NetApp

Corporate legal departments face a structural cost crisis in low-risk contract processing. A representative $25,000 SaaS agreement costs approximately $6,900 to review and process — more than 25% of the contract's total value — based on WorldCC data. With legal teams chronically understaffed and higher-value strategic deals competing for attorney time, procurement faces a binary and equally flawed choice: sign vendor paper as-is, accepting potentially unbalanced terms (including broad data rights, exclusivity clauses, or non-compete provisions), or initiate a full review that can take weeks and halt business projects entirely. The global contracting inefficiency problem is estimated to cost the economy over $1 trillion annually.

A consortium led by NetApp — chaired by Connie Brenton, VP of Law, Technology and Operations — assembled representatives from Travelers Insurance, Liberty Mutual, Code42, a large telecom, law firms, and legal tech vendors to run a structured Phase 1 pilot. The team collected 60 vendor software and SaaS contract sets and processed each through TermScout, a contract analytics platform using Natural Language Processing, scored against a 19-term deal-breaker filter. Contracts failing fewer than five terms received automated Self-Correction Notices prompting vendors to voluntarily address deficiencies. LexCheck was layered in to auto-generate AI redlines based on each buyer's internal playbook. NetApp implemented a tiered routing model — low, medium, and high risk — to calibrate the level of human legal involvement proportionally to contract exposure.

The pilot demonstrated that AI-driven screening can eliminate traditional negotiation in a substantial majority of low-risk contracts:

• 17% of vendor contracts passed the 19-term filter cleanly and were candidates for acceptance as-is
• 57% failed on four or fewer terms — strong candidates for resolution via automated Self-Correction Notices, with no traditional negotiation required
• 74% combined of low-risk contracts could potentially bypass negotiation entirely while maintaining the buyer's risk profile
• 33%+ realistic reduction in total low-risk contract handling costs
• Contracts averaged 35 negotiated terms, covering more than 80% of secondary-importance provisions

The consortium also established a data-driven baseline for which terms actually get negotiated and how often buyers succeed — intelligence that had previously existed only as subjective attorney impression.

• AI contract screening is mature enough to eliminate negotiation entirely for the majority of low-risk vendor agreements without degrading the company's risk posture.
• A tiered routing model (low/medium/high) is the operational backbone: it ensures human attorneys focus on high-value matters while automation handles the rest.
• Vendor self-correction — sending AI-generated notices with market-norm evidence — can resolve problem contracts without adversarial negotiation.
• Change management is the primary implementation barrier; procurement and legal teams must trust AI assessments enough to reduce human touch on routine contracts.
• Consortium-based pilots accelerate adoption by spreading data collection costs and validating findings across multiple buyer organizations simultaneously.