The State of AI in Finance 2026: Key Findings, Tools, and How to Get Started -- Download Report

The State of AI in Finance 2026 report finds that 56% of finance leaders now use AI -- double the adoption rate seen in 2023. Yet finance still ranks last among all business functions in AI deployment. The report explains what's holding teams back and gives CFOs a clear roadmap to move from experimentation to scale.

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Key takeaways from the State of AI in Finance 2026

• AI adoption in finance has reached 56% -- doubled since 2023, but still the lowest of any business function

• 45% of finance teams remain in limited pilot mode; only 17% are using AI in core workflows

• 68% of CFOs say they've been slow to adopt because they don't know where to start

• ChatGPT leads with 35% of finance teams using it; specialised finance AI tools still lag

• Security concerns are declining thanks to enterprise tools like ChatGPT Enterprise, Copilot with EDP, and Gemini Enterprise

• Leading teams are building unified data cores and embedded AI workflows -- not just running isolated experiments

• CFOs should follow a clear 30/90/365-day roadmap to move from pilot to infrastructure

What does the State of AI in Finance 2026 report reveal?

The headline finding is that AI adoption in finance has reached the mainstream -- but most usage remains shallow. A General Atlantic poll found 45% of finance teams are still in "limited pilot" mode, while only 17% are actively using AI in their core workflows.Three structural themes emerge across the report:

• Finance lags every other function. Full workflow automation is already mainstream in engineering, marketing, and sales. Finance isn't there yet.

• The divide between tinkerers and integrators is widening. Teams that have moved beyond experimentation are already seeing lower costs, faster closes, and better business partnerships.

• 68% of CFOs say they've been slow to adopt AI because they don't know where to start. The report is designed to solve exactly that.

How are finance teams using AI today?

According to the report, the most common AI use cases in finance today include:

• Preparing financial presentations and board reports

• Meeting notes and workshop preparation

• Reporting assistance and data analysis

• Contract review and consistency checks

• Variance analysis and reconciliation

• Spend categorisation and forecasting

But the most advanced teams are going further. At OpenAI, an internal Contract Reader Bot extracts terms, applies ASC 606/IFRS 15 logic, and auto-generates journal entries -- allowing their finance team to operate with roughly 22% of the headcount of comparable tech firms. At Spendesk, AI-powered reconciliation runs continuously throughout the month, enabling a real-time close rather than a month-end scramble.

"AI moves finance from backward-looking reporting to augmented decision-making. Real-time data, cloud ERPs, and AI compress month-end into a continuous close." -- Axel Demazy, CEO, Spendesk

ChatGPT leads with 35% usage among finance teams. Specialised finance AI tools still lag behind, as CFOs test practical, low-risk use cases first before committing to purpose-built platforms.

What is holding finance teams back from adopting AI?

The report identifies four main barriers:

• Cumbersome close cycles -- finance teams are too busy closing to find time to build. Without protected time for experimentation, AI stays a side project.

• Fear of the unknown -- 68% of CFOs say they don't know where to start.

• Security and confidentiality concerns -- finance handles sensitive compensation, forecast, and board data. Enterprise tools (ChatGPT Enterprise, Copilot with EDP, Gemini Enterprise) resolve most of these concerns.

• Insufficient training -- few finance professionals have been formally trained in prompting, workflow automation, or model validation.

75% of HR leaders -- critical partners in managing one of finance's largest cost centres -- expect AI to handle more than half of their routine admin tasks by the end of 2026. (Source: Remote Workforce Report) The pressure to upskill and adopt is coming from every direction.

Which AI tools are CFOs and finance teams using most?

The report maps the tools finance teams are actively using today across five categories:

• ChatGPT Enterprise -- the go-to for research, analysis, reporting, memo writing, and agent-based automation

• Microsoft 365 Copilot -- two ready-built agents (Researcher and Analyst) allow CFOs to automate planning, variance analysis, and data visualisation without any coding

• Dust -- widely used for knowledge retrieval, internal Q&A, and connecting company data to AI agents

• Workflow automation platforms (Zapier, Make, n8n) -- essential for stitching AI tools together and enabling lightweight automation across teams

• FP&A and ERP-embedded AI -- many teams are underusing AI features already built into tools they pay for

"The main challenge isn't finding AI tools -- it's having too many. We replaced five separate AI note-taking tools with a native one built in ClickUp." -- Dan Zhang, CFO, ClickUp

What skills do finance teams need for AI adoption?

