How your data strategy will define your AI success
One things that struck me after running a recent Webinar on AI was how many people think that by simply subscribing to ‘AI’ your business will automatically improve. While there is a lot on social (and general) media about the benefits of AI (the latest being the advancements in Claude Cowork) there is also, quite simply a lot of guff out there. Just subscribing to Copilot for 10 people to play with in the office is never going to yield the volume and type of change that is going to make a dent in your business. Sure, your Marketing team can create cool looking graphics and automate social posts, yep Finance can make fancy spreadsheets with colours and even conditional formatting but is that going to raise EBITDA or grow Revenue by 5% ? Nope. What might make a dent is an AI strategy that is properly implemented, and that isn’t going to happen without first looking at data and file locations. Many (many !) clients think a SharePoint project ends when the data is transferred (warts and all) from on-prem to M365 when in fact that is only part way through. If you want that data to become a knowledge source for future AI initiatives and agents it needs to be organised, structured and labelled. These are some of the main steps you need to consider for such a project; AI Is Only as Good as the Data Beneath It There’s a narrative in the market that AI is transformative by default. Shockingly it isn’t. AI is powerful — but only when it sits on top of structured, governed, compliant data. Without that foundation, it’s just an expensive experiment or worse, a confidence illusion. If you care about the welfare of your company’s data — and that is ‘if’ — then AI adoption isn’t about which tool fits best. It’s a data maturity journey. In my experience advising organisations across Microsoft 365, ERP, and business platforms, the path to extracting real value from AI follows a four-stage framework; It breaks down like this; Stage 1: Understand the Data Landscape Assess Data & Locations Before AI, before automation, before Copilot — you need clarity. Most organisations don’t realise just how fragmented their data estate is: Key Considerations This stage is not glamorous. It is forensic. It often involves: Benefits of Stage 1 Without this stage, AI simply amplifies disorder and will quickly get relegated to the ‘tried it and it didn’t work’ bin Stage 2: Centralise Key Data Migrate & Consolidate AI thrives on accessible, unified data. If your information is siloed across multiple systems with no integration, your AI outputs will be fragmented, incomplete, and context-poor. This is where platforms like SharePoint Online, Dataverse, modern ERP, and secure cloud repositories come into play. What Centralisation Really Means It doesn’t mean “dump everything in one place and forget about it” It means: Key Considerations Benefits of Stage 2 Centralisation moves you from chaos to coherence. But coherence without control is still risky — which brings us to Stage 3. Stage 3: Classify & Organise Data Structure & Label Information This is the stage most organisations skip, the data’s in the Cloud so were done right ? Wrong ! This is the stage that determines whether AI becomes transformational or dangerous. AI engines don’t “understand” context the way humans do. They rely on structure, labels, permissions, and semantic signals. If your sensitive HR files sit in the same library as marketing brochures with open permissions, AI will not instinctively correct that mistake. What This Stage Involves Governance Is Not Bureaucracy Governance is protection: Benefits of Stage 3 This is where data welfare becomes real.You move from storage to stewardship. Only now are your AI Readiness is through the roof Stage 4: Apply the Right Analytics & AI Layers Insights & Automation Once data is structured, secure, and centralised — AI becomes a multiplier. Now you can responsibly deploy: Key Considerations AI should align to business objectives, not experimentation agendas. Benefits of Stage 4 This is where the value multipliers kick in Notice also that AI is the final stage rather than the starting point. The Bigger Message: AI Is a Tool, Not a Strategy AI alone is not transformationIt is not governanceIt is not compliance It is purely an amplifier If done poorly (or not at all AI will simply amplify your issues and probable create new onesIf your data estate is structured and governed, AI can amplify intelligence. Final Thought If you are considering AI in your business, ask yourself: Before you rush off and subscribe to any of these amazing AI saviours make sure you’re not simply reacting to hype and make sure you consider all the steps you’ll need to take to ensure positive amplification rather than simply another mediocre initiative. Simon