UNLOCKED The finance brief · Issue 2

The Real State of AI in the CFO Office

What every CFO needs to know

  • 30sources, every number traced
  • 13,000+respondents across the surveys
  • 8chapters, one theme each
    Take the scan

    Actuals Research, October 2026

    In this issue

    Contents

    8 chapters. Each opens with the takeaways, followed by the full interactive story. Start anywhere.

    Chapter 01 · Adoption

    Most finance teams use AI. Few see a big impact yet

    With Actuals Research, from Gartner, Deloitte, KPMG and IBM

    Gartner surveyed finance teams on AI use: 37% used it in 2023, 58% in 2024 and 59% in 2025. This chapter shows why using AI and getting something out of it are different things.

    4 lessons below

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    1. 1

      Adoption has stalled.

      The share of finance teams using AI went from 37% in 2023 to 58% in 2024. Then it rose just 1 point, to 59% in 2025.

      Gartner, November 2025

    2. 2

      Most teams saw low or moderate impact at first.

      91% of finance teams that use AI saw low or moderate impact at first.

      Gartner, November 2025

    3. 3

      The forecast looks far off.

      In 2024 Gartner predicted that 90% of finance functions would use at least one AI solution by 2026. A year before that deadline, Gartner's 2025 survey found 59%.

      Gartner, September 2024 and November 2025

    4. 4

      "Using AI" means very different things.

      KPMG reports 75% active AI use in large finance teams, and Deloitte finds 63% with AI fully deployed. IBM finds only 6% of finance organisations operating at what it calls a transformation-ready level.

      KPMG, May 2026; Deloitte, October 2025; IBM, September 2026

    59%

    of finance functions use AI, up 1 point in a year

    Gartner, 2025
    91%

    of finance teams using AI saw low or moderate impact at first

    Gartner, 2025
    38%

    of Dutch finance departments use AI, a lower share than in the US and China

    KPMG Netherlands, 2025

    In 2023, 37% of finance functions used AI. A year later it was 58%. 21 points in a single year.

    Then 2025: 59%. 1 point in a whole year. In Gartner's words, momentum has slowed.

    In 2024 Gartner predicted that 90% of finance functions would use at least one AI solution by 2026. A year before that deadline, the measured number is 31 points below it.

    And of the teams that do use it, 91 out of 100 saw low or moderate impact at first.

    Finance functions using AIPrediction

    0 of 100 saw low or moderate impact

    Every survey counts "using AI" differently

    KPMG reports 75% active AI use in finance among companies above $250 million in revenue. Deloitte finds 63% of large finance teams have AI fully deployed. IBM, asking 1,500 CFOs, finds that only 6% of finance organisations run at a transformation-ready level.

    The spread tells you more than any single number. "Using AI" can mean a chatbot licence for the team, or a month-end close that runs differently. Our guess: most companies are closer to the chatbot licence.

    The Dutch picture. In KPMG's survey, 38% of Dutch finance departments used AI and 17% had generative AI in place, behind the US and China. Among 100 Dutch CFOs, about 9 in 10 say AI supports at most a quarter of their strategic decisions.

    What this means for you

    The question to ask your team: what changed in your numbers because of AI?

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    Chapter 02 · Money and ROI

    Having AI is not the same as making money from it

    With Actuals Research, from Deloitte, BCG, Gartner and KPMG

    Deloitte asked 1,326 finance leaders at large companies: 63% have AI fully deployed, 21% see clear and measurable value. This chapter shows where the money goes and why the return lags.

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    1. 1

      Few can show what AI brings in.

      63% of large finance teams have AI fully deployed. 21% have it deployed and say they already see clear, measurable value. 14% got that far and also have AI agents at work.

      Deloitte, October 2025

    2. 2

      The typical return is half the target.

      A typical finance team gets 10% ROI from AI, while many aim for 20%.

      BCG, June 2025

    3. 3

      More CFOs aim AI at productivity than at better decisions.

      45% of CFOs say their AI investments lean toward productivity, 20% toward decision quality.

      Gartner, July 2026

    4. 4

      The bets are still small.

      47% of CFOs put just 1% to 5% of their finance technology budget into AI.

      Gartner, February 2026

    21%

    of large finance teams see clear, measurable value from AI

    Deloitte, 2025
    10%

    median ROI from AI in finance, against a 20% target

    BCG, 2025
    71%

    say AI meets or beats their ROI expectations (self-reported)

    KPMG, 2026

    Deloitte asked 1,326 finance leaders at companies above $1 billion. 63% have AI fully deployed and in active use.

