Brendan McVeigh, Ken Bertsch, and Maddie Chisholm of Anteris Advisors present a comprehensive analysis of Artificial Intelligence’s transformative impact on corporate governance, drawing from their firm’s latest memorandum. As the 2027 proxy season approaches, the increasing integration of AI across the corporate governance landscape demands a strategic reevaluation by boards and management. This evolution signifies a fundamental shift, moving beyond mere data aggregation to sophisticated analysis, customized policy application, and proactive engagement.
AI’s Pervasive Influence Across the Governance Spectrum
Artificial Intelligence is no longer a peripheral technology; it is rapidly becoming an integral component of corporate governance, influencing stakeholders from every vantage point. Investors are leveraging AI to meticulously process corporate disclosures, refine their proprietary voting policies, and prepare for more impactful engagements with company management. Simultaneously, proxy advisory firms are increasingly adopting AI-driven methodologies to enhance their policy-driven research. Shareholder activists are employing AI to identify lucrative targets and sharpen their strategic theses, while boards are being pressed to demonstrate robust oversight of AI-related risks, alongside a clear understanding of its strategic opportunities and its broader implications for capital, talent, and overall business strategy. Concurrently, board members themselves are beginning to utilize AI to augment their oversight functions, a development that introduces a new layer of governance considerations.
AI’s pervasive influence is fundamentally reshaping the expectations companies must meet to satisfy investors. This analysis delves into these emerging trends, offering critical insights for companies preparing for the 2027 proxy season, a period anticipated to witness the widespread adoption of AI-enabled voting.
The Rise of the Algorithmic Proxy Review
AI’s Ascent from Data Aggregation to Sophisticated Voting Analysis
The landscape of investor stewardship is undergoing a profound transformation, with artificial intelligence moving beyond its initial role in data aggregation to power sophisticated voting analysis and proactive stewardship initiatives. A pivotal moment in this shift occurred in January, when J.P. Morgan Asset Management announced its decision to discontinue the use of traditional proxy advisory services like ISS and Glass Lewis for U.S. voting, opting instead to rely on its proprietary AI platform, Proxy IQ. In a client memo, the firm stated, "By harnessing advanced AI, we no longer need third party data collection or voting recommendations in the U.S." This bold move underscored a growing trend of institutional investors developing in-house capabilities to manage their proxy voting decisions.
Within weeks of J.P. Morgan’s announcement, Wells Fargo transitioned its voting processes to a proprietary policy engine, developed in partnership with Broadridge Financial Solutions. This move further highlighted the industry’s embrace of technology-driven solutions for voting. Norges Bank Investment Management, the world’s largest sovereign wealth fund, has also significantly expanded its use of AI across its investment research operations. The fund is deploying large language models (LLMs) to screen its extensive equity portfolio, comprising over 7,000 companies, for both financial and Environmental, Social, and Governance (ESG) risks. While investors ultimately retain the final decision-making authority, AI is increasingly becoming the primary tool for identifying companies and issues that warrant closer scrutiny.
Evidence of this trend was abundant at the Council of Institutional Investors’ fall 2026 conference, where numerous investors indicated they were actively testing AI-assisted proxy research. Many expressed interest in exploring models or AI agents designed to analyze ballot items, inform voting decisions, and back-test the efficacy of past voting strategies. Some prominent investors, such as the Florida State Board of Administration (SBA), are actively developing their own proprietary AI tools. These custom platforms integrate issuer assessments, historical voting patterns, engagement records, and third-party research, creating a holistic view for decision-making. The emergence of new fintech providers and platform capabilities further signals the growing maturity of this market segment, pointing towards a broader industry shift towards leveraging technology to organize evidence and apply investment policies consistently, while firmly maintaining investor responsibility for the ultimate vote.
