I have done some quick back-of-envelope calculations on the progress of AI, trying to estimate how much progress has been made vs. how many job-related functions and activities there are left to automate.
On Angel List and Crunchbase there are a total of 4830 AI start-ups listed (assuming both lists contain zero duplicates). To figure out how many unique AI tools and capabilities there are, let’s assume the following:
- All these companies have a working product,
- Their products are unique and have no competitors,
- They are all aimed at automating a specific job function, and
- These start-ups only represent 30% of all AI-focused company universe.
This gives us a pool of 16,100 unique, operational AI capabilities. These capabilities will be in deep domains (where current AI technology is most successful) such as booking a meeting between two people via email.
If we compare this to the number of domain specific activities in the world of work, we can see how far AI has come and how far it has to go before we are all working for the computers. Using US government data, there are 820 different occupations, and stock markets list 212 different industrial categories. If we make the following set of assumptions:
- 50% of all occupations exists in each industrial category,
- Each occupation has 50 discrete activities.
This gives us a total of 4.34 million different occupational activities that could be automated using AI. In other words, at its most optimistic, current AI tools and processes could automate 0.37% of our current job functions. We have come a long way, but there is still a long way to go before we are out of work. As William Gibson said, “the future’s here, it’s just not widely distributed yet”