The Document Revolution

Here's a question that keeps general counsels up at night: what's actually in your contracts? Not what was negotiated six months ago—what's happening now? What obligations are coming due? What risks are quietly compounding?

Icertis just launched what they're calling the "Contract Intelligence Cloud," and the positioning is telling. They're not selling contract management anymore. They're selling contracts as "living data assets"—a unified platform that handles everything from initial drafting through compliance monitoring, all infused with generative AI that learns from your historical contract data.

The real innovation isn't any single feature. It's the recognition that the pre-signature and post-signature worlds have been artificially separated for too long. Most CLM tools help you get the deal done, then leave you to figure out what you actually agreed to. Icertis is betting that forward-looking intelligence—predicting problems before they materialize—is where the value lies.

Watch for competitors to follow this playbook. The era of contract management as workflow automation is ending. Contract management as strategic intelligence is beginning.

Reveal just made a strategic decision that will ripple through the entire e-discovery market: their new "Discovery Co-Pilot"—which automates first-pass document review, privilege log generation, and case investigation summaries—is being bundled into standard subscription tiers. Not a premium add-on. Standard.

Think about what that signals. When a major platform commoditizes AI-assisted review, it's declaring that this capability is now table stakes. Every other e-discovery vendor now faces an uncomfortable choice: match the pricing or explain why your AI is worth paying extra for.

The immediate beneficiaries are mid-size firms and corporate legal departments who've been priced out of sophisticated AI tooling. The losers? Document review contract attorneys and vendors whose entire business model was built on the assumption that human eyeballs would always be needed at scale. That assumption just got a lot shakier.

We've been hearing about AI transformation in law for years now. Thomson Reuters just put hard numbers on it, and they're striking: law firm technology spending surged 9.7% in 2025—the largest single-year increase ever recorded in the State of the Legal Market report.

But here's the number that should get your attention: generative AI tools and platforms accounted for over 60% of new technology budgets. Not incremental improvements to existing systems. Not infrastructure upgrades. New AI capabilities.

Perhaps more surprising: mid-size and Am Law 200 firms outpaced the Am Law 100 in technology adoption rates for the first time. The conventional wisdom was always that the largest firms would lead and everyone else would follow. That script has flipped. Smaller firms, it turns out, can move faster when they're not burdened by legacy system integrations and partnership politics.

The report's framing says it all: "We've moved past the experimental phase. In 2025, AI became infrastructure." If your firm is still treating AI as a pilot program or an innovation exercise, you're not early anymore. You're behind.

The regulatory landscape for legal AI just got significantly more complicated—and uncertain. Following Executive Order 14365, the Attorney General has established a new "AI Litigation Task Force" with a pointed mandate: monitor and legally challenge state-level AI regulations that conflict with federal policy or impede interstate commerce.

The timing is not coincidental. California and New York both saw significant AI regulations take effect on January 1st. The administration is essentially putting states on notice: your AI laws may not survive federal preemption challenges.

For legal tech companies and law firms, this creates an uncomfortable limbo. Do you build compliance programs around California's requirements, knowing the DOJ might successfully challenge them? Do you adopt a wait-and-see approach and risk penalties if the state laws survive? The White & Case analysis doesn't mince words: "significant preemption questions" are now front and center.

The practical implication: anyone deploying AI in legal workflows needs a regulatory strategy that accounts for both state compliance and potential federal preemption. Budget for legal uncertainty. It's going to be a messy couple of years.

A London High Court ruling just established a precedent that will reshape how lawyers think about AI usage: prompts and outputs from generative AI systems used in business are discoverable. Full stop.

The case involved a party that had used an internal AI system to analyze case documents and formulate strategy. The opposing side demanded production of the AI system's logs—every prompt, every response, everything. The court agreed, reasoning that if you use AI to do your work, its records are part of that work.

Think through the implications. Every time you paste confidential documents into an AI to get a summary, every strategic question you ask, every draft you iterate on—all of it could be demanded by opposing counsel. The casual way many lawyers currently use AI tools? That needs to change, immediately.

This is a UK ruling, but US courts are watching. The reasoning is straightforward and portable. If you're using AI for case work, start assuming those interactions will eventually be scrutinized. Document retention policies need updating. Privilege protocols need rethinking. The era of casual AI experimentation just ended.