2026 INTUIT ENTERPRISE SUITE AI TRUST LINE REPORT
The AI Trust Line: How finance leaders are navigating AI adoption
Finance leaders see untapped potential in AI, but accuracy, data security, and human oversight remain central to their adoption decisions.
Finance leaders are being asked to deliver faster answers with no drop in accuracy. In our 2026 Intuit Enterprise Suite AI Trust Line survey of 2,100 senior finance leaders, 76% see a gap between what AI could be doing for their team and how much they put it to work today.
But nearly all agree finance operates with almost no room for error.
The findings point to opportunities for AI to free up capacity, identify problems sooner, and help finance teams answer leadership’s questions faster. Respondents also identify what would give them greater confidence in using it: reliable company data, human review, and results that can be traced back to their sources.
We call this the AI Trust Line, where the opportunities finance leaders see in AI meet the conditions that give them confidence to use it. The survey explores how that line shifts across finance workflows, business needs, and the stakes involved.
AI in finance: Six key findings from 2,100 senior finance leaders
THE OPPORTUNITY GAP
3 in 4
See untapped AI potential
76% agree there's a gap between how much AI could be helping their finance team and how much they use it today.
THE STAKES
99%
Say finance has almost no room for error
Nearly all agree that even a small mistake can affect jobs, growth plans, customer commitments, or cash flow.
RECENT AI USE
#1
Reporting and close is the most common AI use case
Ranked first of eight workflows: 80% of AI users and testers report putting AI to work for financial reporting and close over the past three months.
TOP BARRIER
47%
Cite data privacy or security concerns
The most frequently selected barrier to using AI more deeply or at all, ahead of accuracy concerns (38%).
HUMAN OVERSIGHT
1 in 2
Say human review gives them the most confidence
50% select human review and approval before AI-generated work is finalized as a leading confidence builder for higher-stakes finance work.
THE PACE OF ADOPTION
52%
Say adopting AI too slowly can be as risky as moving too fast
Agree that, for finance teams, adopting AI too slowly can carry as much risk as adopting it too quickly.
What finance leaders want from AI, and what earns their confidence
Finance leaders see opportunities for AI to free up time for strategic work and deliver faster answers. Asked where AI could help most, 43% select freeing up time for strategic analysis instead of manual work, 40% cite spotting problems or errors sooner, and 38% point to answering leadership’s questions faster.
That view of AI’s potential is reflected in a broader expectation for finance work: 82% agree that AI will help finance teams spend less time reporting what happened in the past and more time shaping what the business does next.
For higher-stakes finance work, leaders also identify what would give them greater confidence in using AI. Half of respondents (50%) select human review and approval before work is finalized, followed by accurate, consistent, and current company data (48%) and clear traceability to source data and assumptions (44%).
Together, these findings define the two sides of the AI Trust Line: the opportunities finance leaders see above the line and the safeguards that would give them confidence in using AI below it.
“In construction, quality has always driven trust. Today, that includes clear communication and reliable financial information. AI can help put that information at our fingertips, but we still need the right safeguards and human oversight to make sure we’re using it responsibly.”
Lena Stob
Director of Finance and Strategy, Schippers Construction
Where finance leaders report using AI and where they’d consider using it with human oversight
Where are finance leaders using AI most?
Reporting and close is the most common recent use case (80%).
Recent use centers on month-end close. Among respondents using or testing AI, 80% report doing so for financial reporting and closing the books over the past three months, whether through standalone tools or features built into their financial systems. That puts it well ahead of the second most common workflow, forecasting and budgeting (61%), and the third, board or leadership reporting (50%).
At the other end of the list, leaders are far less likely to report using AI for payroll (33%), where mistakes can directly affect employee paychecks, or reconciliation (35%). Just 20% report using or testing AI for fraud or anomaly detection, making it the least common of all eight workflows measured.
Where are finance leaders most willing to use AI with human review and audit trails in place?
Reporting and close also leads willingness, with 93% open to using AI-generated outputs for it when human review and audit trails are in place.
Recent use only tells part of the story. When all 2,100 respondents were asked about their willingness to use AI-generated outputs with full human review and audit trails, the numbers were higher across every comparable workflow. Reporting and close topped the list at 93% willingness (compared with 80% recent use), while forecasting, budgeting, and cash flow projections reached 85% willingness (compared with 61% recent use).
The gap between recent use and willingness is widest in payroll and compliance. While just 33% of leaders report using AI for payroll, 70% say they would consider using AI-generated outputs for payroll and headcount planning under human review and audit trails. Compliance and audit support reflects that same pattern (68% willingness vs. 41% recent use).
Willingness falls to its lowest point for workflows tied to external reporting and profitability decisions. Even with human review and audit trails assumed, 52% of leaders say they would not be willing to use AI-generated outputs for lender or bank reporting, and 47% say the same for margin and pricing analysis.
Use and willingness came from separate questions with different respondent bases (1,343 users and testers; 2,100 respondents), so the comparison shows direction and cannot be read as an adoption forecast. Recent use was not measured for growth or strategic planning, margin and pricing analysis, or lender or bank reporting.
