State of AI in Finance: 10 Facts About What is Really Happening

The state of AI in finance is moving from hype to reality. Gartner predicts that by 2026, 90% of finance teams will use at least one AI-enabled tool, while BCG reports 75% of CFOs expect agentic AI to be routine by 2028.

The future of AI in finance is not about replacing accountants but amplifying them, with generative AI drafting reports, predictive models enhancing forecasting, and partnerships with vendors raising success rates. For CFOs, the challenge is clear: invest in data, skills, and governance today to capture AI’s long-term value.

The State of AI in Finance – What is Really Happening?

The hype around AI in finance is impossible to ignore. From Generative AI (GenAI) in finance producing board-ready reports to automation cutting days off the month-end close, finance leaders everywhere are exploring how to use AI responsibly and effectively. But beyond the buzz, what is actually happening inside finance functions?

Here are 10 key facts drawn from leading studies that reveal the true state of AI in the finance industry today, and what it means for CFOs, FP&A teams, and accountants.

1. Generative AI is Entering Day-to-Day Finance

GenAI is one of the most disruptive technologies reshaping the finance function. According to EY’s 2024 research, executives are experimenting with using GenAI to summarize financial performance, prepare board-ready materials, and generate first drafts of investor reports.

While still in its early days, these applications show promise. GenAI is particularly valuable for reducing time spent on low-value tasks such as commentary drafting. The challenge lies in balancing speed with risk: bias, accuracy, and explainability remain key concerns. Yet, finance leaders who responsibly adopt GenAI in finance stand to dramatically reduce reporting cycles and improve communication.

2. CFOs Report Productivity Gains with AI

The narrative that AI will displace finance jobs doesn’t align with reality, at least not yet. A 2025 survey revealed that 70% of CFOs said their teams are working faster and delivering more thanks to AI. Interestingly, 88% of leaders reported that AI adoption did not result in headcount reductions.

Instead of replacing roles, AI is allowing CFOs to redeploy talent to higher-value activities such as scenario planning and strategic analysis. This trend is particularly visible in mid-market companies with $50M–$100M revenue, where nearly one-third report enterprise-wide AI deployments. The result is a finance function that delivers more insights without expanding headcount.

3. AI Adoption is Becoming Mainstream

A recent Gartner survey shows how quickly adoption is scaling across finance. In 2023, only 37% of finance teams reported using AI. That figure climbed to 58% by 2024, and Gartner projects that 90% of finance functions will deploy at least one AI-enabled solution by 2026.

This rapid rise demonstrates that AI is no longer reserved for early adopters or innovation labs. By 2026, AI-enabled forecasting, anomaly detection, and reconciliations will be common across most finance functions. For CFOs, this means AI is shifting from a competitive advantage to a basic expectation. Teams that don’t act quickly may soon be left behind.

4. Agentic AI Will Soon Be Routine

A report indicates that 75% of finance leaders anticipate that agentic AI will be routine by 2028. Already, 17% of finance teams are deploying generative agents, although adoption estimates vary by source. Agentic AI differs from traditional automation in that it can independently initiate, manage, and complete financial tasks.

Much like how cloud computing went from optional to ubiquitous, agentic AI will quickly move from pilot projects to core operations. Finance teams that build literacy now will be prepared to integrate autonomous AI into forecasting, reporting, and compliance in the years ahead.

5. Partnerships Boost AI Success Rates

Finance leaders are realizing they don’t need to build everything from scratch. Partnering with vendors increases AI success rates by about 5%. This is consistent with Forrester’s warning that 75% of in-house AI agent projects fail due to technical complexity.

The lesson? Partnering with specialized vendors allows finance teams to access scalable, proven AI applications while reserving internal builds for high-differentiation use cases. For CFOs, this hybrid approach accelerates time-to-value and reduces risk.

6. Data Quality Remains the Weakest Link

While AI tools are becoming more advanced, their success hinges on clean, accessible data. A survey found that 67% of senior executives cite inadequate data foundations as the biggest barrier to scaling AI initiatives. Moreover, 68% of organizations with siloed data reported revenue losses due to failed or delayed AI projects.

For finance teams, the implications are clear. Without integrated data systems, AI forecasts and analyses risk being unreliable. CFOs who prioritize unifying their organization’s financial data across ERP, FP&A, and operational systems will unlock the full potential of AI applications in finance, while those who ignore the problem may see their investments stall at proof-of-concept.

7. ROI is Real but Uneven

The return on investment from AI is evident, but not consistent across organizations. According to a 2025 report, about 20% of finance teams report ROI above 20% from AI initiatives, while the median return is closer to 10%. However, one-third of executives admitted seeing limited or no gains to date.

The gap reflects differences in strategy. High performers embed AI into broader finance transformation programs and carefully sequence use cases. Struggling teams often treat AI as isolated experiments. For CFOs, the lesson is clear: AI must be tied to business strategy, not deployed as standalone pilots.

8. AI Skills Are Now a Hiring Priority

The talent conversation in finance is shifting from “do we need more accountants?” to “do we have the right AI skills?” According to a survey, 85% of finance leaders prioritize AI fluency in recruitment, with 11% calling it essential.

This shift underscores how AI maturity is not just about tools but also about people. CFOs are increasingly building teams with data science, AI, and technology literacy to maximize ROI. Upskilling existing staff is also critical—leaders point to AI training as a top driver of success in finance transformations.

9. Leading Teams Run Multiple Use Cases at Once

One common feature of successful AI adopters is scale. Research shows that leading finance organizations typically run 10 to 11 AI use cases simultaneously, combining proof-of-concept projects with solutions already in production.

By contrast, average teams run far fewer use cases, often limiting the impact of their AI investments. Deploying multiple applications, such as forecasting, anomaly detection, and expense optimization, compounds benefits and creates synergies across the finance function.

10. Governance is the Overlooked Success Factor

Strong governance is emerging as a critical success factor for AI adoption. In a 2024 study, it was found that only 18% of companies have established comprehensive AI governance committees, even though organizations with formal oversight saw stronger financial performance.

Without governance, risks such as compliance failures, model bias, and unreliable reporting multiply. Finance leaders who document integration points, involve legal teams early, and test workflows thoroughly are far better positioned to scale AI responsibly.

The Reality of AI in Finance

The use of AI in finance is no longer experimental, it’s already becoming mainstream. Adoption is spreading rapidly, agentic AI is on the horizon, and ROI is possible but uneven. At the same time, challenges like poor data foundations and a lack of governance remain major bottlenecks.

The bottom line? The future of AI in finance is not about replacement, but augmentation. For CFOs and finance teams, the challenge is clear: leverage AI responsibly, build governance frameworks, and invest in skills that turn technology into a long-term strategic advantage.