Good question and the honest answer is that it's less "Copilot vs. other AI tools" and more "different jobs."

Where Copilot wins is context. Because it's grounded in your own F&O data, Dataverse and M365 content, and it inherits your security roles, it can summarise a vendor record, explain a variance, or draft a customer follow-up using your actual numbers. A general-purpose chatbot can't do that unless you paste the data in yourself which most finance teams shouldn't be doing anyway.

Where general tools (ChatGPT, Claude, Gemini) still win is open-ended reasoning: writing documentation, drafting policies, explaining an accounting treatment, cleaning up a spec before you hand it to a developer. No ERP context needed, and no licence per user.

If you did the training but haven't used it, my suggestion would be to pick one repetitive process rather than trying it broadly. The ones that tend to pay off fastest in F&O:

- Embedded summaries on records, workspaces and forms low risk, immediate time saving

- Vendor invoice capture and matching

- Collections and customer communications

- Bank reconciliation matching suggestions

- Copilot in Excel/Teams/Outlook on the M365 side, which people often underrate

The 2026 release wave 1 stuff is pushing further into agents that can actually run multi-step processes with human approval, so it's worth watching even if you're not ready today.

Two caveats from experience: output quality tracks your master data quality very closely, so if your vendor or customer records are messy you'll be disappointed. And most failed rollouts we see aren't technical they're adoption. People need to be shown it inside their actual daily work, not in a training session.

Full disclosure, I work at Synoptek (we're a managed IT services provider), so I see this from both sides we use Copilot internally across our own marketing, service desk and reporting workflows, and we also help clients with the readiness side before they turn it on: permissions and data-governance cleanup, identifying which processes are actually worth automating, and then adoption support afterwards. The readiness part is boring but it's usually what separates the deployments that stick from the ones that quietly get abandoned.

Happy to share more detail on any of the specific use cases if useful.

Microsoft Copilot