Why AI Transformation Is Defining the CFO's Strategic Agenda
The CFO remit keeps expanding. Stewardship and reporting still matter, but the job now sits at the intersection of strategy, technology, talent, and execution. Confidence is back too. Deloitte's latest CFO Signals shows sentiment rebounded at the end of 2025, matching late-2024 highs-and the agenda for 2026 is clear: build real capability through AI and automation.
Based on a survey of 200 CFOs at North American companies with at least US$1bn in revenue, the priorities for the year ahead are practical and focused on outcomes. Deloitte's CFO Signals points to finance transformation, AI agents, customer behavior, talent, and dealmaking as the main themes.
Finance transformation moved from ambition to execution
Digital transformation of finance is now the top priority for 50% of CFOs, per Deloitte. The driver is simple: efficiency and productivity. Automation sits at the center-standardize processes, shorten cycles, and reduce manual work that slows decision-making.
This isn't just systems; it's people. Nearly half of CFOs say automating work to free employees for higher-value tasks is their number-one talent move. That means reskilling the team for AI, analytics, and product-like thinking in finance.
AI shifts from experimentation to expectation
AI has moved past the pilot phase. Eighty-seven percent of CFOs believe AI will be extremely or very important to finance operations in 2026. The case is made: faster closes, sharper forecasts, cleaner controls, and time back to focus on growth and cash.
Adoption is set to accelerate as tools mature and ROI becomes measurable. Treat AI as a core capability, not a side project.
Intelligent agents emerge as the catalyst for real change
More than half of CFOs (54%) rank integrating AI agents as a top transformation priority-above even data quality and access. The shift is from generic AI to embedded agents that execute tasks within workflows.
Start with high-volume, high-friction areas: reconciliations, AP/AR exception handling, management reporting, forecast variance analysis, and working capital monitoring. Put guardrails in place, set clear ownership, and measure cycle time and error rate improvements.
Customer behavior becomes a core finance concern
Forty-eight percent of CFOs expect shifts in customer preferences or demographics to have a major impact in 2026. That demands tighter coordination with product, sales, and marketing-paired with finance models that reflect how demand actually moves.
Expect pressure to support new payment options, consumption-based pricing, and different go-to-market motions. FP&A should integrate customer cohorts, churn drivers, and unit economics into the standard pack.
Cost pressure pushes CFOs to rethink talent from within
Cost management remains the top internal concern for nearly half of CFOs. The response is pragmatic: 49% plan to hire or promote from within to manage workforce costs while protecting institutional knowledge.
Make a "train-to-adopt" plan part of the budget. Upskill for AI, automation, data storytelling, and process design. Promote the people who can ship change.
M&A momentum builds as confidence returns
Dealmaking is back on the agenda. Sixty-three percent of CFOs report higher interest in M&A than a year ago. With improving financing conditions and stronger equity markets, inorganic growth looks attractive again.
The playbook: clean up the balance sheet, pre-wire diligence analytics, and keep an integration blueprint ready-especially for tech, finance data models, and talent retention.
What this means for CFOs
- Set a 12-month finance automation roadmap: close, reporting, payables/receivables, and FP&A. Tie each initiative to a measurable cycle-time or cost target.
- Appoint an AI product owner in finance to coordinate use cases, vendors, controls, and ROI tracking.
- Pilot 2-3 AI agents in production workflows. Start small, measure impact weekly, and scale what works.
- Fix data at the source. Standardize charts of accounts, master data, and policies before adding more tools.
- Refactor FP&A to include customer metrics: cohorts, conversion, churn, LTV/CAC, and pricing sensitivity.
- Adopt a promote-from-within plan: define skills, provide short-cycle training, and align incentives to adoption.
- Build an M&A readiness kit: target screens, synergy theses, diligence data room, and integration checklists.
- Report quarterly on transformation value: productivity gains, error reduction, cash impact, and growth enablement.
Bottom line: 2026 is the year to operationalize AI in finance. Keep it simple: pick the few workflows that move the P&L, deploy agents with guardrails, and prove value fast.
If you're building team capability for AI and automation in finance, explore these resources: AI tools for finance and AI courses by job.
Your membership also unlocks:
