Early Findings From our Contract AI Maturity Assessment
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Over the past few weeks, we’ve been running an AI Contract Maturity Assessment aimed at legal and procurement professionals. The early results from just over 200 respondents reveal something striking: there’s a significant gap between where organizations think they are with contract AI and where they actually stand.
More than half have no way to measure whether their AI contract tools are working. Three-quarters lack adequate training programs. And more than a third can’t even systematically locate their contracts—let alone apply AI to analyze them.
While these are early findings and our sample size is still growing, the patterns point to three interconnected gaps that separate organizations seeing strong AI results from those that struggle.
The foundation gap: You can’t analyze what you can’t find
Before any AI algorithm can extract insights or automate workflows, organizations need to answer a basic question: where are your contracts?
More than one-third of respondents (36%) report that contracts are either scattered across email, drives, and physical files (19%) or stored in basic shared folders with limited organization (17%). Only 27% have a dedicated contract management system, and just 14% use an AI repository.
The digitization picture is similar. While 30% of organizations have 95%+ of contracts fully digitized with searchable text, 41% have less than half their contracts in this state. Contracts from just a few years ago might be locked in filing cabinets or exist only as unsearchable PDF images.
Data quality follows the same pattern. Only 13% describe their contract data as high-quality and AI-ready. The majority (68%) report either poor data quality or significant inconsistencies. AI models are only as good as the data they’re trained on. Natural language search can’t find clauses in documents that don’t exist digitally. Automated obligation tracking can’t identify renewal dates in contracts stored in someone’s email inbox.
The capability gap: Manual work dominates
Even among organizations with decent storage and digitization, manual processes remain dominant—representing significant opportunities for AI automation.
Contract review is the clearest example. 37% of respondents report line-by-line manual reviews by legal teams. Another 25% use checklists and templates—still largely manual. Only 14% have AI-assisted review that highlights risks and deviations. Obligation tracking tells the same story: 34% rely on calendar reminders and spreadsheets, 33% use basic CLM alerts, and only 13% have AI systems that proactively identify obligations. For data extraction, 41% work manually. For search, 51% rely on manual review or basic keyword searches.
The persistence of manual processes despite available technology suggests the barrier isn’t awareness or lack of solutions. Changing contract workflows requires cross-functional alignment across legal, procurement, sales, and finance—making the right platform and implementation approach critical.
The strategy gap: Investment without infrastructure
The most notable finding is the disconnect between appetite for AI and organizational readiness. Leadership interest is strong: 43% are interested and seeking proof of ROI, 23% are committed with allocated budget, and 19% have an AI-first strategy. Only 14% remain skeptical. But 51% of organizations have no formal measurement for their contract AI initiatives. Another 22% track only basic time-saving metrics. Just 25% have comprehensive KPIs or advanced analytics. Without baseline metrics, organizations can’t demonstrate value, optimize performance, or make data-driven decisions about scaling AI investments.
The training gap reveals similar opportunities. 42% have no formal training program—just ad-hoc learning. Another 34% provide basic training but see inconsistent usage. Only 24% offer comprehensive or advanced training. Organizations that invest in enablement alongside technology see significantly better adoption and results.
The bright spots
Despite these gaps, the data also reveals encouraging momentum. Leadership commitment is strong, with 62% interested or actively investing in contract AI. Nearly a third of organizations have achieved full digitization with searchable contracts. The 27% using dedicated contract management systems report better visibility and control. And early adopters of AI review, extraction, and obligation tracking consistently report significant time savings, improved accuracy, and fewer missed deadlines. The path to contract AI success is proven—it’s about readiness and implementation approach.
What the data shows
These early findings reveal that success with contract AI isn’t about the sophistication of the algorithms—it’s about organizational readiness. Organizations getting strong results from AI are those that have addressed foundational data quality, standardized their processes, and built measurement and training infrastructure.
The gap between high performers and others isn’t insurmountable. It’s a matter of implementation approach: addressing contracts storage and digitization, establishing clear workflows, setting baseline metrics, and investing in team enablement. Organizations that take this structured approach see faster time-to-value and stronger ROI from their AI investments.
Want to see where your organization stands? Take our AI Contract Maturity Assessment to get a personalized readiness score and benchmark against your peers. The assessment takes less than 5 minutes and provides immediate insights into your foundation, capabilities, and strategic readiness.allows. Check your admin console or speak with your Customer Success Manager for deployment assistance.
Ironclad is not a law firm, and this post does not constitute or contain legal advice. To evaluate the accuracy, sufficiency, or reliability of the ideas and guidance reflected here, or the applicability of these materials to your business, you should consult with a licensed attorney.
