Evaluating Microsoft 365 governance software with AI

Last week, I did what millions of software buyers now do every day. I asked AI to compare several Microsoft 365 governance platforms, and less than thirty seconds later I had a beautiful comparison table. Every product looked remarkably similar.

It looked polished, logical, and authoritative. And that's exactly when I realized I'd fallen into what I now think of as the authority trap.

When information is presented clearly, confidently, and objectively, we assume it's accurate. AI is exceptionally good at creating that impression, not because it's trying to deceive us, but because our brains have always associated confidence with credibility.

The problem wasn't that AI had made everything up. It was subtler than that. AI had synthesized information from across the internet and presented it as though every capability carried the same weight. As someone who knows these products well, I knew those checkmarks weren't telling the whole story. Far from it.

How AI changed the way buyers evaluate governance software

Five years ago, software buying looked very different. Most first meetings started with, “Tell me about your company.”

Today, buyers often know who we are before we ever meet. They've compared vendors, read reviews, watched videos, and asked ChatGPT, Claude, Gemini, Copilot, or Perplexity to summarize the market before they've ever spoken to a salesperson.

I think that's fantastic. AI has improved the buying process. Buyers show up better informed, they ask better questions, and they spend less time listening to generic company overviews and more time discussing real business problems. That's exactly what good technology should do.

But this is where we need to be careful. The biggest risk isn't that AI occasionally gets something wrong. It's that AI is exceptionally good at sounding certain, and those are two very different things.

As Gen X, we grew up learning that just because something appeared in print didn't make it true. Then the internet arrived, and we learned that just because someone published something online didn't make it true either. Somewhere along the way we forgot that lesson, because now, if AI presents it in a beautifully formatted table, we're ready to treat it like gospel. That's... optimistic.

Confidence isn't evidence

Take lifecycle management. Ask AI to compare several governance platforms and it'll often tell you they all support it. Technically, that's true. But the operating model behind that single checkmark can be completely different.

Those aren't implementation details. They're entirely different operating models.

The same thing happens with Copilot readiness. Almost every vendor today claims to be “Copilot ready,” a phrase that often promises more than the rollout actually delivers. Does that mean the platform helps you spot oversharing before Copilot surfaces sensitive information? Does it improve your information architecture? Does it automate governance before rollout? Or does it simply integrate with Microsoft 365?

If every vendor claims to be Copilot ready, you've learned exactly one thing: marketing departments attend the same conferences.

Guest management is another good example. AI may tell you three products support it. Can they automatically expire guest access, restrict invitations by domain, require business justification, support recurring access reviews, and bulk-remove external users? One checkmark can represent six completely different experiences.

This gap between the label and the lived experience isn't unique to AI comparisons. Based on Orchestry data, only 13% of Microsoft 365 admins could accurately describe how SharePoint's “Copy link” sharing default inherits permissions. If most admins can't describe how a single feature behaves, a one-word checkmark summarizing it was never going to be enough.

Which brings me to the biggest trap in software evaluation: AI compares nouns. Buyers experience verbs.

Provision. Approve. Review. Archive. Restore. Delegate. Notify. Govern.

Software isn't purchased because it has features. It's purchased because of how those features work in the real world.

Use AI to prepare for the conversation, not to replace it

One of AI's greatest strengths is helping buyers get informed before the first meeting. The mistake is assuming the evaluation is complete before you've spoken to anyone.

Think of AI as the colleague who spent the weekend researching your project. You'd absolutely read their notes. You probably wouldn't sign a multi-year agreement based solely on them.

The best software evaluations don't happen when every box gets checked. They happen when every assumption gets challenged.

A software evaluation checklist for comparing governance tools with AI

1. Use AI to understand the market. Ask which categories of product solve your business problem. That's exactly what it should be doing.
2. Ask AI where it's uncertain. Instead of accepting the answer, ask: “Which parts of this comparison are based on documented evidence, and which are assumptions or commonly repeated claims that should be independently verified?” You may be surprised how nuanced the answer becomes.
3. Make AI argue with itself. Try: “Challenge your own conclusions. If you were evaluating these vendors for a large enterprise, what parts of your comparison would concern you or require validation during a live demonstration?” Now AI becomes your skeptic instead of your cheerleader.
4. Compare outcomes, not features. Instead of “Compare Vendor A and Vendor B,” ask: “Compare how Vendor A and Vendor B accomplish the same business outcome. Highlight differences in automation, manual effort, administrative overhead, implementation complexity, licensing assumptions, user experience, and long-term administration.” That's where the meaningful differences start to appear.
5. Separate evidence from marketing. Ask: “Which capabilities are consistently documented across multiple authoritative sources, and which rely primarily on vendor marketing or third-party summaries?” Not every claim deserves the same confidence.
6. Let AI prepare your demonstration. This might be my favorite prompt: “Based on this comparison, what are the ten most important questions I should ask every vendor to validate your conclusions?” AI shouldn't reduce the number of questions you ask vendors. It should improve their quality.
7. Ask for proof. Never stop at “Does your product do this?” Ask to see it. Show me the workflow. Show me the approval process. Show me the end-user experience. Show me what happens when something fails, and show me how it's restored. Features are easy to describe; workflows are much harder to fake.

That last step is where the checkmarks either hold up or fall apart, and it's the gap Orchestry was built to close.

Instead of a “lifecycle management: yes” checkbox, you see the workflow itself: delegated lifecycle decisions routed to the workspace owner as a one-click action, and item-level permissions reporting that names the specific sharing link that broke inheritance. The claim and the workflow are the same thing.

One final prompt

Before making a significant investment, ask AI one more question: “If you were advising a CIO on a multi-year software investment, what information would you refuse to rely on AI for, and instead insist on validating through a live demonstration, customer references, product documentation, or direct conversations with the vendor?”

That may be the most valuable answer AI gives you.

The bottom line

AI has fundamentally changed software buying, and I wouldn't go back. It helps us understand unfamiliar markets faster than ever, ask better questions, and arrive at vendor meetings ready to discuss outcomes instead of brochures. That's exactly what good technology should do.

But let's not confuse a polished answer with a proven one. Due diligence doesn't go away in an AI world; it gets faster, and the work shifts from gathering information to pressure-testing it. What AI has changed is how quickly we gather information. How good decisions actually get made, through curiosity, skepticism, context, and experience, hasn't moved at all.

And occasionally, a good decision still comes down to looking at a beautifully formatted comparison table and saying, “That doesn't seem quite right...”

Because the future doesn't belong to the people who use AI the most. It belongs to the people who know when not to believe it.

See the workflow, not the checkmark

The fastest way to get past the checkmarks is to see the workflows for yourself. If you want to pressure-test what you've read about any governance platform against what actually happens in your own Microsoft 365 tenant, that's exactly what an Orchestry walkthrough shows you: the workflow behind every claim. See it in your environment at orchestry.com/demo-request.