AI Is Fluent in Public Data – But What About Yours?
Why companies must get their internal data “AI-ready” before they can unlock real value from LLMs.
By now, it’s obvious: generative AI is here, and it’s powerful. ChatGPT, Claude, Gemini – they can write emails, debug code, generate reports, and more. But they all share one thing: they’re fluent in public data.
Ask about GDP trends or ChatGPT’s take on Porter’s Five Forces, and you’ll get a great response. Ask it to optimize your inventory strategy, evaluate margin performance across product lines, or explain why your largest customer is suddenly unprofitable – and you’ll hit a wall.
Why? Because your internal data isn’t ready for AI. And that’s the real bottleneck.
At Profit Isle, we work with retailers, manufacturers, distributors, and service firms that generate mountains of data from ERPs, CRMs, BI tools, and yes, spreadsheets. But the vast majority of that data lives in silos. It’s messy. It’s poorly governed. It’s invisible to AI.
If you’re excited about LLMs, you should be. But if your data isn’t AI-ready, that excitement will quickly turn into frustration.
The Hidden Problem: Your Data Isn’t Ready
In recent surveys, over 88% of AI initiatives fail to reach production (CIO Dive), and only 8% of companies say their data is fully ready for AI (Huble Market Research). The issue isn’t the model – it’s the inputs. You can’t feed dirty, siloed, or outdated data to a large language model and expect magic.
Here’s what we’re seeing:
- Fragmentation: Critical insights are buried across disconnected systems – ERP, CRM, Excel, file shares. AI can’t connect the dots unless your data is unified and integrated.
- Poor Hygiene: Duplicate records, inconsistent naming conventions, missing fields. If your “gross profit” metric is defined differently in three systems, AI won’t know which one to trust. Do you?
- Limited Accessibility: If data lives in legacy on-prem systems or departmental black boxes, even the best AI can’t access it. No access = no insight.
- No Governance: Without clear ownership, standards, and guardrails, you risk regulatory breaches or worse, unreliable insights that lead to bad decisions.
This isn’t just an IT problem. It’s a profit problem.
Public LLMs Can’t Solve This for You
Think of LLMs like interns – brilliant, fast-learning, and capable of amazing work – but only if you give them the right training and context.
You wouldn’t hand your intern a thousand disconnected reports and ask them to “find some insights.” So why are we doing that with AI?
Open models like ChatGPT are trained on the internet. They can tell you what gross margin is, but they can’t tell you why your margins are shrinking in Q3, or which products in Region 4 are eroding profitability. For that, they need your data – clean, connected, and contextualized.
That’s where most companies get stuck. They’ve invested in AI tools but skipped the foundational step: making internal data AI-ready.
What It Takes to Become AI-Ready
The good news? You don’t need to overhaul your tech stack. But you do need to start treating your internal data like a product. That means:
- Inventory What You Have: Know where your critical data lives and who owns it. If you can’t map your data sources, neither can AI.
- Clean It Up: Establish consistent definitions, eliminate duplicates, and standardize formats. No more “revenue” meaning five different things.
- Integrate Across Silos: Use modern data pipelines or API connectors to unify key datasets. Bonus points for using real-time syncs instead of batch jobs.
- Add Context and Governance: Tag data with metadata. Enforce access controls. Document what each variable means and how it’s calculated.
- Start With High-Impact Use Cases: Don’t boil the ocean. Focus on a few areas-like customer profitability or product erosion-and get those datasets ready for AI first.
At Profit Isle, we see the power of this every day. Once internal data is modeled, cleaned, and connected, our customers can:
- Identify their profit drainers at the customer and SKU level
- See where margin erosion is quietly compounding
- Forecast and act with speed-not after quarter-end
We don’t just plug in AI for the sake of it – we make your own data work for you, profit-first.
This Isn’t Optional Anymore
In 2025, the winners won’t be the ones with the fanciest AI tools. They’ll be the ones who gave their AI the best data to work with.
The future of profitability is data-driven. But it’s not generic, web-trained, public data – it’s yours. If it’s buried, siloed, or broken, no LLM will save you.
The companies that act now – those who invest in getting their data AI-ready – will leap ahead. They’ll move faster, price smarter, serve better, and grow margins where others are still guessing.
AI is fluent in the world’s data. But if you want it to speak the language of your business, you need to give it the right words.
Let’s get your data talking.
