The single biggest shift happening in commercial data right now isn’t AI. It’s the growing gap between how data suppliers want to price their products and what enterprise buyers are actually willing to pay for.
I’ve spent 30 years in the commercial data space, building, selling, and advising on data products at enterprise scale. The conversation I’m having most often right now isn’t about AI features or new data sources. It’s about pricing power, and who’s about to lose it.
The model that built an industry
For decades, commercial data ran on a simple model: volume-based licensing. Records pulled. API calls made. Annual enterprise commits with discount tiers tied to volume. Predictable for suppliers, manageable for buyers, and enormously profitable for the players who built the largest proprietary datasets.
The major players each built a moat around a proprietary data asset and charged accordingly. Business identity. Consumer-commercial crossover. Private company financials. The categories were distinct, the switching costs were real, and the margins were exceptional. The model worked because the data was genuinely hard to replicate.
That model is now under pressure from two directions simultaneously. Buyers are starting to ask the question that makes every data supplier uncomfortable: why am I paying for records when what I actually need is outcomes?
The buyer has gotten smarter
Enterprise buyers in 2026 are more sophisticated about data procurement than at any point in history. They’ve run multiple vendor evaluations. They’ve run the match rate comparisons across every major supplier. They know the coverage differentiation story has narrowed substantially. The vendors know it too.
The conversation in procurement has shifted. It used to be ‘which vendor has the best coverage?’ Now it’s ‘which vendor can demonstrate measurable impact on our outcomes?’ Default rates. Pipeline conversion. Fraud prevention. Customer acquisition cost.
That’s a fundamentally different question. And most data suppliers aren’t equipped to answer it.
AI is accelerating the commoditization
Simultaneously, the supply side is getting disrupted. Web scraping at scale, LLM-driven firmographic enrichment, and open public datasets are eroding moats that took decades to build. A well-resourced startup can now construct a broad business identity database in months, not years.
Coverage alone is no longer a defensible differentiator. The question isn’t whether your data is complete. It’s whether your data produces better decisions than the alternative.
Where pricing power is moving
- Proprietary signals: transaction data, behavioral triggers, real-time event detection that can’t be replicated from public sources
- Decisioning infrastructure: the model layer, not the data layer; who produces better outcomes, not who has more records
- Workflow ownership: native connectors to Salesforce, SAP, ERP systems; switching costs built in code, not contracts
- Professional services attach: implementation, custom model development, and managed services as margin-rich, sticky revenue lines
The innovator’s dilemma, data edition
Here’s the structural problem for incumbents: outcome-based pricing isn’t just a commercial model change. It’s a fundamental shift in revenue risk. Under volume-based licensing, the supplier gets paid regardless of whether the data produces value. Under outcome-based pricing, the supplier’s revenue is tied to whether their product actually works.
Most incumbent data suppliers aren’t structurally prepared for that shift. Their margins are built on volume. Their sales motions are built on annual commit negotiations. Their product organizations have never had to instrument outcomes at the customer level.
Moving to outcome-based pricing cannibalizes existing revenue before the new model scales. A classic innovator’s dilemma. The rational short-term decision is to defend the existing model. The strategic long-term risk is that a new entrant builds outcome-native from day one and leads the market.
The suppliers who will hold pricing power over the next decade aren’t the ones with the biggest data lakes. They’re the ones who can answer: did using our product produce a measurably better outcome?
What this means for buyers and disruptors
For enterprise buyers, the leverage position has never been stronger. Suppliers who can’t answer the outcomes question are vulnerable to displacement. The market is repricing accordingly.
For disruptors and new entrants, the window is open. The incumbents’ structural constraints are your opportunity. Build outcome-native. Instrument everything. Make the ROI case in the first 90 days or don’t sign the contract.
For incumbent suppliers, the path forward requires genuine product and commercial model transformation, not incremental feature additions. The companies that navigate this shift will emerge stronger. The ones that don’t will find their pricing power eroding faster than their data coverage.
This isn’t just a pricing problem. It’s a strategic inflection point for an entire industry category. For buyers, disruptors, and advisors who understand the shift, it’s the opportunity of the decade.