The U.S. Securities and Exchange Commission (SEC) has also signaled an openness to these advancements. Brian Daly, Director of the SEC’s Division of Investment Management, remarked shortly after J.P. Morgan’s announcement that agentic AI in proxy voting is "not science fiction, it’s a near-term reality." He emphasized that the responsible deployment of AI agents necessitates rigorous training, human oversight of their output, and a commitment to transparency, auditability, and consistency in their application. The increasing political scrutiny faced by traditional proxy advisors has also served as a catalyst, accelerating the move towards customized, machine-assisted voting solutions. Proponents of AI in this space argue that the technology can significantly expedite proxy voting analysis, thereby expanding the critical window between the publication of proxy statements and shareholder meetings. This expanded timeframe allows for more thorough internal discussions of complex voting items and more meaningful engagements with companies. Historically, many investors deferred their detailed evaluation of voting matters until the release of proxy advisor reports, which typically occurred only two weeks prior to the shareholder meeting.
Proxy Advisors Adapt: Embracing Customization and AI Integration
The leading proxy advisory firms are not immune to this technological wave and are actively rebuilding their operational frameworks around AI. ISS has introduced PolicySteward, a platform designed to generate automated, data-driven voting recommendations accompanied by clear rationale text. Following client testing in October 2026, early adopters gained access in December, with a full launch anticipated in January 2027. Glass Lewis, recognizing the diverging priorities of investors and the capabilities offered by AI, is transitioning from a single, monolithic research perspective to offering four distinct research viewpoints. These new perspectives are slated to be integrated into its research offerings from September 2027, building upon its established Benchmark policy which will continue through the 2027 proxy season. In a significant development in September 2026, Glass Lewis partnered with Clarity AI to create an integrated platform encompassing corporate governance, AI analytics, engagement, and proxy voting. A Glass Lewis paper published in April 2026 acknowledged AI’s potential to accelerate proxy research and ensure the consistent application of voting policies at scale. However, the firm also stressed that fiduciary accountability cannot be delegated to AI, advocating for the integration of human expertise throughout the process, rather than solely for output verification.
Beyond the established players, a new cohort of providers, some deliberately avoiding the "proxy advisor" label, are emerging with AI-enabled platforms. These platforms are designed to assist institutional investor stewardship teams in applying customized voting policies and generating timely, company-specific research with unprecedented speed. Notable examples include Broadridge Financial Solutions, Tumelo, Pennant, Proxywise AI, and Proxify. In some instances, these innovative services possess the potential to challenge and even displace incumbent proxy advisors.
The Implications of Machine Reading for Corporate Disclosure
The advent of machine reading in proxy analysis presents a fundamental challenge to traditional corporate disclosure practices. While a human investor can readily incorporate contextual information not explicitly stated in a proxy, such as insights from previous engagement calls, a long-standing relationship with management, or the underlying strategic rationale behind a decision, AI models operate more literally. However, this literal interpretation can also be a powerful tool for uncovering nuances. AI can meticulously identify subtle shifts in language, changes in peer group definitions, footnotes that contradict headline narratives, or unexplained variations in key metrics.
This necessitates a new discipline in disclosure. Key information buried within charts may not be reliably extracted by AI. Rationales discussed in private but absent from public materials might not survive automated review. Furthermore, inconsistencies in terminology across various company documents—including proxy statements, 10-Ks, earnings materials, press releases, and investor decks—can lead different AI systems to construct divergent interpretations of the company’s story. Companies must therefore carefully consider how AI tools will interpret and summarize their disclosures, ensuring that critical rationales are captured, important context is not omitted, and any inconsistencies are proactively addressed.
AI Oversight Takes Center Stage on the Board Agenda
Escalating Board-Level Focus on AI Oversight
Board-level disclosures regarding AI oversight have experienced a dramatic surge in prominence since 2023. According to ISS Corporate data, the percentage of S&P 500 companies disclosing AI oversight efforts has more than doubled, rising from approximately 15% in 2023 to 31% in 2026. Among the largest corporations, a majority now explicitly designate a committee or the full board as responsible for AI oversight, with 54% of S&P 100 companies reporting such arrangements in their 2026 proxies. Despite this growing awareness, a significant gap persists in the disclosure of director AI training, a reality acknowledged candidly by directors themselves. A 2026 survey by PwC found that a substantial 71% of directors identified AI as the most critical skill their boards need to strengthen to provide more effective oversight.
