Securities Class Action Risks and Investment Due Diligence: The Imperative of Corporate Transparency

The rise of securities class action lawsuits in recent years has underscored a critical shift in investor behavior and corporate accountability. As artificial intelligence (AI) reshapes industries, it has also become a focal point for litigation. Between 2023 and 2025, the number of AI-related securities class actions has surged, with 34 cases filed since 2023 and 12 in the first half of 2025 alone, according to a DLA Piper analysis DLA Piper, 2025 AI-related securities class action filings are on the rise. These cases often hinge on allegations of exaggerated AI capabilities, misleading claims about AI-driven revenue, or the concealment of technological limitations. For investors, this trend highlights the urgent need to scrutinize corporate disclosures with a sharper lens, particularly in sectors where AI promises are both transformative and speculative.

The AI Litigation Surge: Courts Demand Precision

Courts have grown increasingly skeptical of vague or aspirational claims about AI. In cases such as Lamontagne v. Tesla Inc. and In re: General Motors Co. Securities Litigation, plaintiffs failed to meet the threshold for proving material misrepresentation because their allegations lacked concrete evidence of harm or specific factual claims, according to a DLA Piper analysis DLA Piper, 2025 AI-related securities class action filings are on the rise. Judges are now demanding clarity on whether AI systems are operational, their actual performance metrics, and how they differ from human-driven processes. This judicial rigor reflects a broader trend: investors and regulators are no longer content with buzzwords like "AI-powered" or "next-generation algorithms." They want verifiable data.

The stakes are high. In 2024, the median settlement value for securities class actions reached $14 million, with an average of $43 million-a five-year high, according to a WilmerHale report WilmerHale, 2025 Year in Review: 2024 AI Securities Litigation Trends. For companies like Innodata and Evolv Technologies, lawsuits over overstated AI capabilities have resulted in costly settlements and reputational damage, according to a DLA Piper analysis DLA Piper, 2025 AI-related securities class action filings are on the rise. These outcomes signal that investors must prioritize due diligence not just on financial metrics but on the technical and operational realities of AI claims.

Corporate Transparency: A Shield Against Litigation

The correlation between corporate transparency and litigation risk is becoming increasingly evident. Academic studies from 2020 to 2025 reveal that firms with weak governance ratings or poor disclosure quality are more likely to face securities lawsuits, according to a ScienceDirect study ScienceDirect, Impact of academic executives on corporate litigation risk. For instance, Edison International faced a class action for allegedly downplaying wildfire risks tied to its power shutoff programs, according to a Rosen Law Firm alert Rosen, Edison International investor alert, while DouYu International was sued for failing to disclose regulatory threats from Chinese authorities, according to a Rosen Law Firm alert Rosen, DouYu investor alert. These cases illustrate how opaque disclosures-particularly in high-risk sectors-invite legal challenges.

A 2025 study of Chinese-listed companies found that firms with academic executives on their boards were significantly less likely to face litigation. These executives, it argued, brought a culture of rigor and transparency that reduced earnings management and disclosure errors, according to a ScienceDirect study ScienceDirect, Impact of academic executives on corporate litigation risk. For global investors, this suggests that governance metrics-such as board composition, audit committee independence, and ESG ratings-should be central to due diligence.

Due Diligence in the Age of AI: Beyond Financial Statements

Traditional due diligence frameworks must evolve to address AI-specific risks. Investors should ask:
1. Technical Validity: Are the AI systems described in disclosures actually deployed at scale? What are their accuracy rates, data inputs, and maintenance costs?
2. Regulatory Alignment: Do companies comply with emerging AI regulations, such as the EU's AI Act or sector-specific guidelines?
3. Scenario Planning: How do companies address risks like algorithmic bias, data privacy breaches, or overreliance on AI for critical decisions?

The failure to address these questions can have dire consequences. Bitfarms Ltd., for example, faced a securities investigation after restating its financials, revealing material misstatements about its AI-driven cryptocurrency operations, according to a Morningstar report Morningstar, Bitfarms securities investigation. Similarly, AppLovin Corporation was sued for allegedly misleading investors about its ad platform's performance through "backdoor installation schemes," according to a Morningstar report Morningstar, AppLovin securities investigation. These cases demonstrate that AI-related risks are not confined to technology firms but span industries from fintech to healthcare.

Conclusion: Transparency as a Competitive Advantage

For investors, the lesson is clear: securities litigation is no longer a peripheral risk but a core consideration in portfolio management. Companies that proactively disclose AI limitations, invest in robust governance structures, and engage with regulators are better positioned to avoid costly lawsuits. Conversely, those that prioritize hype over substance will find themselves increasingly exposed.

As the legal landscape evolves, due diligence must extend beyond balance sheets to include a critical evaluation of corporate transparency. In an era where AI promises are both vast and volatile, the most prudent investors will demand not just innovation but accountability.