We’re already seeing AI systems being deployed in every sector. There are estimates of what AI can provide to the world economy and this might be accurate assessments of current AI tools, but probably far underestimates future systems - at least the systems AI companies are explicitly aiming to create.
Currently, it’s not trivial to automate custom workflows, which is where a lot of business value lies. This might require custom scaffolding, calling APIs in the right way, or lots of ‘glue’ code.
Future AI systems will likely be able to learn new workflows without need for this ‘glue’, take real actions in the world, and better execute strings of tasks. This might look like controlling a computer to take the actions that an employee would.
Learning these workflows could enable valuable jobs to be replaced entirely by AI systems.
In addition, most countries have worker shortages in domains that can be done entirely remotely, such as software engineering. These positions could be filled by AI systems. Additionally, there may be hidden growth opportunities that AI systems performing those professions cheaply could expose.
Together, this could be incredibly valuable for AI companies: instead of just increasing the world economy by single-digit percentages, they could be capturing almost half of current wages in developed countries.
These companies might be able to operate much faster than human companies, making them far more competitive: we might see an explosion of new companies all innovating and competing, resulting in the fraction of economic work being done by AI systems skyrocketing.
Private companies being driven by economic gain makes sense.
However, this isn’t the full picture. There is a wide range of motivations that incentivize people to build AI systems: