Finance leaders see AI as the top trend - but most teams aren't ready
AI sits at the top of finance leaders' agendas. In a new AICPA and CIMA survey, 88% of respondents said AI will be the most transformative tech trend over the next 12-24 months. Yet just 8% feel their organisations are "very well prepared" to manage it.
That readiness gap is widening as expectations rise. Generative AI is now the single biggest skills gap for 2025 (56%). Broader IT/tech skills have jumped to the front of the queue too (47%), up from 20% in 2021 - a clear signal that finance is shifting from support to value creation through technology.
What's holding teams back
- Human capital, skills, and talent constraints: 50%
- Safety and security concerns: 47%
- Questions about tech maturity: 42%
Productivity is also taking a hit. Lack of skills (41%) and low motivation (37%) top the list, followed by incompatible systems and poor coordination in tech implementation (both 32%).
The skills picture is bigger than gen AI
- Broader technology skills (AI, big data, cloud, IoT, robotics): 37%
- Data and analytics: 36%
- Communication, influencing, and critical thinking: 33%
- Business partnering: 32%
The takeaway: finance needs a blended capability stack - technical literacy, data fluency, and stronger human skills that drive adoption and impact.
How leaders are responding
- Internal training programmes: 62%
- External training: 45%
- Hiring new talent: 35%
On-the-job learning ranked as the most effective upskilling approach (61%). It's flexible, hands-on, and evolves through experimentation - exactly what AI adoption demands. Hiring remains useful for jump-starting capability, especially where internal depth is thin.
Practical playbook for the next 90 days
- Define the use cases that matter: close, reporting, forecasting, working capital, fraud, tax, and internal audit. Pick two with clear ROI and controllable risk.
- Set guardrails early: data access, review thresholds, model provenance, and documentation standards. Use established frameworks such as the NIST AI Risk Management Framework.
- Run paired pilots: one generative use case (policy drafting, commentary, reconciliations) and one predictive/analytics use case (variance drivers, anomaly detection).
- Build a skill map: role-by-role proficiency across gen AI, analytics, data hygiene, and business partnering. Tie training to projects, not theory.
- Create a small enablement pod: finance lead, data/IT partner, risk/security, and an internal trainer. Their job is unblocking, standardising, and measuring impact.
Where to upskill first
- Gen AI for finance workflows: drafting narratives, policy checks, reconciliations, vendor/customer queries.
- Data and analytics: SQL basics, data quality, joining datasets, and building repeatable analyses.
- Tool literacy: spreadsheets with AI features, BI dashboards, workflow automation.
- Human skills: framing problems, communicating assumptions, influencing stakeholders, and review discipline.
Governance that keeps pace
Security and safety concerns are valid - and manageable. Set clear approval paths, define sensitive data handling, and require human review for material outputs. Track model usage, exceptions, and accuracy drift. Small controls, consistently applied, beat big policies that never land.
What this means for CFOs
The survey signals opportunity and risk. AI can lift speed and quality across planning, reporting, audit, tax, and shared services. But the bottleneck is skills, not software. Move training closer to the work, measure adoption in live processes, and keep a tight loop between finance, IT, and risk.
As Andrew Harding, FCMA, CGMA, noted, the pace of new tools has changed what finance teams can do. The gap is no longer awareness - it's action.
Resources
- Association overview: AICPA & CIMA
- Role-based upskilling paths for finance: Complete AI Training - Courses by Job
- Curated AI tools for finance teams: AI Tools for Finance
Methodology note: AICPA and CIMA surveyed 1,400+ senior finance and accounting professionals globally in August-September. Percentages reflect respondent selections in the 2025 Future-Ready Finance report.
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