This expertise gap is particularly concerning given that AI transcends the realm of simple technological risk. It encompasses both substantial risks and vast opportunities, profoundly impacting a company’s strategy, capital allocation, operational efficiency, talent management, and competitive positioning.
Investor Scrutiny Moves Beyond Boilerplate Language
Investors are increasingly scrutinizing the practical implementation of AI oversight, holding companies accountable when deficiencies are identified. CalPERS, for instance, explicitly stated in its 2026 proxy voting guidelines that it may withhold votes from director nominees if there is evidence of "failed and/or insufficient oversight of AI related risks." Vanguard’s stewardship report highlights that boards are now tasked with overseeing both AI risks and opportunities, and are actively working to enhance director knowledge of AI. ISS’s Governance QualityScore now incorporates ratings for board AI oversight, the presence of AI-skilled directors, and the quality of AI policy disclosures. While AI is currently more frequently a topic of engagement rather than a direct driver of voting decisions, its significance is undeniable. In their 2026 proxy statements, companies like Equifax, AIG, and Truist explicitly attributed their expanded AI disclosures to direct conversations with shareholders.
Investors are vocally advocating for disclosures that move beyond generic statements. Simply stating that the board "oversees AI" is no longer deemed sufficient. A growing number of critical questions are being posed by investors, focusing on the depth and breadth of this oversight.
AI-Related Shareholder Proposals Expand in Scope
The 2026 proxy season saw a continued increase in AI-related shareholder proposals filed by S&P 500 companies, with 12 proposals submitted, up from six in the previous year. These proposals are also becoming more specific, addressing issues beyond general AI governance to encompass data privacy, the spread of misinformation, workforce impacts, environmental costs, and the ethical considerations of military or dual-use AI applications. Several proposals specifically focused on AI’s environmental footprint, while others called for enhanced board or committee oversight of AI risks. Despite the growing number of proposals, shareholder support remained limited, with no AI-related proposal achieving majority support. The highest support recorded for a proposal that went to a vote was approximately 26%.
The Evolving Landscape of AI Oversight Structures
Companies are exploring a variety of organizational structures for AI oversight. These range from full board oversight and dedicated technology committees to distributed responsibilities across existing committees, specialized AI committees, and hybrid models. Microsoft, in its most recent proxy statement, detailed board-level oversight of AI, with its Environmental, Social, and Public Policy Committee specifically overseeing responsible AI development. The company treats data center capacity and supply chain management as board-level risks. Salesforce, meanwhile, has revised its committee charters to distribute AI oversight across its five board committees. Walmart channels its AI initiatives through its Technology and eCommerce Committee and extended the tenure of a director with critical technology, AI, and cybersecurity expertise beyond the standard term limit. Logitech explicitly outlines a dual-sided oversight approach, where the full board reviews AI from both an opportunity and risk perspective. Groupon established a standalone AI Committee, chaired by a founder of an AI company, to address these evolving needs.
Board Expertise: A Growing Investor Imperative
Board expertise remains a critical focus area for investors. A skills matrix that simply labels a director as "AI experienced" carries less weight if the director’s appointment record does not demonstrate substantial leadership in technology or data-driven initiatives. The most robust approach appears to be a combination of director education, genuine operational technology expertise, and access to external specialists, with the company’s strategy clearly articulated in its proxy statement.
A significant portion of the reported increase in AI expertise on boards may stem from relabeling existing skills rather than the appointment of entirely new directors with dedicated AI backgrounds. Currently, 37% of S&P 500 companies cite AI experience for at least one director, a notable increase from 11% in 2022. Investors are actively analyzing these changes, often with the assistance of AI tools themselves.
When boards are actively seeking to enhance their technology and AI expertise, they are increasingly recruiting experienced operators, including senior data and technology executives. For instance, J.P. Morgan’s Chief Data & Analytics Officer was appointed to the CVS Health board, and CVS Health’s Chief Data & Analytics Officer joined the Choice Hotels board. These appointments reflect a trend of bringing in individuals with deep practical knowledge of AI implementation. Similarly, AI expertise is becoming a factor in activist-driven board changes. Sysco’s recent board additions, facilitated by the D. E. Shaw group, included a technology committee that was subsequently renamed the "Artificial Intelligence Transformation & Technology Committee," underscoring the strategic importance of AI.
