This AI Superpower Earns a Voice at the Legal Strategy Table

One of the most compelling developments in AI-enabled legal practice is the emergence of AI as a strategic voice in legal decision-making. This goes far beyond document processing to encompass the kind of pattern recognition and strategic analysis that defines high-level legal counsel.

AI’s pattern recognition capabilities are like superhuman hearing. There are sounds on the spectrum that humans simply can’t perceive. And there are patterns in legal strategy, negotiation dynamics, and dispute resolution that exist but aren’t readily discernible to us. AI’s pattern recognition capabilities can surface relationships and insights hidden in vast bodies of data.

But the patterns themselves are only raw material. The essential act—deciding what to do with them—is still human.

Strategic Collaboration in Practice

I’ve experienced this firsthand when working with outside counsel who have implemented sophisticated AI platforms.

These platforms have massive scale, scope, and resources tied to the crucial requirements of confidentiality and privilege maintenance. This allows for strategic collaboration about what arguments may work with particular judges, what negotiation tactics might be effective, or how to approach complex mediations.

These aren’t one-click solutions that spit out a game plan to follow. Rather, AI becomes another compelling voice in strategic discussions. We regularly go into meetings and collaborate with colleagues, distilling different ideas into a coherent strategy through give-and-take. AI provides yet another—and often entirely distinct—perspective that enriches our decision-making process.

The sophistication of this collaboration can be remarkable. AI can analyze judicial writing patterns to predict how a particular judge might respond to certain argument structures. I’ve heard appellate advocates marvel at AI’s ability to anticipate questions for oral argument to a degree that rivals the insight of a former clerk.

In a transactional environment, AI tools can identify subtle negotiation dynamics by parsing communication patterns and historical outcomes in similar disputes. Most importantly, it can highlight counterintuitive strategies that human experience might dismiss too quickly.

READ MORE OF THE SERIES: GC X AI: Reinventing the General Counsel Role in the AI Era

Pattern Recognition in Strategic Context

In one particularly complex mediation, we collaborated with outside counsel using their AI platform. We analyzed our counterparty’s likely perspectives, motivations, and strategic considerations. The AI didn’t replace our judgment—it supplemented and enhanced it. In this case, the tool surfaced possible patterns that we hadn’t seen, opening up nuanced insights and subtle signals—and leading us to refine our approach to the negotiation.

What struck me was how AI could identify patterns across vastly different contexts and suggest their relevance to our specific situation. The platform drew connections between seemingly unrelated cases, contract structures, and negotiation outcomes to reveal strategic possibilities we hadn’t considered. It wasn’t just faster research; it was genuinely strategic thinking at a speed and scale that individual lawyers couldn’t achieve.

In another negotiation where we were puzzled by—and suspicious about—a counterparty’s view on a potential compromise, I shared the details (and our bafflement) with an AI tool. The feedback reflected a deeply insightful and counterintuitive assessment of how the other party’s position aligned with a broader and more nuanced business need.

The applications are as diverse as our practices. AI’s pattern recognition can reveal how an argument weak in court might be strong in regulatory discussions. It can show how a contractual structure successful in one industry might unlock value in another—or how hidden governance, operational, or compliance risks could be identified and mitigated before they become liabilities.

Multidimensional Approach

This represents a fundamental evolution in how legal strategy gets developed. Traditional legal analysis tends to be linear and precedent-based. AI enables a more multidimensional approach that can simultaneously consider legal precedent, business context, negotiation psychology, and historical outcomes across thousands of similar situations.

Rather than replace legal judgment, this expands the foundation on which that judgment operates. The most effective applications I’ve seen combine AI’s pattern recognition with human insight into what those patterns actually mean in a specific business and legal context.

The result is strategy that’s more informed and creative. AI helps us see opportunities and risks that might otherwise remain invisible, while human judgment determines how to act on those insights to serve our clients’ broader objectives.

Foundation for Innovation

This transformation enables what I think of as strategic legal innovation—moving beyond reactive legal support toward proactive value creation. When AI can bring new patterns and possibilities to light, legal teams can anticipate challenges and opportunities rather than simply react to them.

This shift requires legal leaders who understand both the capabilities and limitations of AI tools. The technology is powerful, but its value depends entirely on how it’s deployed and how its insights are integrated with human expertise and business judgment.

Limits of AI Judgment

It’s also crucial to understand what AI can’t do. Although it excels at correlating patterns to predictive outcomes, it fundamentally lacks the ability to exercise professional judgment.

That judgment is essential to nuanced advice, negotiation, and courtroom advocacy. The analytical perspectives and data patterns AI provides are valuable inputs, but it’s up to human lawyers to balance that efficiency and scope with the irreplaceable value of judgment and accountability.

The most successful legal teams view AI as enhancing rather than supplanting strategic thinking. They use AI to expand their analytical capabilities while maintaining human control over the decisions that matter most. In capturing the strategic value of AI, we—and not HAL—must retain control of the pod bay doors.

The next article in this series will examine the concept of “Legal R&D” as a new strategic capability accelerated by AI, positioning legal departments as proactive value creators.

This article does not necessarily reflect the opinion of Bloomberg Industry Group, Inc., the publisher of Bloomberg Law, Bloomberg Tax, and Bloomberg Government, or its owners.

An immaterial amount of this content was drafted by generative artificial intelligence.

Author Information

Eric Dodson Greenberg is executive vice president, general counsel, and corporate secretary of Cox Media Group.

Write for Us: Author Guidelines