    Only 21% have it deployed and already see clear, measurable value.

    And 14% got that far and also put AI agents to work inside the finance function.

    BCG asked about the return. A typical finance team gets 10% ROI from AI, against the 20% many of them are aiming for.

    One likely reason: much of the money goes to doing the same work faster. 45% of CFOs say their AI investments lean toward productivity, 20% toward better decisions.

    And the bets are small. 47% put just 1% to 5% of their finance technology budget into AI.

    Large finance teams
    0%Fully deployed
    0%Clear, measurable value
    0%Plus agents at work
    0%lean toward productivity
    0%lean toward decision quality

    What CFOs say their AI money is for

    0%finance tech budget100%

    0%

    spend 1% to 5% of it on AI

    The counterpoint

    71%

    of finance leaders say AI meets or beats their ROI expectations

    KPMG's 2026 survey of 1,013 finance leaders sounds a lot happier. Read it next to the others: these are self-reported results against the teams' own expectations, and KPMG also sells AI assurance.

    Handle with careThe number everyone quotes

    95%

    "of organisations are getting zero return" from generative AI

    The MIT NANDA report behind it rests on interviews with 52 organisations, 153 survey responses and a review of 300+ public AI initiatives, calls itself preliminary and is not about finance. Worth hearing as a signal, but too thin for your board deck.

    The Dutch picture. More than 80% of Dutch organisations plan to spend less than a quarter of their technology and digital budget on AI, according to Deloitte's autumn 2025 survey of 100 CFOs.

    What this means for you

    Treat AI like any other investment: one business problem, one number to move, one owner. As Gartner puts it about CFOs: "They must not mistake activity for impact."

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    Chapter 03 · Data

    AI runs on numbers your team still checks by hand

    With Actuals Research, from Gartner, EY, FP&A Trends, Adyen and Workiva

    Gartner expects that through 2026, companies will abandon 60% of AI projects that lack AI-ready data. This chapter shows why the problem starts before the ERP, in payouts, fees and refunds.

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    1. 1

      Money runs through too many pipes.

      A large company uses 12 payment providers on average: 6 for pay-ins and 6 for payouts. It also has more than 40 bank accounts.

      Adyen and BCG survey (vendor), January 2026

    2. 2

      Finance still spends much of its time checking data.

      FP&A teams spend 46% of their time collecting and validating data. And 45% still plan mainly in spreadsheets.

      FP&A Trends, 2025

    3. 3

      For most CFOs, data quality is a hurdle.

      61% of CFOs name data quality as a problem when they try to fund AI.

      EY, June 2026

    4. 4

      Few trust their data enough.

      Only 11% of executives in finance, risk and sustainability believe their data is good enough for AI.

      Workiva survey (vendor), August 2026

    60%

    of AI projects without AI-ready data expected to be abandoned through 2026

    Gartner prediction, 2025
    61%

    of CFOs name data quality as a hurdle for AI

    EY, 2026
    12

    payment providers on average at a large company

    Adyen and BCG (vendor), 2026

    A large company runs its money through 12 payment providers on average: 6 for pay-ins, 6 for payouts. Plus more than 40 bank accounts.

    Every one of them settles in its own format, with its own fees, refunds and chargebacks. Treasury teams spend more than 20% of their time on pay-ins and payouts alone.

    FP&A teams spend 46% of their time collecting and validating data. And 45% still plan mainly in spreadsheets.

    So when CFOs try to fund AI, data is a common hurdle: 61% name data quality as a problem.

    Only 11% of executives in finance, risk and sustainability believe their data is good enough for AI.

    Where the money flowsVendor survey

    0%of FP&A time goes to collecting and checking data

    0%still plan mainly in spreadsheets

    0%

    of 1,610 CFOs name data quality as a hurdle for AI investment

    Gartner's warning is about the data

    Gartner expects companies to abandon 60% of AI projects that are not supported by AI-ready data, through 2026. In the same study, 63% of organisations either lack the right data management practices for AI or are not sure they have them.

    For a high-volume business, the problem starts before the ERP. Payouts arrive net of fees, refunds land weeks later, a chargeback reverses a sale from last quarter. If that layer is not reconciled at the source, every AI tool on top of it works with numbers nobody would sign off on.

    What this means for you

    Fix the transaction layer under your ERP first, and every AI use case after it gets cheaper and safer.

