Why AI Adoption in Legal Teams Keeps Stalling: The Culture Problem Contract Tech Cannot Fix Alone

The Numbers Behind Contract Chaos

A new Workday survey of 7,000 lawyers and enterprise staff across ten countries has surfaced a finding that will not surprise many general counsels but should embarrass more than a few technology vendors: only 37 per cent of organisations manage contracts in a consistent, structured way. The rest are still relying on a patchwork of shared drives, email threads, spreadsheets and institutional memory. This is not a technology shortage. Every major legal technology vendor now offers some version of AI-powered contract lifecycle management. The gap is organisational, not technological, and that distinction matters enormously for how legal teams should think about their next investment.

The survey reinforces a principle that has been circulating in enterprise technology circles for decades: culture eats strategy for breakfast, and it appears equally hungry when AI is on the menu.

What Contract Lifecycle Management Actually Promises

Contract lifecycle management, or CLM, covers the full arc of a contract's existence: drafting, negotiation, execution, obligation tracking and renewal or expiry. AI-powered CLM platforms can accelerate each of those stages. On the drafting side, tools can generate first drafts from approved playbooks, flag non-standard clauses and suggest market-standard alternatives. On the review side, they can extract key commercial terms, identify risk concentrations and surface obligations that legal teams would otherwise miss under volume pressure.

The business case for AI contract management is straightforward. Faster cycle times mean deals close sooner. Consistent clause libraries reduce negotiation drag. Automated obligation tracking prevents the costly missed renewals and breached commitments that haunt under-resourced legal departments. When it works, AI in contract management is one of the clearest demonstrations of legal technology delivering measurable return on investment.

The Workday data suggests that for most organisations, it is not working at that level yet.

Why Legal AI Adoption Keeps Stalling

Legal professionals are trained to be sceptical. That scepticism is professionally valuable in a negotiation and professionally inconvenient when an organisation is trying to roll out new software. But resistance to legal technology adoption goes deeper than individual conservatism.

Legal teams frequently lack the authority to mandate how counterparties send contracts, how business units initiate requests, or how finance systems record obligations. CLM sits at the intersection of legal, procurement, finance and sales, which means a successful deployment requires buy-in across functions that have competing priorities and different definitions of what a contract is for. When that cross-functional alignment is absent, even the most capable AI contract management platform becomes an underused add-on rather than a system of record.

There is also a confidence gap. Lawyers are personally accountable for the advice they give. Delegating any part of that to an AI system requires a level of institutional trust in the tool that takes time to build. Vendors who promise immediate transformation undermine that trust-building process rather than supporting it.

Where AI Contract Tools Are Actually Gaining Ground

Despite the broad adoption challenges, there are clear pockets of progress. High-volume, lower-complexity contract types, including NDAs, standard vendor agreements and employment contracts, are proving to be the most tractable starting points for AI contract automation. Legal teams that begin with these categories can demonstrate value quickly, build internal confidence and create the organisational habits that eventually extend to more complex deal types.

Legal operations functions, where they exist, are the most consistent drivers of successful AI adoption in law. Legal ops professionals combine process expertise with enough distance from day-to-day legal practice to evaluate tools on operational merit rather than instinct. Organisations that have invested in legal ops capability consistently outperform those where technology decisions are made exclusively by practising lawyers.

Jurisdictional fluency is also emerging as a differentiating factor. AI contract management tools that understand the specific legal requirements of the markets a business operates in, rather than defaulting to generic, jurisdiction-neutral language, are considerably more useful to global legal teams. The ability to draft and review with local law in mind is not a nice-to-have for multinationals; it is a prerequisite for meaningful adoption.

What Legal Teams Should Do Before Buying Another Platform

The Workday survey is a useful prompt for any legal team that is considering, or reconsidering, an investment in AI contract management. Before evaluating features, legal teams should audit where contracts actually live today, who has visibility into them and what happens when an obligation is missed. If those answers are unclear or inconsistent, adding an AI layer will not resolve the underlying problem.

Change management deserves as much budget and planning as the technology itself. Piloting with a willing sub-team, documenting the workflow improvements and sharing those results internally is a more reliable path to broad adoption than a top-down mandate accompanied by a training session.

Finally, legal teams should ask vendors hard questions about how their tools read contracts from the other side of a negotiation, not just contracts a company generates itself. The ability to ingest and analyse counterparty paper, flag deviations from your own standard positions and prioritise review time is where AI contract review delivers disproportionate value in practice.

An Honest Assessment for 2025 and Beyond

AI in legal is real, the use cases are proven and the efficiency gains for teams that adopt thoughtfully are significant. But the Workday data is a timely corrective to the idea that deploying a CLM platform is equivalent to solving the contract management problem. Technology is a necessary condition, not a sufficient one.

Organisations that treat AI contract management as a culture and process project that happens to require software will outperform those that treat it as a software project that will sort out culture along the way. The 63 per cent of organisations still managing contracts inconsistently have a technology choice to make, but they have an organisational choice to make first.