The Deloitte FinanceAI Nerve Center surveyed finance leaders from 80 Fortune 500 companies and found that artificial intelligence (AI) adoption within finance functions has accelerated noticeably, though most organizations remain at the early stages of exploiting its potential. Nearly 48 percent of respondents ranked AI among their top strategic priorities.
Key figures from the survey:
- 65 percent of implemented AI use cases are now generative and agentic (agent‑based) solutions.
- Traditional predictive and machine learning‑based systems account for 29 percent.
- More than 83 percent of organizations use some form of user‑interactive AI productivity tool.
Why generative and agentic AI are gaining ground
Companies increasingly seek solutions that go beyond analytics and forecasting to support more complex tasks and prepare decision‑making more effectively. As a result, AI’s role in finance is moving past simple automation toward broader operational and strategic support.
"AI in finance is no longer just a future promise; it is increasingly part of day‑to‑day operations. Generative and agent‑based systems can advance not only process automation but also help finance teams support decision‑making faster, more accurately and in a way that is more relevant to the business," said Rédei Attila, senior manager on the Finance Transformation team.
Adoption pace and organizational stance
Despite faster adoption, the majority of respondents take a cautious approach: 63 percent describe their AI adoption level as either followers or conservative. Eleven percent identify as leaders, and 25 percent as early adopters.
Top challenges cited by respondents:
- 73 percent: lack of appropriate skills (talent shortage)
- 63 percent: insufficient data quality
- 57 percent: limited resources
These results underscore that successful AI deployment depends not only on technology but also on people, data and operating models.
From efficiency to growth enablement
While improving processes and reducing costs remain primary objectives of AI projects, there is growing attention to use cases that directly support revenue growth and business expansion. Respondents reported a 49 percent increase in emphasis on growth‑oriented opportunities compared with six months earlier.
"AI implementations in finance are still at an early stage, but momentum is clearly strengthening. The next step is to identify use cases that can quickly demonstrate business value. Success lies not in trying to change everything at once, but in building trust through targeted, measurable and gradually scalable solutions," added Lukács Eszter, director of the Finance Transformation team at Deloitte Hungary.
Planned investments and delivery models
Respondents expect meaningful increases in AI spending for finance over the next few years:
- 84 percent anticipate spending more than $1 million on AI developments related to the finance function within the next three years.
- 41 percent plan to invest at least $4 million.
Implementation is frequently hybrid: the survey found that 79 percent of AI implementations are carried out through collaboration between internal teams and external partners.
Implications for operating models
The path of AI adoption in finance runs from productivity tools to complex agentic systems. Successful implementation will require aligning:
- improvements in data quality,
- upskilling of staff,
- deployment of well‑scoped AI solutions tied to business objectives.
Deloitte continues to study how emerging technologies reshape corporate decision‑making and the role of finance functions. The survey’s findings indicate that AI will play an increasingly central role in the future of finance operations, but realizing broad business value will require substantial investment and organizational development.
