Deloitte's second annual "Finance Trends 2027" report, based on a survey of 1,434 finance leaders across 26 countries, finds CFOs taking direct ownership of AI investment decisions, governance, and cost control as organizations scale enterprise technology deployments. The stakes are concrete: 43% of finance leaders now prioritize AI and advanced technology to automate operations through fiscal year 2027, and more than half are leading cross-enterprise capital allocation for those initiatives.
The survey, conducted in spring 2026 with CFOs and senior finance executives at companies with at least US$1 billion in revenue, shows the CFO mandate expanding well beyond traditional financial stewardship. Finance leaders are now deciding where the enterprise places technology bets, how AI is governed and funded, and how value gets measured.
The expanding finance mandate
Fifty-four percent of finance leaders now lead enterprise AI and technology capital allocation decisions. Another 48% oversee AI trust, including the reliability, accuracy, and explainability of AI outputs, while an equal share manage AI and technology spending and cost controls. Among those who have taken on these responsibilities, more than two-thirds did so within the past three years.
To help their organizations move faster, 46% of finance leaders are prioritizing infrastructure modernization and data unification. Forty-three percent are prioritizing changes to the finance operating model itself. This shift reflects a broader pattern: finance increasingly serves as an integrator connecting strategy, investment, risk, and performance.
"The CFO mandate is expanding from financial stewardship to helping shape how the enterprise invests in, governs and creates value from AI and technology," said Ed Hardy, U.S. Finance Services leader at Deloitte. "Finance leaders bring the measurement, discipline and enterprise perspective needed to turn AI ambition into responsible, scalable growth."
For finance professionals tracking these developments, AI for Finance resources cover the core areas where CFOs are now expected to lead - capital allocation, governance, and value measurement.
Human oversight limits agentic AI adoption
Nearly all finance leaders - 95% - are comfortable with agentic workflows in at least some finance activities. But comfort drops sharply when autonomy increases. While 77% accept agentic solutions that move beyond recommendations into some level of autonomy, only 14% support full autonomy for critical decisions.
The gap between ambition and readiness is measurable. Forty-two percent of finance leaders say their agentic AI ambitions exceed current capabilities, citing the need for stronger controls before expanding adoption. Among that group, 41% identify employee trust in the quality of AI outputs as a leading barrier.
Mo Vakili, Finance Transformation National Offering Portfolio leader at Deloitte, put it directly: "Finance leaders clearly see the potential of agentic AI, but ambition alone will not drive value at scale. Success will depend on trusted data, strong controls, human oversight and greater visibility into increasingly complex costs."
CFOs looking to build those capabilities can explore an AI Learning Path for CFOs that addresses governance, oversight, and investment decisions.
Cost management gets harder as AI scales
Sixty percent of finance leaders say they will need more sophisticated AI cost-management practices through 2027. Those preparing for this shift are already further along: 64% have fully embedded AI productivity tools in finance, and 38% have FinOps capabilities, compared with 51% and 25% respectively among those maintaining current practices.
The obstacles are familiar but persistent. Regulatory uncertainty (20%), complex cloud and vendor billing (19%), and difficulty integrating usage data with finance systems (15%) remain the leading challenges. None of these are new problems, but they compound as AI spending grows.
Technology sovereignty reshapes investment decisions
Eighty-four percent of finance leaders expect technology sovereignty - organizational or national independence and ownership of data, vendors, and supply chains - to significantly affect technology-related capital allocation through 2027. The expected changes include material shifts in technology platform investments (55%), physical assets (16%), and partnerships, M&A, or legal entities (13%).
Sixty-three percent of finance leaders view technology sovereignty as a strategic differentiator that can strengthen resilience and create long-term value. This is not a defensive posture; it is becoming an investment criterion.
Funding models show signs of change
While 66% of finance leaders report their organizations primarily use an internally driven, measurement-led approval process, evaluation methods are shifting. Among those respondents, 27% use stage-gate funding tied to defined milestones, 25% require quantified ROI and a formal business case, and 23% rely on executive or board mandates without a precise process for measuring results.
Funding sources are also diversifying. Private equity, sovereign wealth, and institutional capital account for 30% of funding. Internal capital or balance-sheet funding represents 29%. Managed-services arrangements with shared efficiency targets make up 25%, and alternative co-investment structures round out the mix.
Why this matters for finance professionals
The survey data points to a specific expectation: finance leaders who can combine measurement discipline with AI governance will control more of the enterprise technology agenda. That means building skills in AI cost modeling, agentic workflow oversight, and technology sovereignty risk assessment. The 42% of finance leaders who admit their ambitions outpace their capabilities are not waiting for permission to catch up - they are actively rebuilding controls, funding models, and operating structures to close the gap by 2027.
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