Fixing SharePoint: The Key to Successful AI Integration

The Real AI Bottleneck: Your Messy SharePoint

By now we all know – AI is here, and it’s reshaping industries. Enterprises are all desperately trying to badge up their products as ‘AI Powered’ and optimise their internal processes for efficiency and insight. But for many, an unexpected obstacle stands in the way – the state of their SharePoint sites.

It’s not as thrilling as a new generative model or as impressive as a shiny AI chatbot, but let’s be honest, AI in the enterprise is only as good as the data it works with. Unfortunately, the data in many organizations’ SharePoint sites is chaos, with sites popping up randomly, no metadata or document governance and no confidence of the content within those documents either.

The Untidy Foundations of Enterprise AI

When we talk about enterprise AI, we’re really talking about making sense of the vast volumes of internal data. For most companies, SharePoint is a natural starting point for this. Microsoft is at the foundation of a huge amount of businesses IT strategies and for this reason they’ve passively accepted SharePoint without really thinking about how its implemented. It’s where teams keep their documents, store procedural guides, manage collaborative spaces, and essentially host the organization’s knowledge, but how confident are you about your organisations setup?

SharePoint sites were often set up with good intentions but little planning. Over time, folders were duplicated, documents misfiled, permissions tangled, and much of the content went stale. When we add on top the complications Microsoft Teams brings (each Team has its own linked subsites, further increasing headaches for businesses that just make them without forethought). The resulting mess is more than just an inconvenience, it’s a significant blocker when trying to build effective AI models.

Rubbish In, Rubbish Out

We’ve all heard the phrase, “rubbish in, rubbish out.” It applies perfectly to AI implementations. When AI tools ingest poorly organized, redundant, or irrelevant content, the output suffers. Instead of insightful analysis or productivity-enhancing automation, you’re left with half-baked results that make stakeholders question the ROI of the AI initiatives.

Why is this happening? Because much of an enterprise’s data is like the junk drawer in the kitchen. It’s technically stored somewhere, but good luck finding that important document when you need it. Enterprises are struggling to derive value from AI because they haven’t done the hard work of tidying up first. Its not uncommon to never delete anything either, as without clear ownershup, ensuring the file isnt important is impossible. This can create even more innacurate answers by poluting the response with potentially old versions of the same files with unnapproved changes or similar.

SharePoint, The House That Needs Cleaning

One of the main reasons enterprises have neglected SharePoint organization is that the stakes weren’t always so high. Pre-AI, a little messiness was manageable, you could still find that important policy document eventually, and most teams could limp along with a few workarounds.

But as companies are now pushing towards internal AI tools, the cost of this neglect has skyrocketed. Search and recommendation models work best with well-labeled, high-quality data. Natural language processing tools trying to summarize knowledge need content that’s structured and coherent. And predictive models can’t make sense of a company’s best practices if those practices are buried across a hundred unmarked folders.

The challenge is that this problem is not glamorous to fix. It’s not about new technology or advanced AI algorithms; it’s about fundamentally rethinking how content is organized, managed, and kept up to date. It’s about ensuring that, when you point an AI model at SharePoint, the content it pulls in is trustworthy and complete.

How to Get Started

If you’re reading this and realizing your organization’s SharePoint is a candidate for a digital ‘Extreme Makeover’, you’re not alone. Here’s how you can start:

1. Start With an Audit: Understand what you have. Run a full audit of your existing SharePoint content. Identify what’s redundant, outdated, or trivial (the ROT).
2. Simplify Structures: Instead of a maze of nested folders, work on a flatter, more intuitive structure for each team’s SharePoint. Less complexity makes for better AI results.
3. Get Metadata Right: Tag your content correctly. The best AI tools rely on good metadata to make sense of unstructured content. Start labelling, tagging, and organizing so AI has a fighting chance.
4. Engage Your People: The technology won’t get better if the behavior doesn’t change. Make it part of your culture to keep content fresh, relevant, and easily findable.
5. Train Your People: Once youve defined what good looks like, make sure its trained out properly, reinforced as part of annual training cycles and is part of your new starter process so that everyone lives and breathes it.

The Bottom Line

AI is a powerful tool, but it’s not magic. It relies on clean, structured, well-organized data, to deliver value. Enterprises that recognize this are investing in the less glamorous but essential task of cleaning up their SharePoint sites. They know it’s a foundational enabler, not just for AI but for the next generation of business operations.

As companies embark on this journey, the ones that succeed will be those who understand that AI is not just about technology. It’s about ensuring the foundations, content, and knowledge are in order. A well-organized SharePoint might not sound exciting, but it’s the difference between AI success and another over-hyped pilot.

So before you dive into the next big AI initiative, take a step back and look at your SharePoint. Because if it’s a mess, AI will only make that mess more obvious.