Print
E-MailJon Solorzano is a Partner at Vinson & Elkins LLP. This post is based on his Vinson & Elkins memorandum.
1. Update Your Disclosure Playbook
Major investors are increasingly using AI to decide how to vote proxies, and JPMorgan’s industry-first decision to replace its external proxy advisors with an in-house AI tool signals that the trend is accelerating. Coupled with the SEC’s renewed focus on materiality and streamlined disclosure under Regulation S-K, this new environment calls for a new disclosure playbook.
Companies should now draft disclosures with both human and AI readers in mind, delivering concise, decision-useful information that reasonable investors would deem important and presenting disclosure in machine-readable formats. They should also monitor developments around shareholder proposals and track how major shareholders vote. As AI-driven analyses increasingly shape first impressions of regulatory filings, past voting patterns could become a less reliable indicator of future votes.
2. Navigate Regulatory Fragmentation
Amid ESG’s emergence as a cultural and political flashpoint, the U.S. federal government has pulled back from ESG-related regulation of public companies. Yet despite federal retrenchment and anti-ESG initiatives in red states, some blue states and international jurisdictions continue to forge ahead, complicating business for companies operating across state lines or overseas. Similar fault lines are opening around AI: in the absence of comprehensive federal legislation, various states have adopted their own AI laws. Notably, the FTC recently proposed a policy statement suggesting that certain state AI laws — such as Colorado’s AI Act — may be preempted by federal consumer protection law, a signal that Washington may seek to override fragmented state AI regulation through existing authority.
This fragmentation creates real compliance tension: meeting ESG-related requirements in some jurisdictions can invite investigation or litigation risk in others, and the patchwork of state sustainability, and now AI, laws compounds the challenge for businesses with cross-jurisdictional operations. To navigate these dynamics, companies should manage compliance risk while being mindful of evolving stakeholder expectations, including regularly cataloging requirements and enforcement activity everywhere they operate, assessing ESG- and AI-related regulatory exposure, documenting the business rationale behind major initiatives, and implementing appropriate governance structures and controls (as further discussed below).
3. Make Resilience a Core Priority
As extreme weather grows more frequent and physical disruptions grow more severe, climate-related risks are fast becoming material business issues, drawing outsize attention from investors, regulators, and other stakeholders alike. Investing in physical resilience is now a financial and strategic imperative, and companies must recalibrate their priorities in response.
The key is to embed climate risk management and resiliency strategy into decision-making at the board and executive levels. Treating adaptation not just as a defensive measure, but as a competitive advantage, will position companies to protect their operations, respond faster to disruptions, and capture growth opportunities as capital flows shift.
4. Implement AI Governance and Formalize AI Oversight
As AI continues to rapidly transform how companies operate and compete, effective management of AI’s risks and opportunities is crucial. While AI can drive innovation and enhance efficiency, its potential risks are far-reaching: inaccurate or biased outputs and hallucinations; privacy, data and cybersecurity exposure; intellectual-property and third-party-vendor dependencies; negative impacts on product sales, workforce pipeline, and culture; and disclosure missteps — including unsubstantiated overstatements of AI capabilities (AI washing) or omitting material AI use or dependencies (AI hushing) — can lead to reputational, regulatory, and other consequences.
To manage AI risks while capturing AI benefits, companies should implement a governance framework that defines how AI may be used, assigns clear ownership, integrates AI into existing enterprise risk management, and maintains a current inventory of the systems in use. Board oversight of AI risks and value creation is equally important: it should be formalized at the full-board or committee level, with a regular cadence for management reporting on AI strategy, risks, incidents, and performance. Additionally, directors should develop AI fluency to understand and meaningfully engage with management on these matters — this may be accomplished with education and training.
5. Balance Short-Term Pressures with Long-Term Strategy
Corporate boards face numerous near-term pressures: geopolitical tensions and supply-chain disruptions; climate change and technological revolutions; tariff uncertainty, cyberthreats, regulatory upheaval, reputational crises, and more. Yet as boards work to navigate the pressures of today, they must be careful not to lose sight of their long-term strategy.
Balancing the two means thinking in both quarters and decades, and showing that the company is positioned to succeed on both timelines. Map all of the company’s stakeholders and how their needs and expectations could evolve over time. Listen closely to their views. Communicate clearly about how the company is executing on pressing business imperatives while preparing to adapt as conditions change.
