Question: Do you think we spent too many decades training humans to work like machines… so we, kinda, dug this AI hole for ourselves?
Think about how we define “success” for the modern organization. Consistency… predictability… efficiency… repeatability. We created processes, workflows, scripts, templates, systems, KPIs, knowledge centers and increasingly sophisticated ways to measure whether people were doing what they were supposed to be doing. We took complicated jobs and broke them into smaller tasks. We standardized those tasks. We optimized them. We removed as much variation as possible because variation made everything harder to manage. If you went back in time (say twenty years) and showed someone many of the job titles on LinkedIn today, my guess is they would not even know what the person actually does all day. We’ve become remarkably good at abstracting work into roles, functions, processes and outputs.
In many ways, we trained people to work like machines… then we built the machines.
Tom Rath (famed author of StrengthsFinder 2.0 and his latest book, What’s the Point?) was my guest on this week’s Thinking With Mitch Joel. During our conversation we, of course, went down the AI and future of work rabbit hole… and that’s where it crystallized for me this notion that organizations have spent the better part of a century designing work around exactly the characteristics machines are now becoming incredibly good at. So, maybe some of our anxiety about AI is aimed at the wrong target. The machines didn’t suddenly make our work machine-like… we did that long before they arrived.. Productivity is how we measure… efficiency is how we win… predictability is how we scale. And… it worked. But, like everything, there were trade-offs. The easier work became to standardize, the easier it became to separate the work from the person doing it.
And now AI arrives unevenly.
If a task can be clearly defined… repeated… measured… documented… and optimized… that sounds suspiciously like something AI eats for breakfast. Thankfully, Tom has spent much of his career studying strengths, purpose and what allows people to contribute meaningfully. One idea from our conversation was that purpose doesn’t have to be this massive existential quest. It can exist in the next hour… the next interaction… the ability to make someone else’s life slightly better. That sounds almost ridiculously human compared to most conversations about productivity.
…And that’s where this can get interesting.
We keep telling people that AI will free them to do “higher-value work.” I use that language too. But what is higher-value work? If AI allows someone to complete ten projects instead of five, have we made work more human… or simply adapted to a new machine? Organizations can’t spend decades rewarding people for following the system and then suddenly tell them to become more curious… entrepreneurial or (worse) comfortable with ambiguity because AI showed up. Quick reminder: the person who questioned the process was difficult. The employee who experimented outside the workflow went rogue. The team that took an unusual path created risk. And now we’re telling those same people that their future depends on behaving in precisely the ways we spent decades managing out of them?
Maybe what we suddenly need is not chaos… but human variability.
The judgment to deviate… the curiosity to question… the confidence to try something without knowing exactly how it ends. Honestly, I don’t even know whether these skills remain uniquely human forever. I’m increasingly uncomfortable making predictions about what AI will never be able to do. But that may not even be the point. The more immediate question is why we designed so much human work around capabilities we were always trying to automate in the first place.
Perhaps the future of work is finally giving people permission to stop working like machines.
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