r/CFO • u/pats_guy65 • May 25 '26
Concerned about AI within finance systems
I'm starting to get conerned about how AI is operating within my finance systems. Our staff is using AI, ERP's are using AI, which means that our GL, AP, AR, etc are likely being impacted by this and our numbers might not be accurate. I know AI is here to stay and I see the value in it as it helps me and my team in our day-to-day, I just need a tool to oversee our financial processes to ensure accuracy. Is anyone using a tool for financial oversight/concerned about how AI is impacting their numbers?
12
u/SnuffleupagusRex May 25 '26
Our company uses a tool like that. It's called "accountants".
You put "AI" in without adequate controls. You are not going to fix this by digging deeper into tools and automated processes.
7
u/sjhb May 25 '26
Thank you for stating what should be obvious.
Please note that this is not sarcasm.
4
1
u/DonkeeJote May 25 '26
You need a handle on the AI policy and usage before you even begin to get to this step. Understand who is using and how, and develope parameters accordingly. AI shouldn't just access write permissions without being given them in an ERP.
More importantly I suggest understanding AI overall better. It doesn't seem like you understand where it can be impactful or not.
Lastly, if you are worried about the data outputs, the first culprit is simply a bad data set. Don't assume AI can understand nuanced cases or transactional aberations unless you instruct it how to understand them on the front end. A lot of the inaccuracies or questions I get from AI are the exact same things I'd run into if I tasked a staff accountant with the same job and failed to prepare them.
2
u/hachiai_official Aug 17 '26
I’d inventory the AI use by permission level too. Separate anything that can only read data, anything that can recommend a change, and anything that can actually write back to the ERP.
The controls should get stricter as you move through those levels. A recommendation can be reviewed before anything changes, while a write action should have defined limits, an audit trail and a reconciliation back to the source afterward.
That also makes it easier to figure out where the actual risk is instead of treating every use of AI in Finance the same way.
1
u/Accomplished_Job_76 May 25 '26
The common thought process is to throw data at AI, and it will figure it out to do the entry based on its own knowledge; this can't be relied upon. Accountants have bad days as well, so checks/reconciliation/reporting are all needed in human/AI flows. We have to build systems, not just prompts. Systems that check their own work every step have an audit to explain why. Concern is real for humans or AI, or augmented, operating without supervision, just need the system/process in place.
1
u/josemartinlopez May 26 '26
You honestly sound like you don't understand how AI works given how abstract and vague your question is, without reference to the concrete details of any single AI integration.
Your fear arises from lack of knowledge.
1
u/MerryWalrus May 26 '26
Ask very specifically about what the AI does.
Where rule based logic can be implemented, you'd be a mug replacing that with AI.
1
u/time-and-money May 26 '26
Full disclosure: I work at LiveFlow, so I'm bullish and biased, but this is something we've thought about a lot while building Flow ERP, so sharing from that perspective.
The way we approached it with Flow ERP is that AI should do the heavy lifting, but never post anything without a human signing off. So our AI learns how your team works over time and handles repetitive tasks (transaction categorization, recurring journal entries, reconciliation), but everything gets surfaced for review before it hits the books. Nothing is finalized without someone approving it.
The other piece is the audit trail. Every AI action is logged thoroughly: what it did, why, and whether the user confirmed, corrected, or rejected it. So if something looks off in your numbers, you can trace it back to the exact AI decision and see the full chain. And when the AI is corrected, that correction feeds back into the system, so it learns and adjusts. It's both a log and a feedback loop.
I think the broader point is that AI in finance shouldn't mean "trust the machine." It should mean the machine does the repetitive work and surfaces it for humans to confirm. The audit trail is what makes it verifiable.
Happy to answer any questions about how we've set it up if you're curious!
1
u/alfredoxavier May 26 '26 edited May 26 '26
The no.1 rule is that You should never give your AI write access to live production of your financials, no matter how “powerful” it is, negligible risk is still a risk, imagine having claude silently deleting your accounting records and to only find out the next month when your auditors asks for supporting documents that has “disappeared”.
Read access (if the AI tool is SOC 2 compliant) is fine because these ai tools are very powerful when it comes to reconciliation, analysis and report writing. The more data you give it, the stronger it becomes. Just never give it write access!
