Artificial intelligence (AI) is reshaping the corporate landscape, offering transformative potential and fostering innovation across industries. But as AI becomes more deeply integrated into business operations, it introduces complex challenges, particularly around transparency and the disclosure of AI-related risks. A recent lawsuit filed in the US District Court for the Southern District of New York—Sarria v. Telus International (Cda) Inc. et al., No. 1:25-cv-00889 (S.D.N.Y. Jan 30, 2025)—highlights the dual risks associated with AI-related disclosures: the dangers posed by action and inaction alike. The Telus lawsuit underscores not only the importance of legally compliant corporate disclosures, but also the dangers that can accompany corporate transparency. Maintaining a carefully tailored insurance program can help to mitigate those dangers.

Background

On January 30, 2025, a class action was brought against Telus International (CDA) Inc., a Canadian company, along with its former and current corporate leaders. Known for its digital solutions enhancing customer experience, including AI services, cloud solutions and user interface design, Telus faces allegations of failing to disclose crucial information about its AI initiatives.

The lawsuit claims that Telus failed to inform stakeholders that its AI offerings required the cannibalization of higher-margin products, that profitability declines could result from its AI development and that the shift toward AI could exert greater pressure on company margins than had been disclosed. When these risks became reality, Telus’ stock dropped precipitously and the lawsuit followed. According to the complaint, the omissions allegedly constitute violations of Sections 10(b) and 20(a) of the Securities Exchange Act of 1934 and Rule 10b-5.

Implications for Corporate Risk Profiles

As we have explained previously, businesses face AI-related disclosure risks for affirmative misstatements. Telus highlights another important part of this conversation in the form of potential liability for the failure to make AI-related risk disclosures. Put differently, companies can face securities claims for both understating and overstating AI-related risks (the latter often being referred to as “AI washing”).

These risks are growing. Indeed, according Cornerstone’s recent securities class action report, the pace of AI-related securities litigation has increased, with 15 filings in 2024 after only 7 such filings in 2023. Moreover, every cohort of AI-related securities filings were dismissed at a lower rate than other core federal filings.

Insurance as a Risk Management Tool

Considering the potential for AI-related disclosure lawsuits, businesses may wish to strategically consider insurance as a risk mitigation tool. Key considerations include:

1. Audit Business-Specific AI Risk: As we have explained before, AI risks are inherently unique to each business, heavily influenced by how AI is integrated and the jurisdictions in which a business operates. Companies may want to conduct thorough audits to identify these risks, especially as they navigate an increasingly complex regulatory landscape shaped by a patchwork of state and federal policies.
2. Involve Relevant Stakeholders: Effective risk assessments should involve relevant stakeholders, including various business units, third-party vendors and AI providers. This comprehensive approach ensures that all facets of a company’s AI risk profile are thoroughly evaluated and addressed
3. Consider AI Training and Educational Initiatives: Given the rapidly developing nature of AI and its corresponding risks, businesses may wish to consider education and training initiatives for employees, officers and board members alike. After all, developing effective strategies for mitigating AI risks can turn in the first instance on a familiarity with AI technologies themselves and the risks they pose.
4. Evaluate Insurance Needs Holistically: Following business-specific AI audits, companies may wish to meticulously review their insurance programs to identify potential coverage gaps that could lead to uninsured liabilities. Directors and officers (D&O) programs can be particularly important, as they can serve as a critical line of defense against lawsuits similar to the Telus class action. As we explained in a recent blog post, there are several key features of a successful D&O insurance review that can help increase the likelihood that insurance picks up the tab for potential settlements or judgments.
5. Consider AI-Specific Policy Language: As insurers adapt to the evolving AI landscape, companies should be vigilant about reviewing their policies for AI exclusions and limitations. In cases where traditional insurance products fall short, businesses might consider AI-specific policies or endorsements, such as Munich Re’s aiSure, to facilitate comprehensive coverage that aligns with their specific risk profiles.

Conclusion

The integration of AI into business operations presents both a promising opportunity and a multifaceted challenge. Companies may wish to navigate these complexities with care, ensuring transparency in their AI-related disclosures while leveraging insurance and stakeholder involvement to safeguard against potential liabilities.