AI Shapes Shareholder Voting, Boards Must Adapt Governance Practices

JPMorgan Chase’s asset and wealth management unit announced it will use AI to guide proxy voting decisions for U.S. listed companies, moving away from traditional third-party advisors. This decision comes amid growing interest in leveraging AI for governance-related tasks. It follows a broader shift among large investors to internalize stewardship capabilities and explore algorithmic efficiency.

The adoption of AI in proxy voting is being supported by regulatory scrutiny of third-party advisory firms. SEC Division of Investment management Director Brian Daly said AI tools could provide a viable alternative to traditional advisory services. He noted these tools could handle scale and complexity in proxy voting more efficiently.

President Donald Trump’s executive order on proxy advisors has intensified this transition. The order directs the SEC to evaluate whether these firms should register as investment advisers and assess their role in shaping corporate policy.

Why Did This Shift Happen?

Proxy advisors have grown from limited-scope research providers into influential gatekeepers of governance decisions. Their recommendations can shape industry-wide outcomes, despite not owning shares in the companies they advise.

Over time, reliance on proxy advisors created an efficiency-driven governance model. But as standardization increased, it often came at the cost of contextual judgment. Governance decisions were increasingly reduced to binary outcomes.

How Is AI Changing the Landscape?

AI offers the same scalability and speed as proxy advisors but introduces new challenges. Unlike proxy advisors, AI systems do not replace judgment outright—they shift it upstream to model design, data training, and override protocols.

This change redefines how governance disclosures are interpreted. Algorithms analyze filings, media, and other public sources continuously. Boards must now consider how their decisions are interpreted by machines, which prioritize literal meaning and historical patterns.

What Do Boards Need to Do Differently?

Boards face a new set of governance questions. How are they being assessed by AI systems? Where might their actions be misread? Who is accountable if something goes wrong? These issues are becoming more urgent as AI systems make decisions with minimal human oversight.

For example, ambiguous language in board communications can confuse algorithms. Delays in CEO succession, even if intentional, may be flagged as governance weaknesses. Errors in AI-driven decisions may go unnoticed until after voting occurs.

What Are Analysts Watching Next?

Boards should focus on clarity and transparency in their disclosures. By explaining governance philosophy and strategic trade-offs, they can reduce the risk of misinterpretation. This approach also helps align with the human judgment embedded in AI systems.

Engagement with investors must also evolve. Boards need to ask not only about voting outcomes but also about how decisions are made. They should seek clarity on where human oversight exists and how errors can be corrected.

The shift to AI-assisted governance does not eliminate the need for accountability. It simply changes where it resides. Boards must understand how these systems operate and what role they play in shaping governance outcomes.

What Does the Future Hold for Governance?

In an AI-assisted voting environment, silence and ambiguity will carry greater weight. Consistency in communication and decision-making will become a governance asset. The most effective boards will be those that document their judgment and explain their choices clearly.

As AI becomes more prevalent, governance will become more automated, but not less complex. Boards must navigate this transition by adapting their practices and engaging proactively with both investors and technology.

The future of governance will depend on how well boards can communicate their values and rationale—not just to human analysts, but to the algorithms that are increasingly shaping corporate outcomes.

According to earnings reports, C3 AI Inc. is experiencing significant growth in its AI platform. This shift reflects broader trends in governance and technology integration.