AI’s Emerging Role in Executive Compensation
The integration of AI metrics into executive compensation programs is still in its nascent stages. A 2026 analysis by Mercer found that among early S&P 500 filers, only 14% incorporated explicit AI metrics into their short-term incentive plans, with a mere 2% doing so for long-term incentives. However, companies like IBM and Salesforce have publicly disclosed the inclusion of AI metrics within their executive compensation frameworks in their most recent proxy statements, signaling a growing trend.
AI as an Activist Catalyst and Tactical Enabler
AI’s Growing Prominence in Activist Campaigns
Artificial intelligence has emerged as a significant theme in activist investor campaigns. In the first half of 2026, AI was a featured element in approximately one in six U.S. activist campaigns, and nearly 30% of campaigns within the technology sector. A common thread in activist criticisms revolves around companies’ perceived slowness in adopting AI or their inadequate communication of their AI strategies. Activists are consistently urging companies to develop and implement AI strategies designed to unlock shareholder value.
For example, Starboard Value informed Tripadvisor in February that, "despite the risk of AI disintermediation increasing daily," the company had been "massively late and incredibly slow" to introduce a compelling AI-enabled product. Elliott Investment Management has actively pursued AI-related themes across multiple companies in 2026. The firm reportedly pressed the London Stock Exchange Group to articulate its AI strategy and address concerns that large language models could undermine its data business. Elliott also took a stake in Synopsys, based on the view that AI is driving increased investment and engineering complexity in chip design, and secured a board seat in May. In June, Elliott placed a partner on Hewlett Packard Enterprise’s board under a 2025 cooperation agreement, asserting that the company stands to benefit significantly from the buildout of AI infrastructure. Irenic Capital has advocated for Snap to reduce costs and leverage AI for data monetization. Spruce Point has argued that the market undervalues Zoom’s strategic pivot towards AI, and Starboard has urged Riot Platforms to reorient its Texas power capacity from bitcoin mining to AI data centers.
AI Accelerates Activist Tactics and Strategies
Beyond its role as a thematic driver, AI is also profoundly accelerating the tactics employed by activist investors. AI’s capabilities are enhancing target screening, peer analysis, document review, thesis development, and the creation of campaign materials. Established activist firms are making substantial investments in their internal data and AI capabilities. In May 2026, Elliott hired a former Blackstone data science executive to lead its global research and data science group, comprising approximately 40 research staff and three data scientists, with a mandate to develop AI capabilities across the firm’s operations.
This technological advancement has the potential to make previously cost-prohibitive campaigns viable for a broader range of investment funds. AI enables activists to screen a larger universe of potential targets, manage multiple campaigns concurrently, and accelerate the transition from initial thesis formulation to public pressure. A "fight deck" that once required weeks to produce can now be drafted in a matter of minutes, albeit with significant limitations that still necessitate human oversight. For corporate boards, this development compresses the time available to identify and rectify vulnerabilities before they are exploited by an activist. Proactive strategic planning and robust governance are thus more critical than ever.
AI: A Dual-Edged Sword of Risk and Opportunity for Boards
For boards of directors, the critical question has evolved from a singular focus on risk management to a more comprehensive assessment: "Can we explain and defend our AI strategy relative to peers, in terms an activist could not improve upon?" The inquiry is no longer merely about disclosure ("Did we disclose AI?") but about the clarity and defensibility of the public record, enabling investors, activists, and voting systems to understand how AI influences the company’s strategy, decision-making, and overall governance. Boards must be prepared to meet this elevated standard by 2027.
AI’s Impact on Investor-Company Engagement
Investors Arrive Better Prepared for Engagements
Artificial intelligence is demonstrably enhancing the preparedness of investors for engagements with corporate management. Investors can now efficiently process a company’s disclosure history, compare it with peer performance, internal voting guidelines, past engagement records, and public activist arguments. This leads to more informed and productive engagements, allowing investors to prepare more effectively and enter discussions with a deeper, more nuanced understanding of the company and the issues at hand.
