Is AI automation just RPA with AI bolted on?

No. RPA vendors have added AI features, but the architecture differs: RPA starts from a recorded sequence of clicks, while AI automation starts from an interpreted decision and then calls APIs or code to act. Bolting a model onto a brittle click script usually inherits the brittleness.

Should we replace our existing RPA bots with AI?

Only the ones that keep breaking. Bots that run reliably against stable, structured data are doing their job. The candidates to replace are the ones that need constant babysitting because the input varies — that variability is exactly what AI automation handles.

Which is more reliable, RPA or AI automation?

RPA is more deterministic on a fixed input and less reliable when the input changes. AI automation is the reverse. Reliability in production comes from the design around either: validation, logging, retries and a human approving anything consequential.

Do we need developers to run AI automation?

You need someone to build it properly and someone to own it afterwards. We build and then hand over with monitoring in place, or run it as a managed layer. What you should not do is let a workflow that touches customers or cash go unowned.

How do we decide which processes to start with?

Start with high-volume, repetitive work that is already written down and where a mistake is cheap and visible. Our free 2-minute scan ranks your processes, and the £499 AI Ops Audit returns a costed, sequenced plan.

ANSWERS · COMPARISON

AI automation vs RPA: what's the difference?

The short answer

RPA follows fixed rules and breaks when the input changes; AI automation reads messy, human inputs — emails, PDFs, photos, calls — decides what they mean, and acts inside your existing systems. RPA suits high-volume, identical, structured tasks. AI automation suits the judgement-shaped work in between. Most working systems use both: AI to interpret, rules to execute.

The core difference

Robotic process automation (RPA) is a scripted robot. You record or code the exact steps — open this screen, copy that field, paste it there — and the robot repeats them. It is fast, cheap to run and completely literal. If a supplier renames a column or a portal moves a button, the robot fails.

AI automation puts a model in the decision seat. Instead of being told where the invoice number lives, it reads the document and works it out. Instead of matching an exact subject line, it understands that a customer is chasing a delivery date and routes it accordingly. The trade is predictability for tolerance of mess.

Side by side

	RPA	AI automation
Input it handles	Structured, consistent fields	Emails, PDFs, photos, calls, free text
How it decides	Rules you write in advance	A model interpreting context, with rules around it
When something changes	Breaks until someone rewrites the script	Usually copes; drifts rather than snaps
Output certainty	Deterministic and repeatable	Probabilistic; needs review on consequential steps
Best fit	High volume, identical, boring	Variable, human-shaped, judgement-light
Main risk	Brittleness and maintenance load	Confident mistakes without a human check

When RPA is still the right answer

Moving thousands of identical records between two systems that will not change.
Overnight reconciliation between fixed reports with stable formats.
Screen-scraping a legacy system that has no API and no roadmap.
Anything where a wrong answer is unacceptable and the rules are genuinely complete.

When AI automation is the right answer

Inbound enquiries arriving by email, form and phone in no particular format.
Supplier invoices and delivery notes that all look different.
Site photos, scans and PDFs that need reading before anything can happen.
Drafting: quotes, chase emails, job notes, weekly summaries — with a person approving.

In practice you use both

The systems we build for UK operators tend to look like this: AI interprets the incoming mess and produces a clean, structured decision; deterministic code then executes it against the CRM, accounting system or job platform, with logging and a human approval step wherever money, safety or reputation is involved.

That split matters because it keeps the unpredictable part small and observable. The model never presses the button on its own; it decides what button should be pressed, and the rules-based layer does the pressing.

Cost and effort compared

An RPA script for a single stable task is cheap to build and expensive to keep alive — maintenance is the real cost, and it grows with every system upgrade upstream.

An AI automation workflow costs more to design well, because the work is in integration, evaluation and the approval path rather than in the model itself. In return it degrades gracefully instead of failing outright. A first production workflow with Forth Systems typically lands between £6,000 and £25,000 depending on how many systems it touches, plus a monthly running cost.

Frequently asked questions

Is AI automation just RPA with AI bolted on?: No. RPA vendors have added AI features, but the architecture differs: RPA starts from a recorded sequence of clicks, while AI automation starts from an interpreted decision and then calls APIs or code to act. Bolting a model onto a brittle click script usually inherits the brittleness.
Should we replace our existing RPA bots with AI?: Only the ones that keep breaking. Bots that run reliably against stable, structured data are doing their job. The candidates to replace are the ones that need constant babysitting because the input varies — that variability is exactly what AI automation handles.
Which is more reliable, RPA or AI automation?: RPA is more deterministic on a fixed input and less reliable when the input changes. AI automation is the reverse. Reliability in production comes from the design around either: validation, logging, retries and a human approving anything consequential.
Do we need developers to run AI automation?: You need someone to build it properly and someone to own it afterwards. We build and then hand over with monitoring in place, or run it as a managed layer. What you should not do is let a workflow that touches customers or cash go unowned.
How do we decide which processes to start with?: Start with high-volume, repetitive work that is already written down and where a mistake is cheap and visible. Our free 2-minute scan ranks your processes, and the £499 AI Ops Audit returns a costed, sequenced plan.