Data privacy or security concerns lead barriers to deeper AI adoption
Protecting company data is a leading concern as finance leaders consider how to use AI more widely. Asked what prevents or discourages them from using AI more deeply or at all, 47% cite data privacy or security concerns, ahead of accuracy (38%) and cost or unclear business value (30%).
That caution is tied to very specific concerns about company information. In our survey, 92% of finance leaders point to at least one distinct risk when feeding financial data into AI systems, with worries centering on boundaries, oversight, and ownership:
- 64% say exposure of sensitive financial data outside the company.
- 50% cite insufficient visibility or control over where information is stored or processed.
- 43% worry about company data being used without approval.
- 39% cite unclear accountability if something goes wrong.
When AI helps prepare the numbers, finance leaders split on who answers for them
Shared accountability is the leading response when AI-assisted financial work goes wrong
Accountability is part of the data security conversation too. Nearly two in five respondents (39%) cite unclear accountability as a top risk when using AI in finance workflows.
The question of responsibility carries through to the financial results shared with leadership. Asked who should be held most accountable if an AI-assisted output turns out to be wrong after reaching their CEO or board, just 8% point to the person who configured the workflow, while 15% select the team member who used or reviewed the output. Another 28% point to the finance leader who gave final approval, while the largest share (42%) favors shared accountability, with no single person or party most responsible.
SHARED RESPONSIBILITY
42%
Say no single person should be most accountable
When an AI-assisted financial output proves wrong after reaching leadership, the largest share of finance leaders favor shared responsibility across the team.
FINAL SIGN-OFF
28%
Hold the approving finance leader most accountable
Among those who do name one person, the finance leader who gave final approval is the most common choice, ahead of the team member who reviewed the output (15%) or the person who configured the workflow (8%).
An AI-assisted analysis draws nearly as much confidence as work prepared without AI
Given two versions of the same financial analysis, both reviewed and approved by their finance team, respondents were nearly evenly divided on which they’d feel more confident sharing with their CEO, board, or investors. One was prepared with AI assistance, the other without.
Beyond the work itself, finance leaders also have preferences about how AI fits into the tools they use. Asked which setup would give them greater confidence using AI in important finance workflows, more choose AI built into their main financial platform than standalone AI tools.
A NEAR TIE
40% vs. 42%
AI-assisted and non-AI analyses draw nearly equal confidence
40% would feel more confident sharing the AI-assisted financial analysis with their CEO, board, or investors, versus 42% the version prepared without AI.
WHERE AI SITS
54%
Say embedded AI gives them greater confidence
Select AI built into their main financial platform as the setup that would give them greater confidence in important finance workflows, compared with 25% who select standalone AI tools.
“Business runs on trust and personal relationships, two things software will never supply. AI can assemble the slides and organize the data, but finance leaders are the ones who sit across the table, explain the story, and take responsibility for the outcome.”
Blake Rohm
Controller, Lallier Construction
Finance leaders see risks in both adopting AI too quickly and too slowly
Moving too quickly is harder to defend, but waiting carries risks of its own
Moving too quickly with AI may be the harder decision to defend, but finance leaders also see a downside to waiting. Asked which choice would be harder to justify to their CEO or board, 58% select adopting AI too quickly without adequate controls, review, and accountability. Still, 42% take the opposite stand, viewing too much caution and lost efficiency as harder to defend.
Leaders are also divided on how to weigh the risks of adoption speed: 52% agree that adopting AI too slowly can be as risky for finance teams as moving too quickly. And more than 1 in 3 respondents in every industry surveyed share that view, ranging from 37% in field services to 65% in franchises.
POTENTIAL BUSINESS IMPACT
Slower answers and less strategic time top concerns about limited AI use
Finance leaders also identify potential business problems associated with limited AI use. 93% select at least one, with slower responses to leadership questions and less time for strategic analysis topping the list.
Asked which problems limited AI use could create for their business, respondents identify:
- 32% slower answers to time-sensitive leadership questions
- 30% less time for strategic analysis and advising the business
- 21% additional headcount needs as workloads grow and repeatable tasks remain manual
- 11% greater difficulty attracting and retaining finance talent
How growing businesses compare on AI
At businesses reporting revenue growth, finance leaders are more likely to:
- Report increasing their AI use over the past three months
- Express greater willingness to use AI-generated outputs with human review and audit trails
- Prefer sharing a team-approved, AI-assisted analysis with executive leadership over one prepared without AI
AI remains a priority for finance leaders over the next 12 months
Concerns about accuracy, security, and oversight remain part of the conversation, but AI is firmly on finance leaders’ agendas. 82% say advancing AI is a priority for their finance organization over the next 12 months, including 20% who rank it as a top priority. Many also see AI adoption playing a role in their company’s goals and ability to compete.
AI IS ON THE AGENDA
82%
Say advancing AI is a priority
Eight in 10 respondents are prioritizing advancing AI in their finance organization over the next 12 months, including 20% who consider it a top priority.
BUSINESS GOALS
57%
See increased AI adoption as critical to business goals
More than half agree that increasing AI adoption will be critical to their company meeting its goals.
