By Philip R. Bautista

A recent Taft program on artificial intelligence brought together in-house and outside counsel to examine how AI is reshaping legal work, governance, and risk. The discussion made clear that AI is already influencing client expectations, legal workflows, and business operations, while simultaneously reinforcing the importance of human judgment in the delivery of legal advice.

Across the keynote and panel discussion, several themes emerged for intellectual property and broader corporate practitioners. AI is accelerating routine work, expanding regulatory complexity, redefining contractual risk allocation, and prompting organizations to revisit foundational questions relating to data, ownership, accountability, and governance.

The General Counsel Perspective

The program opened with a fireside conversation featuring Jerico Phillips, Senior Corporate Counsel at Cox Enterprises and President of the ACC Georgia Chapter. Phillips framed AI principally as a leadership issue for general counsel rather than a purely technical development.

His central message was that AI is likely to change materially how legal work is performed, particularly with respect to routine and process-driven tasks, but it will not replace the judgment, leadership, and accountability that define the role of general counsel. Tools that support first-draft contract language, document review, and research assistance may continue to improve efficiency, but their increasing use only heightens the need for lawyers to exercise sound judgment and provide strategic counsel.

As those tasks become more automated, Phillips emphasized that the value of in-house lawyers will continue to migrate toward prioritization, counseling, risk assessment, and business decision support. In that model, the modern general counsel is not merely overseeing legal production, but helping the business move with speed and confidence while navigating legal, ethical, reputational, and operational considerations in parallel.

Phillips also underscored that AI should be understood as a catalyst for rethinking how legal departments create value, not as a threat to professional relevance. The more significant question is no longer whether AI can perform certain legal functions, but how lawyers should redirect their time toward the areas where human judgment is most critical.

Human Judgment and Legal Leadership

A related theme in Phillips’s remarks was that AI cannot substitute for people-centered leadership. Technology may assist with language generation, pattern recognition, and workflow acceleration, but it cannot replace human responsibility, credibility, empathy, or the trust that underpins effective legal counsel.

That distinction has practical consequences for legal departments and outside counsel alike. As AI assumes a greater role in routine work, the profession’s differentiators become clearer: judgment, issue-spotting, prioritization, communication, and the ability to guide organizations through ambiguity and change.

Phillips’s remarks also pointed to a broader mindset shift. High-performing legal teams will increasingly define excellence not by the volume of drafting or review performed manually, but by the quality of insight delivered, the clarity of advice provided, and the business impact of that advice.

The Regulatory Environment

The panel discussion then turned to the legal and regulatory landscape, with Taft partner Jackie Benson addressing current and emerging AI regulation, particularly at the state level. Benson emphasized that AI regulation is no longer theoretical and is increasingly multi-jurisdictional in scope.

In particular, Benson highlighted Colorado as an important jurisdiction to watch, alongside states such as California, Texas, and Illinois. Her broader point, however, was that organizations can no longer assess AI risk solely by reference to where they are headquartered; they must also consider where customers, employees, and users are located, and how those touchpoints may trigger different regulatory obligations.

Benson identified several themes that are emerging across enacted and proposed AI laws, including transparency requirements, bias and discrimination mitigation, governance of automated decision-making, deep fakes, data security, and consumer protections. She also noted that certain sectors, especially insurance and financial services, are already facing more targeted scrutiny in connection with model development, validation, and monitoring.

Just as important, Benson’s remarks emphasized thoughtful AI governance rather than mere box-checking. For many organizations, the core challenge is not simply determining what a statute requires, but building an internal framework capable of governing both enterprise use of AI and the risks presented by third-party tools and vendors.

Benson also addressed the tension between state-level regulation and proposed federal regulations and guidance. For businesses seeking to implement AI tools across jurisdictions, that divergence creates practical uncertainty and reinforces the need for close coordination among legal, compliance, and technical teams.

Quantum and Cybersecurity Considerations

Benson further addressed the intersection of AI, cybersecurity, and quantum computing. She noted that while the possibility of “Q-Day” may still appear distant, organizations should begin evaluating the long-term implications of quantum technologies that could make currently used encryption standards obsolete.

Her guidance was measured and practical. Rather than suggesting immediate wholesale change, she pointed to foundational steps such as inventorying cryptographic assets, identifying sensitive long-duration data, monitoring developments in post-quantum cryptography, and engaging vendors regarding their preparedness.

For IP-intensive businesses, these issues are particularly significant. Trade secret protection, confidentiality obligations, and broader data-security assumptions may all require closer examination as AI  and quantum capabilities evolve alongside longer-term cybersecurity risks.

AI in Transactions and Procurement

The panel also examined the transactional implications of AI, with Taft partner Jeffrey Kosc discussing the effect of AI on technology transactions, procurement, and vendor management.

Kosc characterized the current moment as evolutionary rather than revolutionary. AI has not fundamentally displaced transactional practice, but it has introduced a set of issues that can no longer be treated as peripheral, particularly where contracts fail to address data rights, ownership of outputs, training uses, security obligations, compliance concerns, and allocation of liability.

His discussion focused in particular on the centrality of data. In AI-enabled transactions, the key questions increasingly include who owns the relevant data, who may access it, how it may be used, whether it may be used for model training, who owns resulting outputs, and what remedies exist if something goes wrong.

Kosc also emphasized that AI now appears throughout the procurement lifecycle, from vendor marketing and evaluation to implementation and ongoing oversight. That reality means organizations must consider not only contract language, but also monitoring, risk assessment, and governance practices that remain effective after the deal is signed.

Implications for IP Counsel

Taken together, the keynote and panel discussion underscored that AI is narrowing the distance between technology, legal risk, and business strategy. For IP practitioners and outside counsel, that shift carries several practical implications.

First, clients increasingly need guidance that is not merely doctrinal, but strategic and operational. Questions involving AI-generated content, training data, contractual protections, confidentiality, and regulatory compliance require advice that connects legal analysis with how AI systems are deployed in practice.

Second, outside counsel are likely to face growing pressure to deliver value beyond traditional drafting and routine production. As clients adopt AI-enabled tools internally, the areas in which outside counsel will differentiate themselves are likely to include judgment, foresight, pattern recognition, and sector-specific perspective.

Third, the governance issues discussed throughout the program are closely tied to core intellectual property concerns. Data governance, model governance, cybersecurity, confidentiality, licensing, and ownership all intersect directly with the questions that sit at the center of modern IP practice.

The Broader Takeaway

The program ultimately presented AI not as an existential threat to the legal profession, but as a leadership and strategy challenge. For general counsel, the opportunity lies in using AI to free legal teams to focus more heavily on judgment-intensive work, organizational leadership, and business guidance. For outside counsel, the opportunity lies in pairing technological fluency with the human capabilities clients continue to value most: discernment, accountability, and practical judgment.

AI will continue to change how legal work is performed and how responsibilities are divided between in-house and outside counsel. It does not, however, alter the central role of lawyers in helping organizations make informed, lawful, and sound decisions in a rapidly changing environment.