But almost everyone underestimated how quickly this would move from theory to default behavior.
But how is this affecting companies and the job market RIGHT NOW? A lot of companies are still “figuring out their A.I. strategy.” Their employees are not. They’re already using these tools—sometimes with approval, often without it—because the productivity gains are too obvious to ignore. Some companies mandated the use of A.I. Some companies tried banning it (their employees didn’t listen).
According to a January Gallup poll, U.S. workplace A.I. use continued its gradual rise in late 2025, with daily usage increasing from 10% to 12% and frequent use (a few times per week or more) reaching 26%. At the same time, overall adoption appears to be leveling off—nearly half of workers (49%) still report never using AI at work. For a broader, cross-country signal, the OECD reports that firm-level AI adoption in 2025 reached 20.2%, up from 14.2% in 2024 and 8.7% in 2023, meaning adoption more than doubled over two years.
You can see A.I.’s effect on jobs most clearly at the entry level. Jobs that used to be about learning how to do the work—drafting, summarizing, researching, analyzing — are now partially handled by A.I. That doesn’t mean those roles disappeared, but it does mean fewer people are needed to produce the same output. At the same time, you’re seeing the rise of what people casually call the “10x worker.” Someone who knows how to use A.I. tools effectively can produce significantly more than someone who doesn’t.
The World Economic Forum’s Future of Jobs Report 2020 projected 85 million jobs displaced and 97 million created by 2025 from shifts in human/machine task allocation. The updated WEF 2025 report reiterates the same underlying theme—large churn and reskilling pressure—extended through 2030.
Why This Matters For Policy
Across industries, A.I. is already forcing new policy questions.
Healthcare: diagnostics and liability
Finance: algorithmic decision-making
Housing: pricing transparency
Energy: data center demand
Workforce: job displacement and retraining
All of these questions are being debated—right now—at the state level. According to Multistate, more than 1,500 A.I.-related bills have already been introduced in 2026 alone.
A.I. didn’t sneak up on us. It showed up all at once, embedded itself into how work gets done, and kept moving. The question now isn’t whether it will change policymaking. It’s whether policymaking will adapt fast enough to keep up.