Key takeaways
- Consulting looks forward: what should we do and in what order
- Auditing looks at what exists, or at how ready you are
- If you already run AI, audit first; if not, start with consulting or a readiness audit
Consulting is about decisions
AI consulting helps you decide where AI is useful, which technologies fit, and how to sequence the work. The output is direction: a prioritised list, an architecture recommendation, a roadmap.
It suits teams that know they want to do something with AI but are not sure what, or that have several ideas and need to choose.
An audit is about evidence
An audit examines something specific. A readiness audit looks at whether your processes, data, and systems can support AI. A systems audit looks at an existing AI tool: how reliable it is, how it handles data, where it fails. An opportunity audit ranks your processes by automation potential.
The output is findings: what is true today, what the risks are, and what to fix first.
What an audit is not
It is not a certification, a regulatory approval, or a security guarantee. It is an engineering assessment by people who build these systems. If you need formal certification, that is a separate process with a different body.
Which should you buy first?
If you have no AI in production, start with consulting or a readiness audit. If a chatbot or automation is already live and you have doubts about accuracy, cost, or data handling, audit it before building more.
They also combine well: an audit often produces the evidence that makes a consulting roadmap realistic.