A lot of companies are making a big mistake.
It’s becoming clear that AI makes people more capable than they were before. Let’s say, for this thought experiment, AI makes white collar workers twice as effective1.
Companies’ first decision is whether to do anything about this.
The 0% option is to say, “No thank you”. They do not help their employees become 2x as effective. They do exactly what they did before. About half of their employees will secretly use AI anyway to go home early or get a promotion2, but they are secret cyborgs3 who keep the AI to themselves.
Companies that invest in their employees, providing them with AI skills and making them twice as effective, there are two more options. You can pocket the cost savings, or invest them in growth.
The 50% option is to run your company with the same goals as before, but with half the people. Increasingly, companies are facing pressure to do this4.
But not all of them. Some are in countries that legally restrict layoffs5. Some are focused on the opportunities instead of the cost savings. Those companies will pursue another path.
The 200% option is to take your team of newly minted AI superheroes and accomplish twice as much as you did before. That option means doubling your output instead of halving your costs. Expand your product line, trounce your competitors, improve quality, increase customer satisfaction, and grab market share.
Now, a few questions to consider.
- 200% businesses need to double their revenue. How do you think they’re going to do that?
- Who do you think wins when a 50% business competes against a 200% business?
- If you’re not announcing plans to double your ambitions, what do your employees think you’re planning to do?6
Thanks to Ethan Mollick, Adam Davidson, Hila Lifshitz, Therese Seldon, Matt Leaverton, and Benjamin Jackson for reading drafts of this.
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It’s hard to estimate the impacts of increased quality and speed. 2x is a nice round number and in line with data, history, and trends: ↩
- Experimental evidence on the productivity effects of generative artificial intelligence | Science
- Navigating the Jagged Technological Frontier: Field Experimental Evidence of the Effects of Artificial Intelligence on Knowledge Worker Productivity and Quality – Working Paper – Faculty & Research – Harvard Business School
- Measuring the Self-Reported Impact of Early-2026 AI on Technical Worker Productivity – METR
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https://gusto.com/resources/articles/hr/team-management/ai-workplace-anxiety ↩
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https://www.oneusefulthing.org/p/detecting-the-secret-cyborgs ↩
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Harper Reed pointed this out to me after returning from Japan. ↩
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A catchall for remaining objections: ↩
- It’s very hard to uplevel folks. Not everyone can or will make it. Some will become 1.05x employees and some will become 14.7x employees and some will fall in love with Microsoft Copilot for Excel and try to name it as their next of kin.
- In case it wasn’t clear, the easiest starting point to become a 200% company is by saying “we’re going to take our AI superstars and use the increased output to just wreck our 50% competitor who’s busy laying people off and steal all their customers”.
- I know, the numbers don’t refer to the same thing. It’s 0% of change, vs 50% of costs, vs 200% of output. I apologize.
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