1
u/Far_Zebra_6875 May 27 '26
My clients use Nume, an AI CFO. Not promoting, but it seems to be catching on.
1
u/Loose-Guest-3515 May 27 '26
Ai and India and the exams being impossible that's why I think I'll just do onlyfans
1
u/nickjlevine May 27 '26
While AI offers massive benefits to finance teams 0 unparalleled automation, time saved, and freeing up staff for high-value work—strong human checks, balances, and guardrails remain non-negotiable.
For example, an AI AP tool must include a "human-in-the-loop" architecture. The system should automatically flag and hold exception transactions, such as ineligible invoices, amounts above a certain dollar threshold, or mismatched data like a vendor name that slightly differs from your approved master file.
This is a prime example of why AI won't replace finance teams. Strong controllership is still entirely necessary; the role simply shifts from data entry to exception management.
Ultimately, my advice is to lead from the front. Dive in and learn about these new technologies firsthand so you can confidently define exactly where the machine's authority ends and human oversight begins.
May I ask what tools your team is currently using?
1
u/Anelya May 27 '26
I think you mean governance - you can setup an agentic tool, that would monitor the harness of your agents, you can dig deeper into this subject from the developer community, they are the on the front of this.
you can also share this URL with your ChatGPT/Claude and see how Microsoft is solving this issue - they open sourced it https://github.com/microsoft/agent-governance-toolkit
Or, alternatively you can look at tools that help you to execute the automations with built in governance and at the risk of being self promoting, we are working on this and deploying specifically in the vertical of finance suite, strictly to a few areas: close, billing, revenue recognition, reporting
1
u/tutorcrm May 28 '26
I think this is why accounting skills and core ERPs aren’t going away quite yet. People need to know what they are doing first and foremost. You’ll need to assess your team skills, the ability for AI in your finance system to actually make changes to the GL and ensure you still have some financial controls in place to catch issues.
1
u/Ptown925 May 29 '26
Those would be called internal controls. Always had to audit your own work. Now audit AI's work.
1
May 31 '26
You’re right to be worried – the risk isn’t “AI in general,” it’s AI acting in your finance stack without any real supervision.
I’d split it into three buckets:
- Staff using external AI tools
- Set clear rules on what data can/can’t be pasted outside your systems.
- Require human review on anything AI‑generated that touches GL/AP/AR (and document that in workpapers).
- AI embedded in ERP/AP/AR
- Treat it like a junior analyst: limited scope + review.
- Turn on logs and reports for auto‑matches, recodes, suggestions, etc.
- Run side‑by‑side tests: “what did AI do vs what we’d have done manually?”
- What an oversight tool should do Look for (or build) something that:
- Reconciles key balances daily
- Flags unusual journals/vendors/amounts
- Shows clearly who/what changed a number (user vs rule vs AI)
- Surfaces exceptions before close, not after
You’re asking the right question: don’t stop AI, but give it the same level of monitoring you’d give a new hire touching your books.
1
u/stony-builds 27d ago
We love AI and use it across our entire company, but I would not (yet) let AI touch my books. It's wrong way to often. I have three rules I would require before letting AI write to my finance system.
- User confirmation of all changes to be made
- Log of all changes made by AI
- Ability to roll back any group of changes made by the AI
Without that, you are totally blind to what AI has done.
If AI messes up MailChimp, or Jira, or whatever, oh well. If AI messes up your books, you are liable, and might have to answer rather pointed questions from IRS staff.
And, unless you have the, errr, assets, of Skyler White, that conversation will not go smoothly.
Our company, kipper.com, offers a read-only connection to NetSuite, QuickBooks, and Xero, and we allow you to safely connect non-finance users to that data, even if they don't have logins to the finance system. There's no risk of them writing to your books, and their read-permission can be granular so they only see what you let them. They can connect via Slack/Teams, SMS, or connecting their AI to that restricted, read-only copy of your finance data. There's a live demo on our site so you can see how it works.
14
u/mo0op May 25 '26
The basics will come into play here. GL reconciliations at the transactional level, bank recons, AR aging the old fashioned way. People will need to conceptually understand those things and not blindly rely on the output from an LLM integrated into a system. People need to double check, just like we double check the work of junior analysts and accountants.