Microsoft Copilot often disappoints in enterprise settings, but practical strategies can help achieve genuine return on investment.
A punchy thread on Reddit argues that Microsoft Copilot is being pushed into enterprises with unrealistic claims and thin integration.
“Can we all agree COPILOT is crap”
“It’s not even embedded… in Excel, SharePoint, Power BI… so people don’t understand why it can’t do anything.”
It’s a familiar story: a vendor or partner pitches sweeping efficiency gains, but teams open their everyday tools and don’t see anything different. Expectations sky-high, outcomes ambiguous, and staff left wondering what they’ve paid for.
Let’s unpack why this happens, what’s fair criticism, and how UK organisations can make sensible, measurable progress without buying into hype.
The Reddit post’s core point is fair. If users expect Copilot to light up across Excel, SharePoint, and Power BI from day one, they’ll be disappointed. In practice, people have to know where to find it, how to invoke it, and what it can and cannot access. Without clear enablement, it feels invisible.
“100% efficiency everywhere” is a recipe for disillusionment. AI tools are assistive. They can draft, summarise, and accelerate routine tasks, but they don’t fix broken processes or dodgy data. If your SharePoint is a permissions maze or your spreadsheets aren’t consistently structured, Copilot won’t save the day.
If people don’t know when to use Copilot or what good prompts look like, adoption stalls. Many rollouts front-load licences but under-invest in training, guidance, and simple examples tailored to each team. The result: “It can’t do anything” becomes a self-fulfilling perception.
Even without getting into product minutiae, three practical truths apply to Copilot and most workplace AI:
Keep the scope narrow and tie each use case to a baseline metric (time spent, lead time, or rework). Measure before and after.
Based on the concerns raised, it’s worth stating where many teams do see benefits when expectations are grounded:
These are “assist” scenarios, not fully automated tasks. They shine when content is clear, sources are accessible, and the team has a habit of reviewing outputs.
If your core workflows sit outside Microsoft 365, or you need very specific automations, you might supplement with targeted tools. For example, teams that live in Google Sheets sometimes connect a model directly to a spreadsheet for structured tasks. I’ve written a simple guide on that approach here:
How to connect ChatGPT and Google Sheets (custom GPT)
Equally, some processes are better served by traditional automation (scripts, scheduled jobs, data quality checks) than by a general-purpose assistant. No AI tool will compensate for inconsistent data or unclear ownership.
The thread highlights a real gap between sales promises and day-to-day utility. Copilot is not magic, and it is not omnipresent by default. If you take the time to target a few solid workflows, tidy up access, train people, and measure impact, you can get value. If you expect a drop-in 100% efficiency boost, you’ll be disappointed.
For current capabilities and deployment guidance, see Microsoft’s official documentation:
And for context, here’s the original Reddit discussion that sparked this piece:
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