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RPA and AI: which automation fits

RPA follows fixed rules on stable screens. AI reads documents and handles variation. Many good solutions use RPA and AI together.

The short answer

Robotic process automation (RPA) mimics the clicks and keystrokes a person makes, following rules you define. It works well when inputs are structured and screens rarely change.

AI uses natural language processing and document understanding to read emails, PDFs and scanned forms, and copes when a layout changes. It needs human review on uncertain cases. Often AI reads and RPA or a direct connection does the entry.

Side by side

Side by side
	RPA	AI
How it works	Follows scripted rules and screen steps	Interprets content and context
Input types	Structured: fixed fields, spreadsheets	Unstructured: emails, PDFs, scans, free text
When things change	Breaks when screens or formats change	Copes with layout changes, needs monitoring
Exceptions	Escalates anything outside the rules	Handles some, routes uncertain cases to a person
Predictability	Same input, same output	Probabilistic, so checks and approval matter
Maintenance	Script upkeep as systems change	Quality monitoring and periodic tuning
Best fit	Stable, high-volume, rules-based tasks	Document-heavy work and tasks needing judgement

By use case

By use case
	RPA	AI
Invoice processing	Fixed-format invoices	Any supplier format
Data entry	Spreadsheet to system, exact fields	Documents to system, with checks
Customer enquiries	Not suited to natural language	Drafts replies for a person to approve
Scheduled reports	Well suited	Adds summaries and commentary
Compliance checks	Rule-based validation	Reads context, flags for review

How RPA with AI works together

AI reads
A supplier invoice or email arrives in any layout.
A person checks
Uncertain fields go to your team to approve.
RPA or an API enters
The approved result is keyed into your system.

Questions

What is the difference between RPA and AI?

RPA repeats the clicks and keystrokes a person makes, following rules you define, so it needs structured inputs and stable screens. AI interprets content such as emails, PDFs and scans, copes with variation and routes uncertain cases to a person for approval.

Is AI replacing RPA?

Mostly the two are converging. AI takes over the reading and classifying steps that made bots fragile, while RPA or a direct system connection still does the data entry. Organisations with working bots usually keep them and add AI at the front of the process.

How does AI in RPA work?

AI handles the steps a bot cannot, such as reading an unstructured invoice or classifying an email by intent, and passes a structured result with a confidence score. High-confidence results go straight to the bot or an API, and low-confidence ones go to a person first.

Which is cheaper to run, RPA or AI?

RPA is usually cheaper for simple, stable, high-volume tasks, with costs in bot licences and script fixes whenever a screen changes. AI costs more per transaction in model usage and monitoring, but it is cheaper wherever varied inputs would keep breaking RPA scripts.

We already have RPA bots. Should we replace them with AI?

Keep the bots that run reliably. Add AI where bots fail on unstructured inputs or raise constant exceptions, and replace a bot outright only when the underlying system now offers an API that removes the need for screen automation.

Is natural language processing the same as AI?

Natural language processing is one branch of AI: the methods that let software read, classify and generate human language. In automation it is what lets a system understand an email or contract, which RPA alone cannot do because it only follows fixed screen rules.