AI Terms Are Coming: How to Prepare Your Contracts for Industry Benchmarks

The current state of AI contract provisions resembles the early days of data privacy clauses—underspecified, inconsistent, and largely overlooked until they became focal points of negotiation. Within the next 18-24 months, AI-related contract terms will undergo a similar transformation as regulations crystallize, litigation establishes precedents, and industry benchmarks emerge.

General counsels facing this transition have a choice: react when AI terms become heavily negotiated pressure points, or prepare proactively while flexibility still exists. The reactive approach means scrambling to update contracts when customers start demanding specific AI disclosures or when regulators begin enforcement. The proactive approach means auditing current contracts against emerging benchmarks and identifying gaps before they become problems.

This preparation window won't stay open indefinitely. As regulatory frameworks take effect and industry consensus develops around AI contract standards, the flexibility to shape terms proactively will narrow. Companies that wait until AI provisions become standard negotiation points will find themselves reworking agreements under pressure.

AI contract analysis tools enable this preparation by systematically evaluating current agreements against developing benchmarks and identifying specific areas requiring attention before they become negotiation obstacles.

The Three AI Provisions That Will Become Non-Negotiable

The most immediate benchmarks emerging across industries involve explicit disclosure about whether and how vendors use customer data to train AI models. Current contracts often include vague data usage clauses that don't specifically address training. This ambiguity will become unacceptable as buyers demand clarity.

What Training Data Disclosure Will Require

The developing benchmark requires clear statements answering specific questions. Does the vendor train models on customer data? If so, do improvements benefit only that customer or all vendor clients? Can customers opt out?

What contracts must disclose about AI training:

• Whether customer data trains AI models at all
• If training benefits only that customer or all clients
• Which specific data types get used (content, metadata, usage patterns)
• Whether customers can opt out of training data usage

Preparing for this benchmark means auditing current AI-powered vendor contracts to identify which fail to disclose training data practices. AI contract analysis can quickly scan agreement portfolios to flag contracts lacking adequate training data provisions.

The preparation also involves establishing policies for the company's own AI products. Vendors that proactively adopt clear training data disclosure gain an advantage as customers increasingly demand this transparency.

The Explainability Standards Nobody's Ready For

The second major benchmark involves commitments around AI explainability and customer audit rights. Regulatory frameworks like the EU AI Act are establishing requirements for understanding how AI systems make decisions. These regulatory mandates will drive contractual provisions even for AI usage outside regulatory scope.

The emerging standard requires contracts to address whether customers can request explanations for specific AI-generated decisions, whether they have access to documentation about model inputs, and whether audit rights extend to AI-specific evaluation.

What audit provisions will need to be covered:

• Ability to request explanations for AI-generated decisions
• Access to documentation about model inputs and decision-making processes
• Rights to audit AI operations specifically, not just general security
• Timeline and process for exercising audit rights

For customer-side agreements, AI contract analysis should evaluate whether existing vendor contracts provide adequate audit rights covering AI operations. Many contracts include general audit provisions that technically might extend to AI but don't specify this explicitly. Refusing all audit provisions creates a competitive disadvantage.

When AI Updates Become Contract Issues

The third emerging benchmark addresses how vendors manage AI updates and changes. AI systems evolve continuously, and these changes can significantly affect behavior and outputs. Yet most current contracts don't address whether vendors must notify customers before material AI changes.

Contract analysis AI can identify agreements lacking change management provisions for AI operations. This gap is particularly common in older contracts predating widespread AI adoption.

Getting Your Contract Portfolio Ready

Preparing for AI term benchmarks begins with a systematic audit of current contract portfolios. This audit identifies which agreements involve AI functionality, how comprehensively they address AI-specific concerns, and where gaps exist relative to emerging standards.

The Audit That Can't Wait

Manual review of hundreds or thousands of contracts for AI provisions is impractical. This is where the best AI contract analysis tool becomes a practical necessity rather than an optional efficiency.

TermScout's Certify platform enables systematic evaluation of contract portfolios specifically for AI-related provisions. The platform identifies which contracts mention AI functionality, extracts what commitments exist around training data and explainability, and flags gaps where contracts should address AI but don't.

The audit reveals patterns about AI contract maturity across the portfolio. Companies might discover that recent agreements with major vendors include some AI disclosure while older contracts lack any AI-specific provisions. This pattern enables risk-based prioritization.

Building Standards While You Still Can

The audit findings inform the development of organizational standards for AI contract provisions. These standards define what AI-related disclosures and commitments company contracts should include, both for vendor relationships and for the company's own AI products.

What organizational AI contract standards should cover:

• Required disclosures for any agreement involving AI functionality
• Audit rights that explicitly cover AI operations
• Change management protocols for material AI updates
• Explainability commitments appropriate to the AI's role

The standards should be informed by AI contract analysis of market practices. What are the leading vendors committing to around AI provisions? How do customer-favorable contracts address training data compared to vendor-favorable agreements?

The Implementation Reality

Establishing standards is easier than implementing them. The prioritized approach starts with contracts coming up for renewal in the next 12-18 months. These provide natural opportunities to introduce AI provisions aligned with organizational standards.

The second priority addresses strategic relationships where AI usage creates concern. For these situations, AI contract analysis helps identify the most critical amendments needed. Proactive preparation prevents the reactive scramble that occurs when contract delays hit your pipeline.

Why Waiting Means Playing Catch-Up

AI regulation is moving faster than most legal teams acknowledge. The EU AI Act takes effect with real enforcement mechanisms beginning in 2025-2026. AI contract analysis ensures that contracts written today are designed to support compliance tomorrow. Proactive preparation prevents the scramble of updating dozens of unfair contracts when regulations become enforceable.

The Window Is Closing

AI contract provisions will become heavily negotiated as industry benchmarks solidify. AI contract analysis through platforms like TermScout's Certify enables preparation that would be impractical through manual review. The systematic evaluation of portfolio-wide AI provisions compresses preparation timelines while ensuring consistency.

General counsels recognizing that AI terms are coming have the opportunity to prepare contracts for the industry benchmarks that will soon become standard. The advantage belongs to those treating AI contract preparation as a strategic priority now rather than a compliance burden to address later. This is the cornerstone of certified contracts.

Discover how Certify's AI contract analysis capabilities help organizations prepare their contract portfolios for emerging AI term benchmarks.