Big Tech’s Layoffs, AI, and the Closing of the Productivity Gap

Big Tech has let go of thousands of workers in the last couple of months. In addition to the end of the era of cheap money and a broader economic slowdown, this story may have another angle.

This is the impact of AI and the possible closing of the “Productivity Gap.” 

The Productivity Gap is a phenomenon where workers’ output, especially in developing countries, has been growing slower than expected. The shift to cloud computing and SaaS business models in the mid-2010s led to an explosion in both the valuations of technology companies and increases in the productivity of individual engineers and teams. A small startup could spin up and scale a business faster than ever. 

Fast forward to the mid-2020s, and suddenly cloud computing is a commodity. Innovative Frameworks from the last decade, like React, Spring, and others, are bloated and complex. 

For the last few years, companies like Meta, Alphabet, and Microsoft could hedge their bets and grow their teams because they were less likely to become disrupted by a small startup. Hoarding talent and doing “acqui-hires” was a feasible strategy.

Explaining the Tech Layoffs

Now there is once more a disruptive technology on the horizon. Generative AI Models are making giant leaps – a small team of ML-native programmers could build something that could blow incumbent services out of the water. 

Alphabet’s panic over OpenAI’s ChatGPT is a case in point. Suddenly it doesn’t make sense to hoard talent to work on a platform that is about to be irrelevant. 

AI-enabled software and infrastructure could close the productivity gap and fuel the rise of disruptive startups. 

The incumbents are then cutting costs and preparing themselves for the next round of disruption by making significant investments in AI. 

It no longer makes sense to hoard programmers when the entire industry could undergo a paradigm shift similar to that brought about by Cloud Computing 15 years ago.

The brutal layoffs we have seen in the last three months could be the result.