Your Subject Matter Experts Are Your Secret AI Advantage – If You Don’t Burn Them Out

Ask anyone who has led a successful AI project what made the difference and they will rarely say “the algorithm”.

They will talk about the people who understood the work in detail: the underwriters, case handlers, nurses, planners, schedulers and analysts who could explain the real world behind the data. These subject matter experts (SMEs) are your secret advantage. They know where the value is, what good looks like and where the traps lie.

The challenge is that AI projects often treat SMEs as an endless resource-inviting them to workshops, reviews and testing sessions on top of their full‑time jobs. Burn them out and your AI efforts will quickly lose credibility.

Why AI needs your SMEs so much

Modern AI tools can find patterns and generate content, but they are not magic. SMEs are essential because they:

• Help define which problems are worth solving.
• Interpret messy data and explain important context.
• Spot edge cases, loopholes and unintended consequences.
• Judge whether an AI‑suggested decision is sensible or dangerous.

Without them, you risk building technically impressive systems that do not fit reality.

The SME burnout pattern

It usually looks like this:

1. An AI project is announced with enthusiasm.
2. A handful of respected experts are invited to every workshop “because we really need your input”.
3. Meetings multiply; requests for sample cases, feedback and sign‑off land at short notice.
4. Their day job does not shrink, so evenings and weekends get squeezed.
5. After a few months, they become harder to book-or start politely declining involvement altogether.

Meanwhile, other colleagues miss out on the chance to contribute and build their own AI capability.

Designing SME involvement more thoughtfully

You can avoid this pattern with some deliberate choices.

1. Define the SME role clearly

Be explicit about what you need from SMEs at each stage:

• Problem definition and use‑case selection.
• Data understanding and labelling.
• Testing, validation and scenario analysis.
• Ongoing feedback once the system is live.

Clarify how much time this will take and what they can say “no” to.

2. Make space in their workload

If you treat AI work as something SMEs do only when everything else is done, it will always be squeezed.

Work with managers to:

• Reduce other responsibilities temporarily.
• Adjust targets so they are not penalised for spending time on AI projects.
• Recognise their contribution in performance reviews and promotion discussions.

Participation should feel like a valued part of their role, not a favour.

3. Broaden the pool

Rather than leaning on the same two or three “usual suspects”, build a larger community of SMEs who can contribute in different ways.

• Invite interested staff to short AI awareness sessions and clinics.
• Offer clear routes for them to get involved in future projects.
• Use rotational roles where people spend a few months as an “AI champion” for their area.

This spreads opportunity and reduces risk of burnout.

Giving SMEs tools, not just meetings

SMEs often feel that their time is wasted in poorly structured workshops.

Respect their expertise by providing:

• Clear questions and examples in advance.
• Simple annotation or feedback tools that fit around their day.
• Short, focused sessions that produce tangible outputs.

Where possible, show quick wins from their input so they can see the impact.

Keeping SMEs involved after launch

Once an AI system goes live, SMEs remain critical:

• They can help monitor whether outputs still make sense as context changes.
• They can identify new use cases or refinements.
• They can champion the system to sceptical colleagues.

Formalise this by giving some SMEs ongoing roles in your AI governance structures, with time and recognition to match.

Turning expertise into a multiplier

Handled well, SME involvement does more than make individual projects better. It grows a cadre of people across the business who:

• Understand both the realities of frontline work and the possibilities of AI.
• Can translate between technical and non‑technical teams.
• Model healthy, critical use of AI tools.

That combination is hard for competitors to copy.

Your AI advantage is not just the technology you buy; it is the people who know how to apply it. Protect and support your subject matter experts, and they will repay you many times over.