The SME Finder Copilot Agent - Useful Template or Org Chart in Disguise

Microsoft has been quietly building out a library of agent templates inside Microsoft 365 Copilot that are designed to solve specific business problems without requiring a developer to write code from scratch. The SME Finder template is one of the more interesting ones. The idea is simple. An employee asks "who is the right person to talk to about our SAP integration architecture" and the agent returns a ranked list of internal subject matter experts with evidence, plus a draft outreach message.

The promise is good. Anyone who has worked in a large Australian organisation knows that finding the right person to ask is half the battle. The reality of what the template delivers is more nuanced. I have been building and reviewing agents on the Microsoft 365 Copilot platform for clients across professional services, financial services and mining, and the SME Finder is a useful starting point but it is not a magic answer.

Here is the honest take.

What it actually does

The SME Finder template builds a declarative agent that searches across the standard Microsoft 365 graph - SharePoint documents, Teams channel posts, Outlook emails, calendar meetings, and the organisational People data - to identify likely subject matter experts on a topic. It returns a ranked list with cited evidence, so you can see why each person was suggested.

The features that ship with the template are well thought out. You can ask it to find experts on any topic. You can ask it for "hidden gems" who are not in leadership but have strong individual contributor expertise. You can ask it to identify who owns a SharePoint site or an internal app. It can prepare you for a meeting with a suggested expert by generating talking points based on their documented work. It can suggest mentors with five plus years in a domain.

The standout feature, in my view, is the outreach message generation. After identifying the expert, the agent drafts a Teams or email message in your voice, with the right level of formality for the recipient's seniority, with a specific ask and an evidence-based hook. That is the part that turns the agent from "search tool" into "thing that actually saves time."

Where this works well

For organisations with strong Microsoft 365 adoption and clean internal collaboration patterns, this template delivers value out of the box. The signal sources it uses are the ones that genuinely reflect expertise in those organisations. If someone has authored three SharePoint articles on a topic and presented on it in Teams channel posts and attended six meetings about it, they almost certainly know about that topic.

We have seen this work well at professional services firms where consultants are constantly searching for "who has done this kind of work before." The agent surfaces the right person and saves a thirty-minute search through SharePoint. It also works at engineering firms with deep technical specialisations where the org chart does not reflect actual expertise. The hidden gems feature finds the senior individual contributors who are doing the real work but are not in management.

For client engagements where we are deploying Microsoft 365 Copilot extensibility, the SME Finder is often the first agent we recommend as a pilot. It is high value, low risk, and easy to demonstrate working in the first week.

Where it falls short

There are several places where the template runs into trouble.

The first is in organisations where Microsoft 365 is not the primary collaboration tool. If your team lives in Slack and your documentation is in Confluence and your meetings are recorded in Zoom, the SME Finder is going to miss most of the signal. The agent only knows about M365 data. You can extend it with connectors but that requires real effort and is not what the template gives you out of the box.

The second is the assumption that activity equals expertise. The agent infers expertise from documented work and meeting participation. That works when the experts are also the people who write things down and attend meetings. It fails when the real expert is the quiet senior engineer who never writes documentation and avoids meetings, while the most documented person is a project manager who organises everything and knows nothing.

We have seen the agent confidently surface PMs and team leads as "experts" on technical topics because they participated in the relevant meetings and emails. That is not insight, that is calendar mining. The agent has no way to distinguish "person who scheduled the meeting" from "person who answered the technical question in the meeting."

The third issue is the privacy and politics dimension. In some organisations, surfacing employee activity data, even data they already produced and that is technically searchable, feels invasive. We have had conversations with HR teams about whether the SME Finder counts as workplace monitoring. The answer is no, it is using data the organisation already has, but the perception matters. Plan how you communicate the deployment.

The evidence problem

The template emphasises "evidence-based" expert identification, and it does cite sources for each recommendation. This is good. But evidence-based is only as good as the evidence. If your SharePoint is full of stale documents from a project that wrapped up four years ago, the agent might confidently recommend an expert who has not touched that topic since 2022.

The agent has some weighting for recency but it is not perfect. We have seen it recommend people who left the team but are still on the org chart. We have seen it recommend people based on a single comment in a Teams thread that they were not actually engaged with.

In a real deployment, you almost always need to layer in explicit signals to supplement the activity-based ones. The Microsoft documentation suggests connecting a SharePoint list of skills and certifications, which is a good idea. Even better is connecting your HR system if it has structured competency data. We have done both of these on enterprise engagements and the recommendations get significantly more accurate.

If you are looking at this template for use in AI for professional services, where finding the right consultant for a project is genuinely a competitive advantage, the structured skills data overlay is essential. Do not deploy it without that supplementation.

Extending the template

The template is designed to be extended. The Microsoft documentation suggests three areas for extension - adding structured expertise data via SharePoint, layering a CRM connector for customer-facing expertise, and tailoring the outreach message format.

We would add a fourth. Tune the agent instructions to match your organisation's specific terminology and seniority structure. The default template uses generic terms like "Director-level and above" which may not map cleanly to your organisation. If your org uses "Principal" and "Distinguished" titles, or has matrix reporting, or has external contractor populations that the agent should exclude, all of that needs to be in the instructions.

The outreach message tuning is also worth real effort. The default tone is pretty generic. Australian business communication has a specific register that the agent does not get right out of the box. We typically adjust the instructions to be less formal, less American, and more direct. The difference between "I hope this finds you well, I wanted to reach out regarding..." and "Hi Sarah, quick question about the SAP integration if you have five minutes..." is the difference between a message that gets ignored and one that gets a reply.

Compliance and deployment notes

The template ships with some disclaimers about verifying accuracy before making decisions, and you should keep those in place. The agent is suggesting people to contact, not making business decisions, but the line gets blurry when the agent suggests an expert and the user takes that suggestion to a procurement decision or hiring conversation. Always review the cited evidence.

The other thing to plan for is what happens when the agent surfaces someone who does not want to be the SME for that topic. The reality is that being identified as an expert generates inbound messages, and some people are happy to take those and others find them disruptive. Build a way for employees to opt out of being surfaced, or at minimum to feed back when they have been mis-identified.

If you are working through Microsoft 365 Copilot rollout in an Australian enterprise, the SME Finder is one of the more polished templates Microsoft has shipped, but it still needs thoughtful deployment to avoid becoming an annoyance.

The bottom line

The SME Finder template is genuinely useful. It is the kind of out-of-the-box agent that you can deploy in a week and start getting value from immediately. It is also limited in ways that are easy to underestimate. Activity does not always equal expertise. The recommendations are only as good as the underlying data. The outreach messages need tuning for Australian context.

Treat it as a starting point. Use it as the foundation for what eventually becomes a more sophisticated expertise discovery capability in your organisation. Layer in structured skills data. Tune the instructions. Communicate clearly to employees how it works and what they can opt out of.

If you get those things right, this is one of the better Microsoft 365 Copilot agent templates currently available. If you skip them, it will deliver a mediocre experience and reinforce the perception that AI agents are oversold demos. The difference is in the deployment work, not the template itself.

Reference: Microsoft 365 Copilot SME Finder agent template documentation