Bloated Content Makes Bad AI Decisions
When enterprises talk about AI readiness, many start by focusing on licensing and training. However, the most overlooked issue is the one AI cannot fix on its own: bad data. Specifically, redundant, outdated, and trivial (ROT) content stored across SharePoint, OneDrive, and Teams.
This data does not just take up space. It actively degrades the quality of AI responses, increases the risk of exposure, and undermines trust in AI-generated results. If your enterprise content is a mess, your Copilot will reflect that mess right back at you.
A 2024 Statista report found that over 60 per cent of corporate content in Microsoft 365 is either outdated or no longer accessed by users. That is a huge problem for AI models designed to summarise, interpret, or suggest based on your organisational data.
Bad Inputs Equal Bad Outputs
AI systems do not distinguish between relevant and irrelevant files unless explicitly told to do so. That means:
- Old and outdated project documents can show up in Copilot suggestions.
- Drafts or unapproved content might be summarised as final.
- Sensitive or deprecated information may surface in chats.
The result? Broken trust. End-users start second-guessing Copilot output, security teams worry about exposure, and IT inherits another layer of cleanup they were unprepared for.
Copilot Does Not Filter Your Mess
Microsoft Copilot does not inherently prioritise what is fresh, approved, or in-scope. It works with the data it can access. If your M365 environment is full of outdated meeting notes, duplicated PDFs, and orphaned Excel files, that is what Copilot will use.
Microsoft itself acknowledges this. Their Copilot Lab documentation encourages organisations to improve information architecture and prune legacy content before rollout. But most organisations do not. Because they do not know where to start.
How to Cut the ROT Before AI Eats It
Enterprises preparing for Copilot adoption should make ROT reduction a strategic initiative, not just for storage savings, but to directly improve AI reliability.
Here is how forward-looking organisations are tackling it:
- Content inventory and tagging: Identify all SharePoint and OneDrive locations with unmanaged or outdated content.
- Owner and usage insights: Surface which sites and files have no recent activity or active owners.
- Automated retention policies: Apply rules to flag or archive ROT content.
- Pre-Copilot data audits: Review what Copilot would access if deployed today.
- Content lifecycle policies: Tie Copilot readiness to ongoing data hygiene.
These steps are not theoretical. Rencore Governance customers apply them today to prepare their digital workplace for a more controlled and effective Copilot rollout.
AI Governance Starts With Clean Data
Too many organisations assume that AI governance starts once the system is live. But by then, it is already too late.
Real governance starts with the data. If your Copilot is generating output based on years of digital debris, no risk policy will protect you from reputational damage or misinformation.
Your first step in Copilot governance is not policy. It is a data diet.
Clean content leads to better prompts, safer decisions, and a more trusted AI experience for everyone.
Over to you
To learn how Rencore Governance helps reduce ROT and improve AI outcomes. After all, AI readiness is as much about getting ready as it is about remaining ready! Reach out to us if you have further questions or if you are interested in a demo of our brand new Copilot and AI Governance solution.
