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AI tools for accountants
AI tools for accountants fall into a few clear categories, and choosing between them is mostly a question of data terms, audit trail and fit with the work you already do, not which product tops a list.
This guide sets out those categories and an evaluation method. It deliberately does not rank products: features and terms change too often, and the right answer depends on your firm, your clients and your software.
Leave with a category map, a shortlist method and the questions to put to any vendor.
ICO guidance covers AI accountability, transparency and fairness; the guidance is currently under review. ICO: AI and data protection guidance ↗
On 26 June 2025 the FRC published its first guidance on AI in audit, including principles for proportionate documentation of AI tools; it is not prescriptive and introduces no new regulatory requirements. FRC: guidance on the uses of AI in audit ↗
New to the topic? Read the background on artificial intelligence.
AI accounting software
what categories of AI tools for accountants exist?
General assistants, AI inside accounting software, document extraction, and audit or analytics tools.
General assistants such as ChatGPT, Claude, Gemini or Microsoft Copilot handle drafting, summarising and explanation across any task. They are flexible but know nothing about your clients unless you give them data.
AI features inside accounting, practice management and spreadsheet software work on data already in those systems, for example suggesting transaction categories or drafting commentary, which can reduce copying data between tools.
Document extraction tools read invoices, receipts and statements into structured data, while audit and analytics tools test populations of transactions. These narrower AI tools for accountants are easier to evaluate because the task is fixed.
General assistants for drafting.
Embedded features for in-system data.
Specialist tools for extraction and testing.
AI accounting software
which AI tools for accountants should we start with?
Usually the assistant or embedded feature you already license, used on a narrow task.
If the firm already has Microsoft 365 or Google Workspace, the assistant attached to it is often the lowest-friction start, because identity, access and data terms are already managed centrally.
Start with one or two tasks, such as client email drafts or variance commentary, rather than a broad rollout. That gives you a baseline to compare against before you buy anything new.
Our pages on Microsoft Copilot training and ChatGPT training cover the assistant-specific detail; this page stays at the category level.
AI accounting software
how do we evaluate AI tools for accountants on data and confidentiality?
Ask where data is stored, how long it is kept and whether it trains the provider's models.
The ICO guidance on AI and data protection frames the questions: accountability, transparency, lawfulness, accuracy, fairness, security and data minimisation. The ICO says the guidance is under review, so check for updates.
For any of the AI tools for accountants you are considering, get written answers on data location, retention, sub-processors, model training on customer data and the admin controls available to the firm.
Client engagement terms matter as much as the vendor's. If a client has not agreed to their data being processed by a third party of that kind, the tool is unsuitable for that client however good it is.
| Check | What to establish |
|---|---|
| 1 | Get data terms in writing. |
| 2 | Check admin and access controls. |
| 3 | Match against client engagement terms. |
AI accounting software
how do we judge accuracy and audit trail?
Test on your own past work and insist on being able to trace each output back to source.
Run a candidate tool on a sample of completed jobs where you already know the right answer, and record where it was right, wrong or vague. That tells you more than any demonstration.
For anything that may be reviewed by a regulator or a client, the output needs a trail: what data went in, which version of the tool was used and who checked it.
The FRC's guidance on AI in audit sets out principles for proportionate documentation of AI tools. Even outside audit, that is a sensible standard for AI tools for accountants.
AI accounting software
what about cost, lock-in and skills?
Price the whole change, including review time and training, not only the licence.
Licence cost is visible; review time, set-up, integration and training are not. A tool that saves drafting time but adds review time may not help, and Acas advice on AI at work is clear that outputs still need checking for accuracy, tone and bias.
Check how easily you can export data and prompts if you switch, and whether the tool only works inside one software ecosystem.
ACCA's Digital Horizons report stresses that finance professionals need to understand AI's capabilities and limitations; ICAEW members can also use its free generative AI e-learning as a foundation.
Count review and training time.
Check export and switching.
Budget for skills, not only licences.
AI accounting software
how do we turn a shortlist into adoption?
Pilot with a small group, write the rules down, then train everyone on real tasks.
A two-or-three person pilot on defined tasks, with a simple log of time and issues, gives you evidence before a firm-wide decision.
Capture what you learn in a short policy; our AI policy template and the hub on AI for accountants cover what that should include.
Then train the wider team on the tasks the pilot proved. Our AI training for accountants does that on your own work. Contact us if you want help running the pilot.
Pilot small, log everything.
Write the rules from the pilot.
Train on proven tasks.
Make the decision concrete
What does the current task cost in time?
Choose a task connected to ai tools for accountants and enter its current workload. This gives you a baseline to discuss before buying training or commissioning a build.
A baseline is useful even if you decide to keep the process manual. Measure the work that matters, then compare quality and review effort as well as time.
Assess the workflow before changing it, or plan business AI training if the gap is how people use existing tools.
Your current workload
Estimate how much time the existing task takes before discussing ai tools for accountants.
16 hours per week
People × minutes × weekly tasks ÷ 60. A workload baseline from your inputs, not a prediction of AI time savings. Include review and support time when comparing a proposed workflow.
A useful AI investment leaves your team able to do the work and judge the result.
Continue with the right question
Where should you go next?
Use the overview for context, then follow the pages that match your delivery decision.
See our ai training service or read the ai for accountants overview.
FAQ
Questions, answered
Evidence and further reading
Which sources support the guidance?
Source links support the specific background described here. The practical checklists and illustrative examples are predeploy’s guidance.
ICO guidance covers AI accountability, transparency and fairness; the guidance is currently under review. ICO: AI and data protection guidance ↗
On 26 June 2025 the FRC published its first guidance on AI in audit, including principles for proportionate documentation of AI tools; it is not prescriptive and introduces no new regulatory requirements. FRC: guidance on the uses of AI in audit ↗
ACCA says finance professionals need to understand the capabilities, limitations and potential applications of AI, and have a crucial role in steering ethical and responsible adoption. ACCA: Digital Horizons ↗
ICAEW members can access up to eight hours of free e-learning giving a practical overview of generative AI and its application in finance. ICAEW: accountants' GenAI skills to get boost with ICAEW training ↗
Acas advises clear AI policies, consulting workers and representatives, checking outputs for accuracy, tone and bias, and care entering business-sensitive or personal information into public tools. Acas: One third of employers think AI will increase productivity ↗
Background reading on the broader field of artificial intelligence. Wikipedia: artificial intelligence ↗
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