COMPETITIVENESS
77%
Expect AI to create new competitive advantages
More than 3 in 4 believe AI will create competitive advantages in their industry over the next 12 months.
Explore the full AI Trust Line report
See how finance leaders’ views on AI adoption differ across industries, workflows, and business growth segments. Explore the full report for detailed findings and analysis.
Access the detailed survey data supporting this report available to download, including breakdowns by industry, company revenue, business growth, AI usage, and ERP usage.
Frequently asked questions
What is the AI Trust Line?
The AI Trust Line is the point where the opportunity finance leaders see in AI meets the conditions they need before they will rely on it. The line moves depending on the task and what is at stake. It comes from a 2026 Intuit Enterprise Suite survey of 2,100 senior finance leaders.
The line sits in a different place for different work. Leaders are more open to AI help with financial reporting and closing the books than with payroll or board reports. The line also moves based on how good the company’s data is, whether a person reviews the work before it is final, and who is responsible if a number is wrong. The report maps where the line sits today for each type of finance work.
How many finance teams use AI today?
Most finance teams are still early. In Intuit Enterprise Suite’s 2026 Future of Finance survey, 77% of finance leaders said they were not yet using AI in their finance work or were only testing it. Adoption also varied by business growth. Among finance leaders at the fastest-growing multi-entity businesses, only 7% reported no AI use at all, compared with 46% at steadier businesses.
Separately, The AI Trust Line survey found that 76% of finance leaders see a gap between how much AI could help their team and how much they use it today.
What would make finance leaders trust AI with higher-stakes work?
Finance leaders point to three things: a person reviewing and approving AI’s work before it is final (50%), company data that is accurate, consistent, and current (48%), and the ability to trace an AI answer back to the numbers and assumptions behind it (44%).
None of these are about the AI itself; they are about the system around it — good data, human review, and a clear record of how each answer was made. The biggest barrier to deeper AI use is not accuracy either; it is concern about data privacy and security (named by 47% of leaders) ahead of accuracy (38%) and cost (30%). A simple test for any finance AI tool: Can you check its work, trace it, and name who owns the result?
Where are finance leaders willing to use AI?
Finance leaders express willingness to use AI across a range of workflows when full human review and audit trails are in place. Under those conditions, 93% would be willing to use AI-generated outputs for financial reporting and closing the books, 70% for payroll and headcount planning, and 68% for compliance and audit support.
Recent usage runs behind willingness. Among leaders already using or testing AI, 80% use it for reporting and close, 33% for payroll, and 41% for compliance or audit support. The findings suggest that willingness to use AI can extend beyond current usage, particularly when human review and audit trails are assumed.
Is adopting AI too slowly a risk for finance teams?
Many finance leaders now say yes: 52% agree that adopting AI too slowly can be as risky as adopting it too quickly. But caution still feels easier to explain: 58% say moving too fast without the right controls would be harder to defend to their CEO or board.
The costs of moving slowly are concrete. The top concerns leaders named are slower answers for leadership and less time for strategic work. And 76% already see a gap between what AI could do for their team and how much they use it today. The real question is not speed vs. safety; it is putting the right checks in place so that moving faster becomes safe.
Will AI replace finance jobs?
The survey points to opportunities for AI to change how finance teams work, particularly by helping with repetitive tasks and freeing up time for strategic analysis. Judgment and responsibility stay human. When AI-assisted work goes wrong, leaders most often say the people who used, reviewed, and approved it share responsibility — not the tool or its vendor.
Trust in that combination is already high. An analysis prepared with AI’s help, then reviewed and approved by the finance team, earns nearly as much confidence as work prepared without AI. For a deeper look at what this means for the profession, see Will AI Replace Accountants? No, and Here’s Why.
Who was surveyed for the AI Trust Line report?
Intuit commissioned the research firm CatalystMR to run an online survey in August 2026 of 2,100 senior finance leaders — CFOs, controllers, and VPs of Finance at U.S. businesses with $2.5 million to more than $100 million in yearly revenue. All of them help decide which finance technology their company uses.
About half (1,054) described their businesses as growing; the rest as stable or struggling. Questions about recent AI use went to the 1,343 respondents already using or testing AI. All answers are self-reported, figures are rounded, and the findings show patterns. They do not prove that one thing causes another.
Methodology
Intuit commissioned an online survey fielded by CatalystMR in August 2026. The survey included 2,100 CFOs, controllers, VPs of Finance, and other senior finance leaders at U.S. businesses with $2.5 million to $100 million or more in annual revenue, all of whom hold primary or shared responsibility for financial technology and operational decisions. Of those, 1,054 describe their businesses as growing and 1,046 as stable, in survival mode, or facing closure. Recent AI use questions were asked of the 1,343 respondents using or testing AI.
AI refers to AI-powered capabilities used in finance workflows, including standalone tools and capabilities embedded in financial software. All figures are rounded to the nearest whole number and may not add up to 100%. For questions where respondents could select more than one answer, figures show the share of respondents. All findings are self-reported. Relationships between variables are correlational and do not establish causation. Respondents received remuneration.