How to choose an AI adoption consultancy (without getting sold hype)

"AI consulting" means anything today: from building a WhatsApp bot to redesigning how an entire organization makes decisions. Before you hire, it helps to know what to look for.

These are the six signals of a good AI adoption consultancy:

• Experience in your sector, not just in AI. A consultant who has worked in pharma, finance or healthcare understands your constraints: regulation, risk, decision cycles. Ask for real cases and references.
• They talk about business results, not algorithms. If the whole conversation is "models" and "parameters" and never "what changes in your P&L," be careful.
• Focus on adoption, not just implementation. Installing the tool is 20%. Getting people to change how they work is 80%. Ask how they measure adoption.
• Ability to execute, not just recommend. A consultancy without implementation is an expensive PDF. They should stay until the new workflow actually works.
• Upskilling and governance included. AI without training gets abandoned; without governance it becomes a risk. Both have to be in the proposal.
• A diagnosis before a prescription. Be wary of anyone selling you the solution before understanding your problem.

And three red flags:

• They promise "AI that pays for itself in 3 months" without having seen your operation.
• They sell a tool, not a change: they hand you the license and leave.
• They can't name a single adoption metric.

Choose for implementation capability and focus on adoption. Everyone has the technology; getting people to change, not so much.

At Kintara we work exactly on that part: real adoption, in pharma, finance and healthcare companies. If you're figuring out where to start, an honest diagnosis is always the first step.