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    Chapter 04 · Where it works

    The boring work pays back first

    With Actuals Research, from Gartner, Stanford, MIT and BCG

    Gartner finds that the most common uses of AI in finance are knowledge management, accounts payable and anomaly detection. This chapter shows where the proof is, and where the experts disagree.

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    1. 1

      The most common use cases are the plain ones.

      Among finance teams that use AI, 49% use it for knowledge management. Next come accounts payable (37%) and error and anomaly detection (34%).

      Gartner, November 2025

    2. 2

      Quick wins pay back within a year.

      3 use cases pay back within 9 to 10 months: data extraction, AP and AR automation, and report creation.

      Gartner, September 2026

    3. 3

      In one field study, the close was more than a week shorter with AI.

      In field data from 79 small and mid-sized firms, those that used AI closed the month 7.5 days sooner.

      Stanford GSB and MIT Sloan, 2025

    4. 4

      On forecasting, the experts disagree.

      BCG ranks forecasting close behind risk management for ROI. Gartner ranks forecasting and insight generation among the weakest use cases.

      BCG, June 2025; Gartner, May 2026

    7.5 days

    sooner monthly close at firms that used AI, in data from 79 small and mid-sized firms

    Stanford GSB and MIT Sloan, 2025
    30%

    faster close by 2028 with AI built into cloud ERP, Gartner predicts

    Gartner prediction, 2026

    Finance teams use AI most for knowledge management (49%), accounts payable automation (37%) and error and anomaly detection (34%).

    The quick wins pay back fast. Data extraction, AP and AR automation and report creation return their investment within 9 to 10 months.

    The hardest evidence comes from a field study by Stanford and MIT. In data from 79 small and mid-sized firms, those that used AI closed the month 7.5 days sooner.

    On forecasting, the experts disagree. BCG ranks it near the top for ROI. Gartner ranks forecasting and insight generation among the weakest use cases.

    Gartner expects AI inside cloud ERP to make the close 30% faster by 2028. Note the word: expects.

    Top use cases among adoptersPrediction
    Knowledge management0%
    Accounts payable automation0%
    Error and anomaly detection0%

    Months until data extraction, AP/AR automation and report creation pay back

    0

    days sooner monthly close

    BCG, 2025Forecasting

    "ranks close behind" risk management, the highest-ROI use case

    ▲
    vs
    Gartner, 2026Forecasting

    among the lowest-rated finance AI use cases

    ▼

    0%

    faster financial close by 2028, Gartner predicts

    What this means for you

    Start where the work is repetitive, the rules are clear and the volume is high. That is where AI has a track record, and where it frees up the people you need for the harder questions.

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    Chapter 05 · Where to start

    Start where the work repeats

    With Actuals Research, with Gartner, FP&A Trends and BCG

    Not sure where AI belongs in your finance team? We put 10 use cases on one map of reward, effort and risk: our reading of the evidence in this issue. Move the slider to see what changes when your data is less clean.

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    1. 1

      Start with work that repeats.

      Gartner finds the fastest payback, within 9 to 10 months, in data extraction, AP and AR automation and report creation.

      Gartner, September 2026

    2. 2

      Fix the transaction data before it reaches your ERP.

      FP&A teams spend 46% of their time collecting and validating data. Reconcile payouts, fees and refunds at the source before AI builds on them.

      FP&A Trends, 2025; Actuals Research

    3. 3

      Let AI watch for errors and anomalies.

      34% of finance teams that use AI apply it to error and anomaly detection. BCG ranks the wider field of risk management highest for ROI.

      Gartner, November 2025; BCG, June 2025

    4. 4

      Hold off on agents until you trust your data.

      Gartner expects over 40% of agentic AI projects to be cancelled by the end of 2027, because of cost, unclear value and weak risk controls. Agents on data you do not trust add to that risk.

      Gartner prediction, June 2025

    9 to 10 months

    payback on extraction, AP and AR automation and report creation

    Gartner, 2026
    10 use cases

    on one map of reward, effort and risk

    Actuals Research
    05 · Where to start

    Where to start with AI, and where not yet

    Not sure where AI belongs in your finance team? Put every idea on the same three scales: what it returns, what it takes, and what can go wrong. This map is our reading of the evidence in this report. Click any bubble to see why it sits there.

