While Others Waste Billions on AI, Use Existing Data You Already Own

Billions are being invested in generative AI, but the payoff isn’t showing up on the balance sheet. MIT’s State of AI in Business 2025 found that 95% of enterprise AI pilots deliver no return. Adoption is high, yet transformation is low.

Why? Too often, businesses chase after new data streams, while overlooking the significant value they already have access to: the information buried in their own systems. Sales databases, invoices, contracts, and past reports contain years of operational insight — but because they’re unorganized, unexamined, or locked behind technical barriers, they rarely get used to their full potential.

For businesses seeking immediate ROI from AI, this represents both a smart and practical opportunity. While larger competitors burn budgets on failed AI projects, unlocking existing data is what we at Paleotech have found to be a fast and reliable way to help cross what MIT calls the “GenAI Divide” — the gap between experimenting with AI and achieving measurable business results.

The GenAI Divide and Why ROI Stalls

On one side, there are lots of organizations enthusiastically piloting AI tools. On the other, very few of them see measurable business impact. The numbers are stark: while more than 80% of companies have experimented with tools like ChatGPT, only 5% of custom enterprise AI pilots ever make it into scaled production.

Why the disconnect? The report makes clear that it isn’t about infrastructure or talent. It isn’t about budget constraints. The real issue is integration. Most AI initiatives fail because they are built to sit on top of the business, rather than live inside it. They don’t connect to workflows, they don’t learn from feedback, and they don’t adapt to the way employees actually work.

For business leaders, the lesson is simple: AI success doesn’t come from experimentation alone. It comes from embedding AI in the places where business already happens. And that means start with the data you own, not the data you wish you had.

Why Your Existing Data Is Gold

When people think about AI, they often think about collecting new data: new customer signals, new market intelligence, new behavioral patterns. That sounds exciting, but it’s rarely the best place to start. The fastest wins usually come from unlocking the existing data in your own systems:

1. From Unorganized to Structured Intelligence

Your sales records, invoices, and customer service logs aren’t just scattered files—they’re a complete map of how your business actually works. Rather than generic insights, you get context that’s impossible to find anywhere else about your company: which customers buy what, when expenses spike, how deals typically close. 

AI can then transform this operational chaos into structured intelligence that reflects your unique business patterns.

2. From Unexamined to Actionable Insights

That contract from three years ago contains renewal terms you forgot about? AI flags it months before the deadline, giving you time to renegotiate or budget accordingly. Last quarter’s expense report reveals a cost pattern you never noticed? AI spots the trend early so you can adjust spending before it impacts your bottom line. Your support tickets start to reveal which product issues repeat most often. 

AI can examine years of operational data to surface insights that were always there but never discovered—turning your historical information into actionable foresight.

3. From Technical Barriers to Natural Language Access

You shouldn’t need SQL knowledge or an IT report creation request to understand “Which customers haven’t ordered in 90 days?” or “What were our biggest expenses last quarter?” 

AI democratizes data access, letting anyone ask business questions in conversational language and uncover insights that were always there but never accessible.

This is why “shadow AI” has become so prevalent. MIT reports that 90% of employees use personal tools like ChatGPT to get work done (while only 40% of companies provide official subscriptions). Employees want easier access to information, and they’ll find it however they can. Unlocking existing business data through enterprise AI meets this need directly, democratizing access and empowering employees, but while maintaining the security and oversight that companies require.

The Payoff of Unlocking Existing Data

What happens when companies take this approach?

First, the payoff comes faster. Existing data is already in your systems, so unlocking it doesn’t require months of setup or costly new pipelines. You can show results quickly, which is critical for organizations that don’t have the luxury of long timelines. MIT also found that internal builds fail twice as often as external partnerships, which makes chasing “new” data even riskier. Starting with what you already have is the lower-risk, higher-reward path.

Second, it integrates naturally into your workflows. MIT’s research also shows that the biggest determinant of ROI isn’t model quality but whether the AI integrates with processes and improves over time. Data that’s already tied to sales, finance, or operations is the best place to build that integration.

