Workforce decisions have emerged as a critically likely pathway to class action litigation, according to a recent midyear survey of corporate counsel conducted by the prominent law firm Norton Rose Fulbright. The findings indicate a significant shift in the legal risk landscape for U.S. organizations, with nearly half of respondents identifying workforce changes as a primary catalyst for future legal challenges. Specifically, 47% of those surveyed pinpointed actions such as layoffs, significant policy revisions, and other employment-related shifts as probable triggers for class action lawsuits against their organizations by 2026. This places workforce decisions second only to data breaches, which remain the leading concern at 51%, underscoring the escalating legal vulnerabilities inherent in managing human capital.
The comprehensive midyear findings are derived from a 2026 poll that gathered insights from 135 in-house counsel across various U.S. organizations. These legal professionals represent diverse and critical sectors, including energy, financial institutions, healthcare, and technology, providing a broad and insightful perspective on prevailing litigation trends. This survey serves as a crucial follow-up to Norton Rose Fulbright’s broader 2026 Annual Litigation Trends Survey, offering a timely pulse check on evolving legal exposures. The increased prominence of workforce decisions as a litigation threat reflects a complex interplay of economic pressures, evolving employee expectations, and an increasingly intricate regulatory environment.
The Rising Tide of State-Level Employment Risk
A notable trend highlighted by the survey is the disproportionate growth of employment and labor dispute exposure at the state level compared to federal challenges. Respondents reported a 44% increase in state-level exposure, significantly higher than the 39% growth observed at the federal level. This pattern is not arbitrary but rather a direct consequence of decentralized enforcement mechanisms and the proliferation of new, often more stringent, employment requirements enacted by individual states. Jurisdictions such as California and New York are at the forefront of this legislative wave, pioneering regulations that often exceed federal standards and create a patchwork of compliance obligations for businesses operating across state lines.
Kimberly Cheeseman, co-head of litigation and disputes at Norton Rose Fulbright in Houston, articulated the implications of this shift, stating, "State-level employment exposure is rising as plaintiffs look to jurisdictions they view as more favorable, especially as federal interpretations shift. For multistate employers, that dynamic increases compliance complexity and forum risk in a very real way." Her observation underscores the strategic calculus employed by plaintiffs’ attorneys, who increasingly leverage state-specific statutes that may offer broader protections, more generous damage awards, or easier routes to class certification. This creates a challenging environment for multistate employers, who must meticulously navigate a continually multiplying set of requirements that vary significantly from one state to another, often demanding bespoke policies and procedures.
This fragmented legal landscape can be attributed to several factors. Historically, states have served as "laboratories of democracy," experimenting with laws to address specific local concerns. In recent years, this has accelerated, particularly in areas like wage and hour regulations, pay equity, predictive scheduling, paid leave mandates, and restrictions on non-compete agreements. California, for instance, with its Private Attorneys General Act (PAGA), empowers employees to sue on behalf of the state for labor code violations, creating a potent mechanism for class-action-like claims that circumvent traditional class action procedural hurdles. New York has similarly enacted robust protections, including expansive paid family leave laws and stringent workplace harassment prevention mandates. The federal government, by contrast, has seen a more static or even, at times, a narrowing of certain employee protections under various administrations, prompting plaintiffs to seek more favorable avenues at the state level.
AI in Hiring and Workforce Management: A New Frontier of Legal Exposure
Beyond traditional workforce decisions, the survey also meticulously tracked the materialization of AI-related legal risk within organizations. The rapid integration of Artificial Intelligence tools into human resources functions, from candidate screening and recruitment to performance management and workforce analytics, has introduced a novel and complex layer of legal exposure. In the firm’s annual survey conducted late last year, a substantial 59% of respondents identified managing AI litigation risk as a significant challenge. By midyear, the urgency of this concern had translated into tangible dispute exposure, with 46% reporting an increase in federal dispute exposure tied to AI and 42% citing state-level increases.