AI is particularly well-suited for discrete analytical tasks such as extracting specific disclosures, conducting peer comparisons, and identifying key questions. However, its role should be to inform, not to supplant, human judgment. As AI-assisted research becomes available earlier in the proxy process, investors may no longer need to wait for traditional proxy advisor reports before initiating engagement. This shift could expand the window for shareholder dialogue and increase the overall volume of engagement, providing companies with more opportunities to address concerns and influence voting decisions proactively.
Companies Gain Insight into Investor Perceptions Through AI
The very tools that investors employ to analyze companies can also be utilized by corporations to gain a critical perspective on how they are perceived by the investment community. Companies can leverage AI to stress-test their own disclosures, identify inconsistencies across various public materials, anticipate potential investor questions, and benchmark their strategic positioning against peers and evolving investor expectations. This internal application of AI can foster greater transparency and a more proactive approach to governance and disclosure.
The Governance Implications of Board-Level AI Use
Navigating the Governance Challenges of AI in the Boardroom
Artificial intelligence offers the potential to significantly enhance board preparation by assisting directors in synthesizing complex information, identifying emerging risks, and formulating more incisive questions. However, the use of public LLMs also introduces significant governance challenges, including the potential exposure of confidential information and concerns related to security, privacy, privilege, and recordkeeping. Furthermore, AI-generated outputs may contain inaccuracies or biases, underscoring the indispensable role of human judgment and verification.
The integration of AI into boardroom operations necessitates a thoughtful approach to oversight and accountability. The objective should not be to prohibit AI assistance but to establish a secure and responsible framework for its utilization. One promising approach involves the corporate secretary utilizing approved AI tools to generate AI-assisted summaries alongside the original board materials. Ultimately, the challenge for boards lies in harnessing the manifold benefits of AI while rigorously maintaining appropriate safeguards, robust oversight, and clear lines of accountability.
Strategic Imperatives for Boards and Companies Ahead of the 2027 Season
As the corporate world gears up for the 2027 proxy season, Anteris Advisors recommends a series of proactive steps for boards and companies to navigate the increasingly AI-driven governance landscape:
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Write for Both Readers: Ensure that critical data presented in charts is also articulated in the main text. Provide clear explanations for compensation decisions and any exceptions. Crucially, maintain consistent terminology across all disclosures and engagement materials to avoid misinterpretation by both human and machine readers.
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Disclose AI Oversight Mechanisms: Clearly identify the entity responsible for AI oversight, delineate how responsibilities are divided among committees and individuals, and specify the processes for reporting, escalating, and measuring AI-related issues. Transparency in this area is paramount for investor confidence.
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Align Expertise with Appointment Records: Move beyond superficial "relabeled" skills matrices. Demonstrate genuine operating expertise in AI, provide evidence of relevant director education, or establish a credible bench of external AI specialists. Investor scrutiny of board composition is increasingly sophisticated.
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Stress-Test Strategy Against Activist Scenarios: Proactively identify potential strategic gaps in areas such as speed of AI adoption, monetization strategies, productivity enhancements, data utilization, infrastructure development, capital allocation, and disclosure practices. Anticipating activist critiques can strengthen a company’s defenses.
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Establish Clear Rules for Board AI Usage: Define approved AI tools for board use, explicitly outline prohibited information that should not be inputted into AI systems, mandate human review and verification of AI outputs, and establish clear escalation protocols for any identified issues or concerns.
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Re-evaluate Voting Pattern Predictions: Identify institutional holders that are likely utilizing AI-enabled voting systems, custom policy engines, or pass-through voting arrangements. Historical voting patterns may become less predictive as AI influences decision-making at scale.
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Proactive Shareholder Engagement: Initiate dialogue with shareholders well in advance of the proxy season to understand their evolving expectations regarding AI. Addressing potential vulnerabilities and concerns proactively can significantly mitigate risks.
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Begin Preparation Early: The preparation for the 2027 proxy season is not a future endeavor; it is a present reality. The ultimate goal should not be the creation of more sophisticated-sounding disclosures, but rather the establishment of more defensible governance structures and robust strategic frameworks.