The report outlines a new finance skill set emerging across leading teams:Technical skills:

• LLM literacy (ChatGPT, Copilot, Gemini)

• Workflow automation and prompt engineering

• Data literacy and AI-driven analysis

• AI governance and compliance

Soft skills:

• Curiosity and willingness to experiment

• Cross-functional collaboration with engineering and data teams

• Ability to communicate AI outputs to non-technical stakeholders

• Willingness to automate your own role

"Soft skills like curiosity and rigour are timeless. But AI amplifies their importance." -- Mike Tsang, Finance Director, ARIA

Six real-world case studies from companies using AI in finance

The report features detailed case studies from:

• Spendesk -- real-time spend planning and continuous close

• OpenAI -- automating technical accounting and contract intelligence

• Adyen -- a unified Finance Data Core enabling AI at scale

• Zapier -- 98% employee AI adoption through mandates, not nudges

• ClickUp -- consolidating AI tools and embedding them directly into finance workflows

• Microsoft -- ready-to-use Copilot agents any CFO can deploy today

How can a CFO start adopting AI? A 30/90/365-day roadmap

First 30 days: scope and test

• Identify one high-friction workflow -- choose a manual, repetitive process with clear inputs and outputs (reconciliations, variance analysis, spend categorisation)

• Audit your existing tech stack -- assess AI features already embedded in your ERP, FP&A tools, and productivity software before buying anything new

• Start measuring beyond time saved -- track speed of decisions, forecast accuracy, error reduction, and stakeholder satisfaction from day one

Next 90 days: build structure

• Launch a 90-day automate-upskill-govern plan -- define which processes to automate, what skills to develop, and how AI use will be governed

• Establish AI champions -- identify curious, credible people close to the work and empower them to test, learn, and bridge finance with IT and data teams

• Create governance frameworks -- set clear rules for data usage, model validation, access controls, and human oversight

6 to 12 months: scale and embed

• Build a governed finance data core -- AI performance depends on data quality. Create a trusted foundation with clear ownership and standard definitions

• Redesign roles around AI capabilities -- as AI absorbs routine work, update role definitions, performance metrics, and career paths toward judgement and business partnership

• Scale what works -- standardise proven use cases across teams and regions. At this stage, AI moves from innovation to infrastructure

FAQ: AI in Finance

What is AI used for in finance?

AI is used in finance for contract analysis, reconciliation, reporting, variance analysis, spend categorisation, memo drafting, forecasting, and business partnering. The most advanced teams are also using AI agents for investor relations, scenario modelling, and knowledge retrieval.

How many finance teams are currently using AI?

56% of finance professionals report using AI in their work, up from 17% in 2023. However, only 17% are actively using AI in core finance workflows -- most usage remains limited to administrative tasks.

Which AI tools are most commonly used in finance teams?

ChatGPT leads with 35% usage among finance teams, followed by Gemini, Microsoft Copilot, and Dust. Workflow automation platforms like Zapier, Make, and n8n are also widely used to connect AI tools into end-to-end workflows.

What skills do finance professionals need to use AI effectively?

Finance professionals need a combination of LLM literacy, prompt engineering, workflow automation, and data literacy on the technical side -- alongside curiosity, cross-functional collaboration, and a willingness to automate their own roles on the soft skills side.

How can a CFO start adopting AI without knowing where to begin?

Start with one high-friction, manual workflow. Audit existing tools before buying new ones. Measure impact beyond time saved from day one. The report includes a full 30/90/365-day roadmap to guide the process.

Why does finance lag behind other functions in AI adoption?

Finance teams cite four main barriers: cumbersome close cycles that leave no time for experimentation, uncertainty about where to start, security and confidentiality concerns, and insufficient training in AI tools and workflows.

👉 Download the full State of AI in Finance 2026 report here

50 pages. 14 finance experts. Free.