Live Demo: Using AI to Draft Better Business Agreements (Virtual)

AI's Urgent Push in Contract Drafting

The legal landscape for business agreements is shifting rapidly in early 2026. Corporate legal teams have embraced AI at an unprecedented pace, with surveys showing adoption more than doubling in a single year to over 50% by 2025. This acceleration stems from the need to handle growing contract volumes efficiently while controlling costs in an environment where routine legal work still consumes significant time and resources.

A major catalyst is the impending full application of the EU AI Act in August 2026. This regulation imposes strict requirements on high-risk AI systems, including those potentially used in legal contexts for drafting or analyzing agreements, with non-compliance penalties capped at the higher of €35 million or 7% of worldwide annual turnover. Businesses operating in or with the EU must now prioritize transparency, human oversight, and risk management in any AI-assisted processes, directly affecting how contracts allocate responsibilities and liabilities.

The stakes extend beyond Europe. Companies face real-world consequences from inadequate agreements, such as prolonged disputes, unexpected obligations, or invalidated terms that disrupt operations and erode value in deals. Traditional manual drafting is slow and prone to oversights, often delaying closings or inflating legal fees, while early AI adoption has demonstrated dramatic time savings—sometimes cutting drafting efforts by up to 90% in certain workflows.

Yet trade-offs abound. AI excels at suggesting clauses and spotting inconsistencies but risks generating inaccurate or hallucinated content, a problem highlighted by hundreds of documented court cases involving fabricated references. This creates tension between efficiency gains and the need for robust governance, especially as client expectations evolve and regulators demand accountability. In-house teams and law firms must balance augmentation of human expertise against over-reliance, particularly when contracts involve complex negotiations or cross-border elements subject to emerging rules like those in Colorado's AI Act.

Non-obvious angles include the reallocation of liability in AI vendor agreements and the push toward auditable, explainable systems that satisfy both business speed and regulatory demands. As AI embeds deeper into contract lifecycles—from initial drafting to ongoing management—the focus shifts from experimentation to trusted integration, where poor choices could amplify risks rather than mitigate them.