Workday Survey: Nobody Agrees Who Owns Contract Management

A Workday survey of 7,000 lawyers and other enterprise staff across 10 countries has surfaced a problem that no amount of AI tooling can fix on its own: most organizations cannot agree on who is responsible for their contracts once they are signed.

Just 37% of in-house lawyers said post-signature contract management fell under their remit. Among the wider enterprise staff surveyed, only 25% assumed lawyers owned that responsibility at all. Another 26% said contracts should belong to "whichever team seemed most relevant," a answer that effectively means no one owns the process by default.

That ambiguity shows up physically. More than half of respondents said their organization has no centralized system for storing contracts. Instead, agreements are scattered across personal hard drives (22%), email inboxes (20%), and, in nearly a quarter of cases (23%), physical paper files.

Why fragmentation blocks AI adoption

The numbers matter because contract lifecycle management has become one of the most heavily marketed use cases for enterprise AI, with vendors promising automated review, obligation tracking, and risk flagging. None of that works if the underlying documents are not even in one place.

An AI model can only analyze what it can access. If a fifth of contracts live in someone's inbox and another fifth sit on a personal laptop, no amount of large language model sophistication changes the fact that the data pipeline itself is broken before automation ever begins.

Culture, not technology, is the bottleneck: unclear ownership and fragmented storage are keeping AI-driven contract management out of reach for many enterprises.

The findings suggest that legal and operations teams face a governance problem before they face a technology problem. Deploying an AI contract tool into an organization that cannot agree on ownership or storage risks automating chaos rather than resolving it.

For enterprises evaluating AI-driven legal tech, the survey points to a practical first step that has nothing to do with model selection: assign clear ownership of the contract lifecycle and consolidate records into a single system of record. Only then does AI have a coherent dataset to work against.

The survey did not detail vendor-specific remediation steps, and it stopped short of naming which industries or company sizes showed the widest ownership gaps. But the topline figures are consistent enough across the sample to suggest the problem is structural rather than isolated to a handful of laggard organizations.