    Start here
    Big bets
    Nice to have
    Not yet
    Effort →Reward →
    Not at allFully
    0start now
    0big bets
    0not yet
    Low risk Medium risk High risk Bubble size: how much it depends on clean transaction data

    Do now

    1. Automate invoice capture and APThe clearest payback in the data: 9 to 10 months.
    2. Reconcile payments before they hit the ERPPSP payouts, fees, refunds and chargebacks matched at the source. It is the base under every other use case.
    3. Put anomaly detection on high-volume flowsOne of the three most used cases, and BCG ranks risk management highest for ROI.
    4. Match incoming cash in ARAnother 9-to-10-month quick win, once your payment data is reconciled.

    Not yet

    1. Autonomous agents on data you don't trustGartner expects more than 40% of agentic AI projects to be cancelled by the end of 2027.
    2. AI-written numbers straight to the board26% have already seen AI errors reach the board or the outside world.
    3. Forecasting on unreconciled actualsA forecast is only as good as the actuals underneath. Even the experts disagree on its ROI.
    4. Consumer credit decisions without an AI Act planHigh-risk obligations for creditworthiness checks on individuals apply from 2 December 2027.

    Self-check

    How many of these are true for your team?

    Tick what applies.

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    Chapter 06 · Agents

    Agents need a ledger you would sign off on

    With Actuals Research, from Deloitte, KPMG and Gartner

    AI agents are on the 2026 agenda of more than half of CFOs at large North American companies. Deloitte finds them working, with clear value, in 14% of large finance teams. This chapter shows why finance has heard this promise before.

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    1. 1

      More than half of large-company CFOs plan for agents.

      54% of CFOs at North American companies with $1bn or more in revenue say integrating AI agents into finance is a transformation priority for 2026.

      Deloitte, January 2026

    2. 2

      Few pass Deloitte's stricter test.

      14% of large finance teams have AI fully deployed, already see clear value and have agents integrated.

      Deloitte, October 2025

    3. 3

      Gartner expects many agent projects to stop.

      Gartner expects over 40% of agentic AI projects to be cancelled by the end of 2027.

      Gartner prediction, June 2025

    4. 4

      Finance has heard this before.

      In 2022, 55% of finance functions aimed for a touchless close by 2025. In 2026, 63% of finance leaders said AI implementation in 2025 went slower than expected.

      Gartner, September 2022 and May 2026

    14%

    of large finance teams have agents working with clear value

    Deloitte, 2025
    over 40%

    of agentic AI projects expected to be cancelled by the end of 2027

    Gartner prediction, 2025

    54% of CFOs at North American companies with $1bn or more in revenue say integrating AI agents into finance is a transformation priority for 2026.

    KPMG asked where large finance teams stand. 97% of large finance teams say they have started with agents, and 12% say they already run multi-agent systems. All self-reported.

    Deloitte's stricter test: AI fully deployed, clear value already delivered, and agents integrated. 14% pass.

    Gartner expects more than 40% of agentic AI projects to be cancelled by the end of 2027, because of costs, unclear value or weak risk controls.

    We have been here before. In 2022, 55% of finance functions aimed for a touchless close by 2025. In 2026, 63% of finance leaders said AI in 2025 went slower than expected.

    AI agents in financePrediction

    0% call agents a 2026 priority

    0 of 100 have agents working, with clear value

    Over 4 in 10 agentic AI projects expected to be cancelled by end of 2027

    2022 · the promise0%

    aimed for a touchless close by 2025

    2025 · the reality0%

    said AI went slower than expected

    What this means for you

    An agent acts on whatever data it is given, at machine speed. Give it a ledger you would sign off on, one clear task and a person who reviews the exceptions.

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    Chapter 07 · People

    Your team sets the pace more than your tools do

    With Actuals Research, from ACCA, Gartner and IBM

    ACCA asked 1,600 finance professionals about their generative AI skills: 72% call them basic or have none. This chapter shows why skills are now the main barrier, and how the CFO job is changing.

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    1. 1

      Most finance professionals have basic AI skills or none.

      38% of finance professionals call their generative AI skills basic, and 34% have no experience at all.

      ACCA and CA ANZ, July 2026

    2. 2

      AI literacy is now the biggest barrier.

      Gartner now calls low AI literacy the biggest barrier finance leaders must address. And acquiring and developing AI and digital talent is the top near-term challenge for CFOs.

      Gartner, September 2026 and March 2026

    3. 3

      The CFO job is growing.

      62% of CFOs have taken on enterprise technology or AI strategy leadership.

      IBM, September 2026

    4. 4

      Gartner expects few teams to cut jobs, and more to change who they hire.

