The biggest risk of AI in accounting is the risk of being left behind. One way to avoid this is to better understand the range of technology that incorporates AI; and the different ways in which this may challenge or support accountants in the future.
Essentially, AI is an umbrella term. And I recommend being clear as to the 5 distinct types of AI that are impacting the finance and accounting world. And once you know what each one does, it’s easier to spot where the related tools might help (or hinder) your work.
Think of them as your invisible team members – each with their own speciality.
Large Language Models – the enthusiastic, well-read but often naive intern
Large Language Models (LLMs) like ChatGPT and Claude are text wizards. They digest huge amounts of information and spit it back in plain English. Well, mostly plain.
They can help you with loads of tasks such as:
– Drafting emails to tricky clients
– Summarising lengthy tax guidance – Turn HMRC manuals into client-friendly summaries
– Turning meeting notes into to-do lists or reports – A quick way to stay on track
– Translating accountant-speak into client-speak
– Giving you a starting point for blogs, articles and reports
But remember: they can be confidently wrong. So treat them like a bright intern – useful, but needing supervision.
And, one other tip, these are Large LANGUAGE Models. This is why they tend to be less effective, impressive and accurate, when you ask them to manage numbers rather than words.
Generative AI – the creative assistant
This is where AI gets fancy. Generative AI (often referenced simply as ‘GenAI’) creates stuff – whether that’s visuals, code, or client-ready reports.
In practice, that means:
-Auto-generating FAQs or help centre answers – Especially useful for client portals
– Producing first drafts of board packs or advisory summaries
– Generating charts or graphs from raw data – Great for client-facing presentations.
– Suggesting how to categorise messy bookkeeping entries
It’s often powered by LLMs, but focused on creation. Handy for speeding things up, especially when the blank page is staring back at you.
Agentic AI – the self-starter junior
Still a bit of a rising star, Agentic AI tools don’t just wait for instructions. They are autonomous systems that complete multi-step tasks with minimal input. So they take a task, plan the steps, and crack on with it. In an accounting context, they might:
– Chasing overdue clients for missing info – With personalised, professional messages.
-Pull data from bookkeeping software and spreadsheets
– Clean it, tag it, analyse it
– Spit out a draft report with comments for you to review
Microsoft Copilot is edging into this space, as are tools like Digits and MindBridge. It’s like having a junior who doesn’t need spoon-feeding.
Machine Learning – the data whisperer
This one’s been around the longest. Less flashy but quietly powerful. Software that contains elements of machine learning spots patterns and learns from data.
It’s already baked into lots of tools you probably use, helping with:
– Automatically allocating sales and expenses to nominal account codes
– Fraud detection
– Predicting payment delays
– Flagging unusual and dodgy transactions
– Risk-based auditing
It won’t write your newsletter, but it’ll save you from missing what matters.
Natural Language Processing – the multilingual archivist
Natural Language Processing (NLP) helps machines understand language – written and spoken.
In our world, it powers tools that can:
– Extract dates from 100-page contracts
– Voice-to-text conversion for meeting summaries
– Understand voicemail transcriptions
– Understand spoken instructions
– Read messy scanned invoices
If you hate data entry and sifting through docs, NLP is your new best friend.
it’s not about replacing you – it’s about supporting you
Think of these tools not as rivals, but as potential team members. They won’t steal your job unless your job only involves the most basic, simplest of tasks.
But they might help you reclaim some time, avoid the grunt work, and look even smarter in front of clients.
These examples show that each type of AI plays a different role. But the real magic comes when they work together — GenAI builds the content, NLP understands your documents, LLMs explain it, ML finds patterns, and Agentic AI glues it all together into workflows.
To get the most from AI-driven systems you need to learn best practice (including effective prompt engineering) and how to manage each one that you employ in your office/firm.
