Accounting Automation: Is AI Upskilling a Must for Your Staff?

AI upskilling is the process of training your team to understand and use artificial intelligence tools effectively. Sounds straightforward, right?

In reality, it’s a lot of “learn how to talk to the machine” type of work. Especially when it comes to LLMs (Large Language Models) like ChatGPT, Gemini, or Claude. These tools are powerful—but only if your team knows how to prompt them properly.

It’s not just about throwing keywords at a chatbot. It’s about precision. Context. Relevance. In other words, upskilling takes time, practice, and strategy.

And when it comes to accounting automation, not every tool requires your staff to become AI experts. The difference lies in what type of AI is under the hood.

When Is AI Upskilling Necessary?

Here’s when it makes sense:

• You’re using LLMs to automate emails, draft reports, or assist in research.

• You want staff to generate content, summarize data, or create workflows using AI.

• You’re integrating AI directly into your client communications or internal ops.

This is where prompt engineering comes into play—crafting inputs that yield accurate, relevant outputs. If your tools are LLM-based, you’ll absolutely need some training to get ROI.

But here’s the kicker: not all AI is LLM-based. And not all AI needs you to talk to it.

What Types of AI Are Actually in Play in Accounting?

Let’s break down the different types of AI your team might encounter in accounting automation:

• LLMs (Large Language Models): Require prompts. Think ChatGPT.

• Generative AI: Creates reports, summaries, client comms. Still needs human guidance.

• Predictive AI: Forecasts trends or cash flow based on historical data.

• Machine Learning (ML): Learns from data over time. Powers automation behind the scenes.

• Robotic Process Automation (RPA): Mimics repetitive human tasks (think invoice processing).

• Computer Vision AI: Extracts data from receipts and documents using OCR tech.

Here’s the Problem: Most Automation Isn’t Actually AI

Let’s be honest. Much of what’s considered automation in accounting is still driven by scripting and rigid rules, not true intelligence.

• Rule-based triggers

• If/then logic

• Script-based integrations

This isn’t AI, not that that makes it useless. What it is, is automation that sticks faithfully to its instructions. Unfortunately, if it encounters an unexpected situation, it can break.

True AI adapts. It can learn. It improves over time. And it doesn’t need a checklist of instructions every single time.

So—Do You Really Need to Upskill Your Staff?

If your AI tools rely on prompting? Yes.

If your team is managing RPA bots? Probably.

If you’re training models from scratch? Absolutely.

But if your platform is built to ingest data automatically and interpret it to provide results to you? That’s a different story.

Here’s Where Botkeeper Changes the Game

Botkeeper uses proprietary AI with machine learning to automate bookkeeping. That means:

• No prompt writing.

• No code wrangling.

• No need for your team to moonlight as AI whisperers.

The only “training” your team needs is how to provide clean, categorized, consistent data, because that’s what our ML models learn from. The better the inputs, the better the results. That’s it.

Let’s Talk AI That Works—Without the Upskilling Tax

Botkeeper offers several smart features that make good use of AI without your team needing another degree.

• Transaction Manager – Categorizes and manages transactions with AI-powered intelligence. Our models learn your clients’ habits and customize their actions to fit each client.

• Auto Bank Rec – Performs reconciliations automatically—no spreadsheets, no sweat.

• Bot Review – AI checks your books for errors in real time before your team even knows they exist.

And yes, the rest of our tools (like Activity Hub, Work, Documents, and JE Automation, among others) are designed to work with your existing processes, not make you overhaul them.