In the ever changing world of enterprise GenAI, the new Researcher Agent functionality in Microsoft 365 Copilot started me questioning whether I should retire my own Copilot Studio developed M365 Research Agent. So, I tested it and really only found one minor flaw (that I couldn’t select sub-folders from SharePoint sites).
What is it?
The Researcher Agent is Microsoft’s reasoning-agent built into Microsoft 365 Copilot that is purpose-designed to handle multi-step, complex research tasks. It leverages Deep Research models in combination with the Microsoft 365 ecosystem – your files, chats, meetings, emails and the wider web – to deliver insights anchored in your context (which you can control).
In practical terms, you can ask Researcher to explore a business topic, pull together internal and external data and generate a structured report.
As I mentioned, I have my own custom M365 research agent built in Copilot Studio pointing at around 400 PDFs in two SharePoint folders and I was interested in how they compared. Here’s a summary of my observations:
- My Copilot Studio M365 Agent was much faster with a response.
- Both Agents used a total of 10 documents in their references and they were different documents (which in itself is interesting – I have definitely seen my M365 Copilot Studio Agent reference as many as 20 documents in the past.).
- The Copilot Researcher Agent asked clarifying questions (as Deep Research models tend to do) and while it took longer it produced a much higher quality report (it was more complete).
- The Copilot Researcher Agent has an additional option to open the resulting document in Word which worked well.
- The Copilot Researcher Agent only allowed adding a SharePoint Site, not individual folders, which is a bit of a problem when I only want it to look at specific folders in the site.
What does it mean from a business perspective?
From an enterprise standpoint, the arrival of Copilot Researcher with these additional options opens up several potential shifts:
- Reduced custom-agent overhead: If the standard Researcher Agent can serve much of the research workload, businesses may reduce the need to build and maintain many bespoke agents.
- Faster time-to-value: With Microsoft packaging this as part of the Copilot offering, organisations can unlock research-AI faster rather than building from scratch.
- Focus shifts from build to optimise: Rather than building a custom agent, companies may shift to optimising prompts, tuning data sources or layering value-add on top of Copilot Researcher.
- Competitive differentiation via specialist agents: With the baseline agent handling many tasks, the business value of custom agents becomes sharper: the differentiator will be the “unique domain logic”, “industry-specific content” and tool usage that bespoke agents offer.
What do I do with it?
Here are concrete next-steps you should consider:
- Pilot the Researcher Agent against your existing data: Identify a set of your PDF or document collections (e.g., stored in SharePoint) and run a comparison: your custom agent vs Researcher. Measure accuracy, relevance, speed and user satisfaction.
- Computer Use Agent: Decide whether or not to block the use of the Computer Use Agent portion – whether you want you team to be able to use the browser based capability of the Researcher Agent (access to this can be controlled)
- Map the feature gaps: Where your custom agent performs better, document the delta (for example: custom prompt logic, additional tools). Decide if you can live without those for the standard agent, or if you still need a custom build.
- Train user-community and change-management: Since the standard agent may be simpler to deploy, launch a user adoption programme (especially for business-teams) so they know the difference between “just use Researcher” and “use a custom agent”.
- Monitor evolution and vendor roadmap: Since Microsoft’s offering is still early, keep track of updates (e.g. connectors). Be ready to reassess regularly: does the standard agent now fully replace custom builds or not?
The introduction of these features for Microsoft’s Copilot Researcher Agent is a big step towards a very high-quality, standard research assistant baked into Microsoft 365. For those of us who have taken the custom-agent path, it offers potential for simplification. But, as I found in my own testing with my Copilot Studio agent, it may almost do everything, but not quite yet. The key now is to experiment, measure, and decide: is this standard agent enough, or do you (and I) still maintain custom builds?
I’d encourage you to spin up a pilot this week, benchmark what you’ve already done, and explore how Researcher could help.