While finance leaders deal with market volatility and economic uncertainty, investment in AI continues at a torrid pace. Underneath the chaos, adoption accelerates. Use cases progress. Financial benefits slowly accrue.
Stanford University’s Institute for Human-Centered AI recently released its 2025 AI Index Report and survey.
The annual report compiles information on AI model development, business use, ethical issues, government policy changes, expected economic effects of AI and much more.
We pulled out some key facts, trends and takeaways for finance leaders, who will be key to developing AI use cases for finance and building a pathway for it inside organizations.
Big dollars. In 2024, U.S. private AI investment grew to $109.1 billion—Generative AI saw powerful momentum, attracting $33.9 billion globally, a nearly 19 percent increase from 2023. Globally, corporate AI investment reached $252.3 billion. AI business usage is also accelerating: 78 percent of organizations reported using AI in 2024, up from 55 percent the year before.
AI model growth. The United States continues to be the leading source of AI, with institutions producing 40 notable AI models last year. And nearly 90 percent came from industry. “AI models get increasingly bigger, more computationally demanding and more energy-intensive,” says the Stanford report. Model scale is growing rapidly. “Training compute doubles every five months, datasets every eight and power use annually.”
Business deployments. The most common application is marketing strategy content support (27 percent), followed by knowledge management (19 percent), personalization (19 percent) and design development (14%). Most of the leading reported use cases are within the marketing and sales function. Survey respondents who reported using generative AI in at least one business function more than doubled—from 33 percent in 2023 to 71 percent in 2024.
Flawed reasoning. “Complex reasoning remains a problem” for large language models, says the report. These “systems still cannot reliably solve problems for which provably correct solutions can be found using logical reasoning, such as arithmetic and planning, especially on instances larger than those they were trained on.” The report says unreliability impacts these systems’ “suitability in high-risk applications.”
Financial impacts. About half (49 percent) of respondents whose organizations use analytical AI in service operations report cost savings, followed by supply chain management (43 percent) and software engineering (41 percent). According to the Stanford report, most of them report cost savings of less than 10%. Regarding revenue, “71 percent of respondents using AI in marketing and sales report revenue gains, 63 percent in supply chain management and 57 percent in service operations.” The most common level of revenue increase was less than 5 percent.
Societal sentiment. “AI is seen as a time saver and entertainment booster, but doubts remain on its economic impact.” Few of the people surveyed are confident in its health or economic benefits. Only 38 percent think AI will improve health. A little more than one-third (36 percent) believe AI will improve the national economy, 31 percent see a positive impact on the job market and 37 percent think it will enhance their own jobs.
This article first appeared in CFO Leadership’s Finance & Accounting Technology Briefing.
