Hire an AI Specialist who turns AI tools into real productivity

Look for practitioners, not just enthusiasts

Many people talk about AI. Fewer have helped real teams change how they work. Ask candidates for examples of specific tasks they improved, how they measured the improvement and what went wrong along the way.

Start with an inventory of current use

Your specialist should first understand which tools staff already use and for what. This reveals both quick wins and risks, such as confidential information entered into consumer tools.

Pick three high-value use cases

Focus early effort on three tasks that many people perform, such as drafting client emails, summarising documents or preparing reports. Narrow focus produces visible wins faster than broad training.

Build a policy people will follow

A short, practical AI policy with examples is far more effective than a long legal document. Your specialist drafts it with input from leadership and, where needed, your legal or compliance adviser.

Report impact to leadership

Monthly updates on adoption, time saved and examples of wins keep leadership engaged and help justify the next phase, such as automation or custom agents.

A sample job summary for an AI specialist

A clear summary might read: we are looking for an AI specialist to help our team adopt AI tools safely and productively. You will identify high-value use cases across departments, configure our business AI tools, write and maintain a prompt library, run practical training and track adoption and time saved. You will also draft our AI use policy with leadership. This role suits someone practical, patient with beginners and realistic about what AI can and cannot do.

Red flags when hiring an AI specialist

Be wary of candidates who promise dramatic results without asking about your processes, or who recommend many tools before understanding what your team already uses. Hype is easy, while practical adoption is hard. Also watch for weak awareness of privacy and accuracy risks. A credible AI specialist talks about verification, data settings and policies as naturally as they talk about productivity gains.

What a good first week looks like

In week one, your AI specialist surveys current AI use, interviews a few people from each team and reviews the tools in your software stack. They identify obvious risks, such as confidential data being pasted into consumer tools, and propose quick fixes. They also shortlist three candidate use cases for the first training sessions. The week should end with a short plan you can share with leadership.

AI specialist or AI developer?

An AI specialist helps people use AI tools well. An AI developer builds AI into software, such as your product or internal systems. If your goal is faster writing, research, summarising and analysis across the business, start with a specialist. If you need custom features, integrations or agents, you need development capability. Many businesses begin with a specialist, then hire developers once clear automation opportunities emerge.

Tools and access to prepare for your AI specialist

Confirm which AI tools are already licensed and who administers them, and provide admin access to configure business settings such as data retention and sharing controls. Share your IT and privacy policies, the list of systems that contain sensitive information and contacts in each team who can help with interviews. A shared space for the prompt library, such as a Teams channel or Notion page, gives the specialist a home for training material from the start.

Measuring the impact of your AI specialist

Measure adoption first: the share of staff using approved AI tools each week and the number of use cases in regular use. Then measure value through short surveys of time saved and quality improvements on key tasks. Track risk indicators too, such as policy breaches or incidents. Share results with leadership monthly, including specific examples, because stories of real wins drive further adoption more effectively than statistics alone.

Interview questions to ask a AI specialist

1. How would you discover the best AI use cases in our business?
2. Show me a prompt you would use to summarise a long client document.
3. How do you explain AI risks to non-technical staff?
4. Which AI tool would you recommend for a Microsoft 365 business, and why?
5. How do you measure whether training worked?
6. Tell me about an AI rollout that did not go to plan.
7. When should a task move from an AI tool to an automated workflow?
8. How do you keep up with changes in AI tools?

A 30, 60 and 90 day plan for your new AI specialist