Contract Data Gaps Slow Deals and Leave Revenue Unbilled, Survey Finds

Contract data problems show up in operating results: deals slow when teams can’t locate agreed terms, services go unbilled, and executives wait for answers. In Pramata’s 2026 Contract Intelligence Index, 93% of respondents said they had faced challenges in the past year because contract data was inaccurate, missing or too slow to access. The findings point to a business-wide information problem, with consequences for revenue capture and decision speed.

The survey included more than 450 leaders in Legal, Finance, Commercial Operations and IT. It found that 91% say at least three business processes depend on accurate, accessible contract data. Those processes include renewals, billing, audits and compliance. Yet only 11% of respondents said they can get reliable answers from contract data in minutes.

Fragmented records create practical costs

Respondents described a range of problems tied to missing or hard-to-find contract details. Half said a deal had slowed because they couldn’t find what the parties had already agreed to. Nearly half, 48%, couldn’t quickly answer an executive’s request. Another 37% faced an audit, compliance or legal exposure they hadn’t anticipated, while 33% said they delivered services or usage that never got billed.

These figures describe different points in the same operating chain. When teams can’t retrieve the terms that govern a customer relationship, they may struggle to confirm scope, timing or billing obligations. That can hold up a commercial decision, divert staff into manual searches, or leave charges uncollected. The survey does not quantify the total financial impact of these incidents, but it does show how widely the reported effects reach.

The underlying issue appears to be distribution. Nearly half of respondents named contract data spread across too many places as their single biggest challenge. Sixty-one percent said contract data lives in at least four locations. In that setup, teams may have to reconcile multiple records or rely on colleagues who know where information is stored. Even when the contract itself exists, finding a dependable answer quickly can remain difficult.

Executives see value in fixing the process

Nearly all respondents, 97%, said improving how their organizations get value from contracts is a priority over the next 12 months. More than half said fixing just one thing would be worth $250,000 or more annually; 18% put the potential value in the millions. Those are respondents’ assessments of possible annual value, rather than measured savings reported by the survey.

The difference matters. The survey signals that leaders see meaningful upside in addressing contract data problems, but it doesn’t establish how much organizations will recover or what it will cost to make changes. Results will depend on how often inaccurate or inaccessible records affect a company’s contracts, what processes it changes, and whether teams use the resulting information consistently.

Responsibility also extends beyond Legal. More than two-thirds of respondents, 68%, said a team other than Legal is accountable when contract data is wrong or missing. IT and Data teams were named most often, at 30%, followed by Commercial and Contract Operations, at 25%. That distribution reflects the practical fact that contract information supports work across departments: a record may be created or stored in one place, then needed by people handling billing, customer delivery, reporting or systems.

Pramata CRO Justin Schweisberger said the results show that contract information serves multiple business functions and that organizations often lack a single source of truth. He also described contract intelligence as an enterprise-wide priority. Pramata sells services in this area, so its characterization of the problem comes from a company with a commercial interest in the market; the survey figures offer the supporting evidence for the scale of reported challenges.

AI use is growing faster than data readiness

The survey also highlights a gap between AI adoption and confidence in the underlying information. Nearly 80% of respondents said their organizations are already using AI with contract data, either in production or in pilots. Yet only 25% said their data is completely ready for an AI agent to act on without a person checking the output.

That gap puts data quality at the center of AI deployment. A system can retrieve or process contract information quickly, but missing records, inconsistent terms or conflicting versions can still produce answers that require review. For teams using AI in billing, renewals or commercial operations, the issue is not simply whether a tool is in place; it is whether the records feeding it are dependable enough for the task.

Pramata’s findings make a case for treating contract data as shared operating infrastructure. The reported costs span delayed deals, slow internal responses, unexpected exposure and unbilled work, while the potential value of fixing the process remains an estimate from respondents. The figures to watch are whether organizations can reduce fragmented storage, improve answer times and raise confidence in the data used by both staff and AI systems.

The company’s 2026 Contract Intelligence Index provides further detail on the survey. Pramata’s website is available at pramata.com.