Third, it delivers value in overlooked places. Additionally, MIT found that while 50–70% of AI budgets go toward sales and marketing, the highest ROI often comes from back-office automation. That’s exactly where existing data sits: contracts, invoices, support tickets, vendor records. Automating these workflows reduces costs and frees employees to focus on higher-value work.

And finally, it improves everyday outcomes. Reports are generated instantly instead of days later. Contract reviews surface risks and potential financial problems that may have been missed in manual reviews. Customer service teams can find answers in seconds instead of searching through documents. These aren’t theoretical benefits; they’re practical, measurable improvements.

How To Start Finding Hidden (Data) Treasure

The first step is to identify your highest-friction workflows: processes that eat up time, create bottlenecks, or consistently frustrate your team. These are often the places where valuable information exists but accessing it feels like pulling teeth. Common examples include waiting days for IT to pull a custom sales report, manually combing through invoices to spot billing errors, digging through filing cabinets or document folders to find contract terms, or searching through email threads to reconstruct the history of a customer issue.

These friction points reveal where your existing data could deliver immediate value. The goal isn’t to automate everything at once, but to find the one workflow where better data access and insights would make the biggest difference in daily operations.

From there, start small and focused. Choose one dataset that directly relates to your highest-friction workflow: your CRM if sales reporting is the pain point, your financial system if invoice processing slows you down, or your document archives if contract research creates delays. The key is first connecting AI to data that people already need, not data that seems impressive but sits unused. (And as we always recommend, build using an LLM-agnostic architecture for optimal control, performance, and cost.)

Enable natural language access to this information. Instead of requiring technical skills or special software, employees should be able to ask plain-language questions through chat-like interfaces and receive useful answers in seconds. “Which customers haven’t placed orders in the last quarter?” “What were our largest unexpected expenses last month?” “When does our largest vendor contract expire?” These everyday business questions should have instant, accurate answers.  

The beauty of this approach is that success builds naturally. Once people experience the value of immediate, easy access to one dataset, they’ll identify other areas where the same approach could help. Rather than forcing adoption through training or mandates, you’ll find employees asking for broader access to company information.

Not sure what value you might already have from existing data? Download our complete guide to hidden data value to see the 11 categories of information that most businesses already have but rarely leverage—from CRM records and financial transactions to meeting notes and customer feedback. This comprehensive breakdown will help you identify which datasets in your organization could transform from unexamined, scattered files into strategic advantages.

Over time, these small wins compound into significant operational improvements. MIT found that only 5% of custom AI pilots reach production, but those that succeed share a common trait: they’re tied directly to existing workflows and data. For successful companies, the path to crossing the GenAI Divide isn’t chasing the next shiny pilot or building complex new systems from the start—it’s starting by systematically removing friction from the work that already happens every day.

Conclusion

MIT’s research reveals why AI transformation feels impossible: many companies are solving the wrong problem. They chase new data while ignoring existing value. They build complex systems while employees gravitate toward simple tools. They focus on flashy pilots while real ROI hides in back-office workflows.

The good news is, this dysfunction creates massive opportunities for your organization. While competitors burn through AI budgets on failed experiments, you can achieve measurable results by unlocking the data you already own.

The GenAI Divide isn’t permanent. But crossing it requires different choices: not about technology, but about where to start. The treasure isn’t necessarily to be found in some future dataset. It’s likely hidden in your systems, right now.

Ready to unlock your hidden data? At Paleotech, we specialize in connecting businesses to the operational intelligence they already own. Instead of chasing new data sources or building complex systems from scratch, we can help you transform existing information into natural language interfaces that anyone can use. The result: instant access to business insights, faster decision-making, and measurable ROI from data you’ve already paid to collect.

Your competitors are still figuring out their AI strategy. Your advantage is starting with what you already have, and making it work better than they ever imagined possible.

Article Sources

• STATE OF AI IN BUSINESS 2025 (2025), MIT
• Why Companies Need LLM-Agnostic AI (Sep 2025), Paleotech AI
• 90% of Your Employees Already Use Chat AI—Now Turn It Into Powerful Business ROI (Sep 2025), Paleotech AI