- What RPA and AI each do well
- Comparing four approaches
- Fixed tasks versus judgement
- How to combine them
- Where people should check
The short answer
RPA repeats a set procedure exactly as defined. AI reads content and decides what it is. Neither is better; they are good at different work.
When automating, start by splitting the job into fixed tasks and tasks that need judgement. Fixed tasks go to RPA or a workflow, some of the judgement goes to AI, and anything where someone must answer for the result stays with a person. That split is the starting point for combining them.
The four approaches side by side
The terms are easy to confuse, so here they are together.
- RPA (robotic process automation): software that records on-screen actions and repeats them in place of a person — "click this button, paste into this field".
- Workflow: a defined sequence of steps and approvals, such as "request → manager approves → accounts notified", run in order.
- AI: reads text or images and makes judgements — classifying, extracting fields, summarising.
- AI agent: AI that chooses between tools and works out the steps itself to complete a task.
| Aspect | RPA | Workflow | AI | AI agent |
|---|---|---|---|---|
| Strength | Repeating screen actions | Fixed sequences and approvals | Reading, classifying, extracting | Working out steps as it goes |
| Who defines the steps | People | People | People (AI handles one step) | The AI |
| When input is unexpected | Stops, or fills the wrong field | Stops | Produces a plausible result | Tries a different approach |
| Predictability | High | High | Expect some errors | Steps themselves may vary |
The third row is the one that matters. RPA handles surprises badly; a moved button can stop it. AI produces some answer even for unexpected input, but that answer is not necessarily right. A failure that stops and a failure that carries on wrongly are noticed in very different ways.
Fixed tasks and tasks that need judgement
To split the work, ask: does this follow the same steps and give the same result every time?
Examples of fixed tasks:
- Every morning, export yesterday's sales from the sales system and save the file to a set folder.
- When a request is submitted, notify the manager and wait for approval.
- Copy the third column of a spreadsheet into an input field in another system.
Examples of tasks that need judgement:
- Purchase orders arrive from customers in different layouts, and item names and quantities are in a different place each time.
- Read an incoming email and decide whether it is a quote request, a complaint or a billing query.
- Pull the necessary details out of a handwritten note.
Use AI for a fixed task and you introduce variation into something that should come out the same every time. Build a judgement task with RPA alone and it stops at every exception, leaving people to fix it. Choosing a tool that does not fit the nature of the work is a common reason automation disappoints.
If different people do the task in different ways, standardise the steps before automating. Work that has no fixed procedure does not become fixed because of the tool you choose.
What a combination looks like
Take a company that receives purchase orders by PDF or fax and enters them into its sales system.
- Workflow: collect incoming orders in a set folder and tell the person responsible that something new has arrived.
- AI (OCR): read the order and extract customer name, item, quantity and requested delivery date. This is the part that copes with differing layouts by estimating where each field is.
- Person: review the extracted details on screen, comparing quantity and delivery date against the original in particular.
- RPA: enter the checked details into the sales system's input screen. If the system offers an API for receiving data, using that instead of screen actions is less likely to break.
- Workflow: once entered, notify the shipping team.
Each approach handles only the one step it is good at. Handing the whole thing to an AI agent is possible, but for work that runs the same way every day, fixing the flow as a workflow makes it much easier to trace what happened where.
Where people check
Automation still leaves places where a person looks. Three are worth fixing in advance.
- Right after AI output: AI answers even when the input is unexpected, so review on the assumption that errors are mixed in. Money, quantities and dates come first.
- Before anything irreversible: confirming an order, making a payment, sending outside the company. Do not let these flow through automatically; require human approval.
- When something stops: RPA halts, or the AI reports it could not read a document. Unless someone is named to pick up these exceptions, work piles up at that point.
Automated processes tend to become something only their builder understands. Write down which task is handled by which approach, in what order, or nobody will be able to fix it when the person in charge changes.
Where to start
Trying to connect everything at once usually slows things down.
- Pick one process and write out each step.
- Mark each step as fixed, needing judgement, or requiring a person to take responsibility.
- Automate the most frequent fixed steps first.
- When bringing AI into a judgement step, add the review step at the same time.
If the process currently runs on spreadsheets, it is also worth asking whether it should move into a proper business system before automating it.
Summary
- RPA is good at repeating fixed procedures; AI is good at reading and deciding.
- Workflows run a defined flow; AI agents work out the steps themselves.
- Start by separating fixed tasks from tasks that need judgement.
- When combining, give each approach only the one step it does best.
- Check right after AI output, before irreversible actions, and whenever something stops.
APOUL OCR Reader