AI Automation in Wales
Most AI automation projects fail because the wrong process was chosen, not because the technology could not do it. AI Wales assesses which of your processes are genuinely worth automating, what the return actually looks like, and builds the proof of concept before anyone commits to a rollout.
How an AI automation project runs
Process assessment
We map candidate processes, volume, current cost and failure modes, then rank them by return and risk. Output is a prioritised list, not a pitch.
Feasibility and tool selection
For the top candidates: off-the-shelf, fine-tuned, or custom? What data exists, who owns it, and what does governance require?
Proof of concept
Build the smallest version that proves or disproves the case, measured against the current process rather than a demo.
Deployment and handover
Integration with live systems, human review points, monitoring, and training for the people who will run it.
Processes that automate well
These come up repeatedly across Welsh businesses, public sector bodies and universities. Not every one will suit your organisation — that is what the assessment is for.
Document and invoice processing
Extracting structured data from PDFs, scans and email attachments that arrive in inconsistent formats.
Enquiry triage and routing
Classifying inbound customer or citizen contact and routing it to the right team with a drafted first response.
Compliance and quality checks
First-pass review against policy or regulation, flagging exceptions for human decision.
Reporting and summarisation
Turning case notes, transcripts or operational data into consistent written summaries.
Data cleaning and matching
Deduplicating and reconciling records across systems that were never designed to talk to each other.
Knowledge retrieval
Letting staff ask questions of internal documentation and get answers with a citation they can check.
Frequently asked questions
What is AI automation?
AI automation uses machine learning or language models to carry out work that previously needed a person — reading and routing documents, extracting data from unstructured text, drafting responses, or making a first-pass decision that a human then reviews. It differs from traditional automation, which follows fixed rules, because it handles variation and ambiguity that rules cannot describe.
Which business processes are worth automating with AI?
The best candidates are high-volume, repetitive, and involve unstructured input — invoice and document processing, customer enquiry triage, claims assessment, compliance checks and report drafting. Processes that are low-volume, highly variable, or carry serious consequences when wrong are usually poor first candidates, whatever the technology can do in principle.
How is AI automation different from RPA?
Robotic process automation follows explicit rules and breaks when the input changes shape. AI automation learns patterns from examples, so it tolerates variation — a supplier changing their invoice layout, or a customer phrasing a request in an unexpected way. In practice the two are often combined: AI handles interpretation, RPA handles the deterministic steps that follow.
How long does an AI automation project take?
A process automation assessment typically takes two to four weeks and produces a prioritised list of candidate processes with an estimated return for each. A proof of concept on a single process usually runs four to eight weeks. Full deployment depends on how many systems are involved and what governance sign-off the organisation requires.
Does AI Wales build the automation or just advise?
Both. AI Wales runs the assessment, builds proofs of concept through AI Labs, and supports implementation. We are vendor-neutral and resell no platform, so the recommendation is whatever fits the process — including advising that a given process is not worth automating.