Even AI champs blink on job cuts

Mark Zuckerberg called off widespread job cuts at Meta earlier this year in a high-profile example of the limits companies face when trying to become AI native. Such enterprises are structured in a manner that means they can't operate without AI. Most companies are unlikely to become AI native soon because they can operate with humans and still get the job done, maybe at a higher cost. Even this point is debatable because the productivity gains from AI are not yet quantified with precision. This ensures that any decision for a business leader to make his organisation AI native is a subjective choice and is impossible to execute unless he is starting from scratch.

The traditional approach of incorporating AI around human skills - rather than building enterprises around AI skills supplemented by humans - remains the key pathway for organisational evolution. This limits how far companies can go with job cuts. Aggressive strategies have retreated, with firms rehiring after excessive deskilling or inadequate agentic performance. A dense cluster of human skills guiding a large agentic workforce can easily become an over-simplification without clearly defined human-AI interactions. AI-native enterprises need a matrix for human intervention, companies with legacy human workforces need one for AI intervention.

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AI-native enterprises are more likely to emerge in the startup space because retrofitting legacy businesses with AI may not be easy. AI job replacement is rarely a clean swap. A more harmonious outcome can be achieved by reskilling people to work with AI. This is straightforward in a startup built around specific sets of AI skills. These can be complemented through sensitised hiring. The process rarely remains sensitised when job cuts are involved. The likelihood of losing more skills than anticipated is high. Enterprises must position themselves on an AI dislocation scale within the business environment in which they operate. As Meta has shown, even AI champions blink.