ÌÇÐÄÆƽâ°æ

Generative AI had the least impact on the automation possibility of builders and agriculture professions in 2023. These are highly irregular and take stock of local conditions, each project being highly individual, and most of these professions are highly physical. The physical nature of these industries means that the wholly digital process of generative AI has the least impact potential on them.

Education to face the greatest challenge

Positions requiring the highest levels of education are the ones most likely to see a significantly increased rate of automation with the use of generative AI. Master’s degree positions or higher had barely a of a chance of being automated before generative AI but are likely to be automated at a rate of nearly ** percent with generative AI. In stark contrast, positions requiring no education were already very likely to be automated but saw nearly no difference with generative AI, or a bare increase of **** percent.

Direct relation to structure

The gain from generative AI in automation is in similar proportion to how much education the position requires and in direct relationship with how linear and structured the position is. That is to say the less its duties vary from case to case. Education and workforce training, which require degrees but are also highly structured, are the most likely to be automated. On the reverse are positions in agriculture and building, each so varied and individual that generative AI can do little to influence the automation process.