Outside of tech companies, other areas where AI is used fairly often are in education and library services; arts and media; office and administrative work; and life, physical, and social sciences. As you'd expect, jobs reliant on physical labor have the lowest AI usage rates. The most notable example is farming, fishing, and forestry, which accounted for just 0.1% of queries.
Still, a growing number of occupations are using AI. The way they use AI depends heavily on the type of job.
Some occupations predominantly use AI for automation, meaning the model directly completes a task with minimal human involvement. Computer systems administrators, web administrators, and software developers are the top occupations that use AI in this way.
Other occupations mainly use AI for augmentation, where the model and the human work together on a task. Copywriters, editors, and instructional designers are the top occupations that use AI to augment their work.
Is AI Adoption About to Take Off?
No industry has high AI adoption yet, but that could change over the next few years. Leading AI companies are seeing massive demand and making significant investments in product development.
U.S. private AI investment reached a new high of $109 billion in 2024, according to Stanford HAI's 2025 AI Index Report. And many major tech companies have plans to increase their AI data center spending even more going forward. The Stargate Project is a recent example -- SoftBank, OpenAI, Oracle(ORCL +2.23%), and MGX are planning to invest $500 billion toward building new AI infrastructure in the United States.
One of the main drivers of AI adoption is the development of lower-cost models. These make it easier and more affordable for companies to integrate AI throughout their businesses. AI models are getting cheaper -- the cost of querying an AI model that scores the equivalent of GPT-3.5 went from $20 per million tokens in November 2022 down to $0.07 per million tokens by October 2024, according to Stanford HAI. That trend should continue, spurred by competition from Chinese AI company DeepSeek.
How much AI use increases will also depend on how it affects productivity. The early returns on this are promising, with studies finding that AI can boost worker productivity on certain tasks but not all of them. Businesses will need to evaluate which tasks are suitable for AI to best implement it in their operations.
