Here is an uncomfortable truth: most AI projects do not fail because the model is not clever enough. They fail because the data is messy, nobody owns the outcome, or security says “absolutely not” in week eight. 😬
The roles to have in place first
1. A business owner
Someone accountable for the problem being solved and the value delivered. Without this person, AI projects become science experiments.
2. A data engineer
Gets the data clean, connected and accessible. Usually the most important early hire.
3. A machine learning or AI engineer
Builds and evaluates the solution, whether that is a traditional model or a large language model with retrieval.
4. A cloud or platform engineer
Makes it secure, scalable and affordable to run.
5. A security and privacy reviewer
Ideally involved from day one, not at the end. Australian privacy obligations and customer trust both depend on it.
Roles you can add later
- MLOps engineers once you have more than one model in production
- Change and adoption leads as users come on board
- Prompt and conversation designers for customer-facing assistants
Start small, then scale
A focused team of four or five can deliver a meaningful proof of value in 8 to 12 weeks. Use contractors for speed, then convert the roles you need long-term.
👉 Read about the new AI roles employers are hiring, or tell us about your AI project.
Employer
Employer