      Gartner predicted that fewer than 10% of finance functions would cut headcount because of AI by 2026. By 2028 it expects 20% of finance teams to stop hiring people who are not digitally literate.

      Gartner predictions, 2024 and 2026

    72%

    of finance professionals have basic or no generative AI skills

    ACCA and CA ANZ, 2026
    62%

    of CFOs now lead technology or AI strategy

    IBM, 2026

    ACCA asked 1,600 finance professionals about their generative AI skills. 38% call them basic. 34% have no experience at all.

    Gartner's newest research points the same way: its analysts call low AI literacy the biggest barrier finance leaders must address. And acquiring and developing AI and digital talent is CFOs' number one near-term challenge.

    Meanwhile the CFO job is growing. 62% of CFOs have taken on enterprise technology or AI strategy leadership.

    Jobs? Gartner predicted fewer than 10% of finance functions would cut headcount because of AI. It also expects 20% of finance teams to stop hiring people who are not digitally literate by 2028.

    100 finance professionalsPrediction
    No experience 34Basic 38Beyond basic 28

    0% of CFOs now lead tech or AI strategy

    By 2026<10%

    of finance functions cut headcount because of AI

    By 20280%

    stop hiring people who are not digitally literate

    What this means for you

    Long before AI changes the size of the finance team, it changes what the team does all day. Budget for training the way you budget for software.

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    Chapter 08 · Trust and control

    Treat AI output like a junior's work

    With Actuals Research, from Workiva, KPMG, CFO Dive and the EU AI Act

    26% of executives in a Workiva survey say AI errors have already reached the board or the outside world. This chapter shows what that costs and which rules are coming.

    4 lessons below

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    1. 1

      1 in 4 executives say AI errors reached the board or beyond.

      26% of executives say internal audits found AI errors that reached external audiences or board members.

      Workiva survey (vendor), August 2026

    2. 2

      Many worry about accuracy. Few track failures.

      48% of finance leaders name the accuracy of AI-generated financial output a top concern. Only 29% formally track where their AI adoption fails.

      KPMG, May 2026

    3. 3

      AI errors have already cost money.

      In October 2025 Deloitte refunded just over A$97,000 to the Australian government. The A$440,000 report it delivered, written partly with AI, contained made-up references.

      CFO Dive, October 2025

    4. 4

      The rules have a date.

      Under the EU AI Act, the high-risk rules for credit scoring of individuals apply from 2 December 2027. Fraud detection is excluded.

      EU AI Act and Regulation 2026/1744

    26%

    saw AI errors reach the board or the outside world

    Workiva (vendor), 2026
    48%

    worry about the accuracy of AI-generated financial output

    KPMG, 2026

    26% of executives say internal audits have found AI errors that reached external audiences or board members.

    Accuracy is now a top worry. 48% of finance leaders name the accuracy of AI-generated financial output as a top concern.

    Yet only 29% formally track where their AI adoption fails.

    It already cost money. In October 2025, Deloitte refunded part of a A$440,000 report for the Australian government after it was found to contain made-up references. The refund: just over A$97,000.

    AI errorsVendor survey

    0% saw AI errors reach the board or outside world

    0% formally track where AI adoption fails

    A$97,000 refundedA$440,000 report
    The rules are arriving

    The EU AI Act timeline for finance

    2 Feb 2025

    AI literacy becomes a duty

    Companies that use AI must take measures to support their staff's AI literacy. The 2026 Digital Omnibus kept the duty, without a required level.

    2 Aug 2025

    Rules for general-purpose AI

    Obligations for the providers of models like the ones behind ChatGPT and Copilot started to apply.

    Feb 2026

    COSO publishes AI controls

    COSO's guidance on internal control over generative AI: govern, inventory, assess, design, implement, monitor. It is not law. Expect your auditor to use it as a frame.

    2 Dec 2027

    High-risk AI obligations apply

    Moved from August 2026 by the Digital Omnibus. Credit scoring of individuals is high-risk. Fraud detection is not.

    2 Aug 2028

    AI in regulated products

    The last group of high-risk obligations, for AI built into products covered by EU safety law.

    What this means for you

    Treat AI output like the work of a new junior: logged, reviewed and traceable to the source. If you cannot trace a number back to the transaction, neither can your auditor.

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    Checklist

    Your Monday list

    One line per chapter. Tick what your team already does. What's left is your agenda.

    0 of 8 in place.

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