Buyer's guide
How to choose an AI consultancy in Australia
Last updated
A fair guide to the four types of AI firm, how they compare, twelve questions to ask and the red flags to watch for.
What are the four types of AI firm?
Global and Big 4 consultancies bring deep strategy benches, industry research and the capacity to run large, multi-country programs. They fit enterprises that need board-level change at scale. A mid-sized organisation should check who will actually do the work, and how much of the effort goes into building and supporting the system.
Large Australian technology groups run infrastructure, licensing, cloud and support at scale, often with vendor partnerships. They fit organisations that want one provider for IT operations. Ask how AI work is staffed, whether recommendations are linked to products they resell, and who owns the code.
Multi-service delivery firms take one problem from strategy through integration, data, build and support with one senior team. Solve8 sits in this group, built for organisations from around 50 staff to large enterprises across several sites in Australia and New Zealand. Ask any such firm to show delivered work and how it proves value first.
Specialist product boutiques build one product or one type of AI very well, such as chat assistants or document extraction. They fit when your problem matches their product closely. Check how the product connects to your existing systems, where your data is processed and what happens if you outgrow it.
How the four types compare
| Global and Big 4 | Australian technology groups | Multi-service delivery firms | Specialist boutiques | |
|---|---|---|---|---|
| Strategy depth | Deep and research-backed | Varies, often platform-led | Practical, one process first | Focused on their product area |
| Build capability | Large teams, often with partners | Strong on infrastructure and platforms | In-house, strategy to support | Strong within their product |
| Integration with existing systems | Strong on large ERP programs | Strong within their vendor stack | A core skill across mixed systems | Depends on the product's connectors |
| Ongoing managed support | Available, usually at program scale | A core service | Optional, after handover | Product support and updates |
| Data sovereignty options | Depends on the delivery model | Often Australian data centres | Usually your own infrastructure | Depends on where the product is hosted |
| Typical engagement shape | Large, multi-month programs | Multi-year service contracts | Phased projects with decision points | Subscription or licence |
Questions 1 to 6: the work itself
Show us delivered work
Delivered work they can describe or demonstrate in detail, even where the client is under NDA.
Which process first?
Which single process would you fix first, and why that one?
How will you prove it?
What accuracy or time measure must the pilot meet before we commit more?
Which of our systems?
Which existing systems will you integrate with, and who owns each connection?
Who does the work?
Who exactly works on our project, and are they onshore or offshore?
What is fixed?
Is the fee fixed for each phase, and what is out of scope?
Questions 7 to 12: data, ownership and support
Where is data processed?
Where will our data be stored and processed, including backups and support access?
Is our data used for training?
Will any provider use our prompts, documents or outputs to train a model?
Who owns the code?
Do we own what you build, with documentation and admin access?
Who supports it after go-live?
Who monitors accuracy and fixes problems once it is live, and on what terms?
Can we stop?
What do we keep if we stop after the first phase?
Who makes the decisions?
Where does a person approve the output, and which decisions are legally reserved for a person?
Red flags
A number before discovery
A price or savings figure quoted before anyone has seen your process or data.
Proof you cannot check
Past results with no case study, product or reference you can verify.
Vague data answers
No clear answer on where prompts are processed or whether a vendor trains on them.
Lock-in
A proprietary platform you cannot run or change without the vendor.
Senior at the pitch only
The people who sell the work are not the people who deliver it.
Questions
What is the difference between an AI consultancy and an AI software vendor?
An AI consultancy works out which problem to solve and builds or configures a solution around your systems. A software vendor sells a product and supports its configuration. Many organisations use both, with the consultancy checking the product fits.
Should a mid-sized organisation hire a Big 4 firm or a specialist AI consultancy?
It depends on scale. A Big 4 firm suits large, multi-country change programs, while a mid-sized organisation often gets more from a firm where the senior people who scope the work also deliver it. Ask both types the same twelve questions.
What should an AI consultancy deliver in the first 90 days?
Expect a measured baseline for one process, a working version tested on your own data and a clear go or stop decision backed by numbers. If the first 90 days produce only slides and workshops, ask why nothing has been tested on real work.
How do I compare AI consultancy proposals?
Compare them on the same terms: which process, how success is measured, what is fixed in scope and fee, where data is processed, who owns the code and who supports it after go-live. A proposal with vague scope often costs more later.
How many AI consultancies should we shortlist?
Three is usually enough: firms of the types that fit your scale, each asked the same twelve questions. More than that turns selection into a long procurement exercise, and fewer leaves you without a fair comparison for scope, approach and terms.
Ask us the twelve questions
Bring the checklist to a first conversation and hold us to the same standard.
Fixed-fee phases, agreed before we start. Stop after any phase.