Practical AI workflows for accounting practices

Focus on operations, not autonomous advice

The safest early uses of AI in a practice support the work around professional judgement: organising, summarising, drafting and reminding. Advice, lodgements and conclusions about a client's position should stay with qualified people.

This is not only a risk question. AI can produce convincing answers that are wrong. CPA Australia's INTHEBLACK describes using AI to draft client email responses (opens in a new tab) that are then checked and approved by an accountant before sending, and warns that confident AI output still needs checking.

Four administrative workflows worth exploring

These are the areas practices most often explore first. Each has a clear human review point.

• Document organisation: sorting incoming documents into the right client and job, naming files consistently and flagging items that do not match a checklist. A person confirms anything uncertain.
• Draft correspondence: preparing first drafts of routine emails, such as requests for missing information or appointment confirmations, for staff to edit and send.
• Meeting summaries: turning a client meeting recording or notes into a summary and action list. INTHEBLACK notes that transcription tools raise consent, privacy and storage questions (opens in a new tab), so participants should know how recordings are stored and used.
• Task handovers: summarising where a job is up to when it moves between team members, based on notes and workflow status, so nothing relies on memory.

Before buying a new tool, check your existing software. business.gov.au points out that many tools businesses already use, including accounting software, now include AI features (opens in a new tab) for tasks like processing invoices and receipts.

Useful starting points versus unsuitable first projects

A good first project is frequent, contained and easy to review. A poor one is high stakes, hard to check or dependent on judgement.

Check sources and assign review responsibilities

Every AI-assisted workflow needs a named reviewer and a rule about what they check. For drafts, the reviewer checks facts, tone and anything that sounds like advice. For summaries, they check names, figures and action items against the source.

Keep the source visible. A summary that cannot be traced back to the document or meeting it came from is hard to trust and harder to correct.

Some practices also set a simple prompt rule. INTHEBLACK describes a practice that avoids client identifiers such as names, ABNs and tax file numbers in prompts, which reduces the information exposed if a tool is used in the wrong way.

Privacy and provider terms

If your practice is covered by the Privacy Act, the OAIC's guidance on commercially available AI products (opens in a new tab) says privacy obligations apply to personal information entered into AI and to personal information in its outputs. It recommends, as best practice, not entering personal information, particularly sensitive information, into publicly available generative AI tools.

The same guidance suggests checking provider terms, including whether inputs may be used to train models, and continuing to train staff and monitor use after implementation. Our guide to AI and privacy for Australian businesses covers these questions in plain language.

Write a short AI use policy first

INTHEBLACK recommends developing an AI-use policy and training staff to recognise appropriate uses. It does not need to be long. A page that lists approved tools, what may and may not be entered, who reviews outputs and how to report a problem is a solid start.

Bring your team along

New tools work best when the people using them help shape them. business.gov.au suggests (opens in a new tab) explaining that AI is being introduced to support staff rather than replace them, involving people in choosing tools, and training them to use the tools safely and responsibly.

In a practice, that might mean asking the team which administrative tasks frustrate them most, trialling a drafting workflow with two or three volunteers, and collecting their edits to improve prompts and templates. Keep communicating as the trial runs, and be honest if a tool is not working.

A small, well-supported trial tells you far more than a practice-wide rollout that nobody asked for.

Where to go next

If chasing client documents takes up a large share of your team's time, read how to streamline client document collection. When you are ready to talk to someone about implementation, our guide to choosing an AI implementation specialist for your accounting practice explains what to ask.

You can also find implementation help for your accounting practice and request a free 15-minute consultation.