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The smartest AI strategy still starts with people.
IBM built an AI assistant, AskHR, that now resolves 94 percent of its routine HR queries. By almost any automation standard, that’s a triumph. So, it surprised a lot of people when the company announced plans to triple its U.S. entry-level hiring in 2026.
The reason comes down to the other 6 percent—the requests involving ethical calls and exceptions the AI couldn’t handle.
For leaders, the lesson is this: The routine work was never where your people’s value lived. If you cut heads based on what AI can do on an average day, you’ll pay for it on the hard days.
IBM isn’t alone in learning this. New Robert Half data from a survey of nearly 2,000 U.S. hiring managers found that 32 percent had eliminated a role primarily because of AI then rehired for the same or a similar position. In finance, it was 44 percent.
Research firm Orgvue found that of leaders who made staff redundant for AI, 55 percent now admit it was a mistake. Gartner expects that by 2027, half of the companies that cut jobs for AI will be rehiring for similar positions.
If you’re deciding which roles AI should absorb, the reversal wave is a cheap education. Here are three things worth doing before you sign off.
1. Map the work before you cut it.
Org charts show job titles. They don’t show where judgment actually happens.
Commonwealth Bank of Australia cut 45 customer service roles after deploying an AI voice bot in July 2025 and reversed the redundancies within weeks when call volumes told a different story.
I spent six years running support at Evernote while we scaled from thousands of users to over 100 million. The overwhelming majority of tickets were routine, and yes, you want those automated. However, the customers who stayed loyal for a decade weren’t won on the routine tickets. They were won on the weird ones—the edge cases where someone on my team bent a process and turned a furious user into an evangelist. That work never showed up as a line item. It was invisible right up until you cut it.
Before you eliminate a role, sit with the person doing it and list everything they handled last month that required a decision the documentation didn’t cover. That list is what you’re really deciding on.
2. Protect your pipeline, not just your payroll.
Nickle LaMoreaux, IBM’s chief human resources officer, put the second problem plainly in a video interview.
“If we don’t continue to invest in entry-level hires, what happens in three to five years?” he asked. “There’s no pipeline.”
Entry-level work is where judgment gets trained. Stop hiring juniors because AI does their tasks, and you’ve scheduled a leadership shortage for 2029.
The founders I coach hear this from me constantly: Your senior people were once junior people someone was patient enough to develop.
3. Treat AI as a tool, not a strategy.
Ford has spent three years rehiring and promoting about 350 veteran “gray beard” engineers to work alongside its AI systems.
“Artificial intelligence is a fantastic tool, but it’s only as good as the information you use to train it,” explained Charles Poon, Ford’s VP of vehicle hardware engineering.
The result: Ford’s best J.D. Power Initial Quality ranking in 16 years, while still targeting $1 billion in savings.
Notice what Ford didn’t do. It didn’t choose between AI and experience. It paired them and got quality and savings at the same time.
Finally, remember: AI will keep getting better at the 94 percent. However, your hardest customers and your worst days live in the 6 percent. Staff for that, and the rehiring wave stays something you read about instead of something you explain to your board.
This post originally appeared at inc.com.
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