Let’s address the quick fix that too many teams use when SharePoint search results go sideways: manipulating search settings. It might seem harmless—helpful, even—but when used as a band-aid for deeper problems, search manipulation can actually backfire. Not only does it fail to address the root cause of findability issues, it also creates long-term technical debt and undermines your readiness for AI tools like Microsoft Copilot.
Let’s break down what’s going on.
When Search Fails, Don’t Just Fix the Search
I’ve seen this pattern time and time again. Users complain they can’t find documents in SharePoint. Search results feel irrelevant, buried, or just plain random. The typical response? IT jumps into search settings: adjusting result sources, writing query rules, boosting keywords and tweaking ranking models.
It feels productive, but it’s the wrong fix.
Search manipulation treats symptoms, not causes. If your underlying information structure is a mess, no amount of search trickery will fix it. It’s like patching cracks in a crumbling wall instead of reinforcing the foundation.
You’re Adding Technical Debt, Not Value
Every custom search configuration adds complexity. One query rule becomes two. One ranking tweak becomes a whole catalogue of exceptions. over time, you’re left with a tangled web of search rules that need constant maintenance, documentation and internal expertise to manage.
And here’s the risk: what happens when the person who configured all of this leaves? Or when SharePoint rolls out a search update that conflicts with your custom setup?
Suddenly, your quick fix becomes a liability. What looked like a clever solution starts breaking things—or worse, becomes completely unmanageable.
AI Will Inherit Your Mess
Now let’s talk about AI, because that’s where this becomes a critical issue.
Tools like Microsoft Copilot thrive on clean, structured and logically organised content. AI isn’t magic—it’s pattern recognition. When your SharePoint environment is inconsistent, disorganised, or overloaded with manual search customisations, the AI has to work around those flaws rather than through them.
That means poor architecture + search manipulation = unreliable AI output.
For example, if you’ve artificially boosted certain documents in search just to make up for bad folder design, Copilot might mistakenly assume those documents are more important than they really are. You’ll start getting odd recommendations or irrelevant content surfacing at the wrong times.
Worse still, manipulated search results can create inconsistent user experiences. Users may find content via search but not through navigation or web parts. This inconsistency confuses both people and AI and makes it harder to predict user behaviour accurately.
Fix the Foundation First: IA Over Hacks
The real solution to SharePoint findability problems is—and always has been—information architecture.
That means:
- Structuring content in a way that reflects how people work
- Using consistent naming conventions and metadata
- Creating navigation paths that mirror user mental models
- Avoiding complex, conflicting permission layers
- Keeping folder structures shallow and logical
When you invest in proper IA, search improves naturally. No tricks. No band-aids. Just well-organised content that’s easier to find across every discovery method—search, navigation, web parts and yes, AI.
Future-Proof Your SharePoint
The payoff of good IA isn’t just better search today—it’s lower maintenance, smoother migrations, better compliance, and a stronger foundation for future technologies.
If you’re serious about preparing for Copilot and AI integration, stop masking problems with search manipulation. Start fixing them where they begin: your information architecture.