HR is highlighted as a particularly vulnerable area, given AI’s increasing role in critical employment decisions. A significant 43% of respondents anticipate that bias or discrimination claims involving AI will escalate their litigation exposure through the end of 2026. Furthermore, 39% specifically pointed to employment or workforce decisions that leverage AI-assisted tools as a source of heightened risk. For larger organizations, particularly those with over $1 billion in revenue—companies most likely to have extensively deployed AI screening and workforce tools—this latter figure rises to 41%, underscoring the direct correlation between AI adoption scale and perceived legal risk.
Cheeseman elaborated on the immediate implications of this technological shift: "AI-assisted hiring tools are creating real uncertainty for employers, particularly around bias and discrimination claims. The risk isn’t theoretical—it’s already being tested in courts and before the EEOC." This statement is supported by emerging legal challenges. For instance, the case against Workday, an HR software provider, alleging that its AI-powered screening tools discriminate against older job applicants and those with disabilities, illustrates how quickly theoretical concerns can become real-world lawsuits. Similarly, the New York City Automated Employment Decision Tools (AEDT) law, effective since July 2023, mandates bias audits for AI tools used in hiring and promotion, signaling a growing regulatory trend aimed at mitigating algorithmic discrimination.
The legal risks associated with AI in HR are multifaceted. They include, but are not limited to, disparate impact claims where an AI system, though seemingly neutral, disproportionately screens out protected groups (e.g., based on age, race, gender, disability). Algorithmic bias can stem from biased training data, flawed algorithm design, or even the proxy variables AI might inadvertently use that correlate with protected characteristics. Additionally, there are concerns regarding transparency (the "black box" problem of AI), explainability, data privacy, and the potential for AI to perpetuate or amplify existing human biases. The timeline of AI regulation is still nascent but rapidly developing, with federal agencies like the EEOC and DOJ issuing guidance and state and local governments stepping in to fill regulatory gaps, creating a complex and evolving compliance landscape for employers.
Exposed Industries: A Sectoral Analysis of Risk
The survey also provided a granular look at how different industries are disproportionately affected by these burgeoning employment and labor risks.
Energy Sector: Respondents from the energy sector reported the highest employment and labor exposure across all categories, with 57% at the federal level and 51% at the state level. They were also the most likely to identify workforce changes as a probable class action trigger. This heightened vulnerability is attributed to several intrinsic characteristics of the industry. The energy sector is often characterized by cyclical workforce volatility, heavily influenced by fluctuating commodity prices that dictate periods of rapid expansion followed by significant layoffs or restructuring. Furthermore, a heavy reliance on hourly workers and contractors inherently raises wage and hour compliance risks, including complexities around overtime pay, meal and rest breaks, and proper worker classification (employee vs. independent contractor). Misclassification, in particular, can lead to substantial back pay, penalties, and benefits liability, making it a prime target for class action litigation. The safety-critical nature of many energy roles also adds another layer of regulatory and legal complexity.
Healthcare Sector: In the healthcare industry, employment and labor issues topped the list of state-level exposure at 50%. This sector faces unique and persistent challenges, primarily driven by chronic labor shortages, particularly for skilled professionals like nurses and specialized technicians. These shortages necessitate reliance on contract labor, such as travel nurses or locum tenens physicians, which introduces complexities around agency relationships, pay structures, and compliance with various state licensing and labor laws. Wage-and-hour complexity is also a significant factor, stemming from 24/7 operations, on-call requirements, shift differentials, and intricate regulations governing overtime and breaks for diverse healthcare roles. The emotional and physically demanding nature of healthcare work also contributes to higher rates of burnout, turnover, and potential claims related to working conditions.
Financial Institutions and Technology: While not as acutely exposed as energy or healthcare in the employment and labor categories, these sectors face their own distinct set of risks. Financial institutions, for example, are highly regulated and often deal with sensitive customer data, making them prime targets for data breach class actions. However, they also face employment risks related to compensation structures, whistleblower protections, and internal compliance failures. The technology sector, characterized by rapid innovation and frequent restructuring, is prone to class action risks stemming from mass layoffs, intellectual property disputes, and challenges related to remote work policies and global talent management. Both sectors are also early adopters of AI, meaning they share the growing AI-related litigation risks highlighted in the survey.
Strategic Imperatives for Mitigating Litigation Risk
The insights gleaned from Norton Rose Fulbright’s survey point unequivocally to a growing and urgent need for a paradigm shift in how organizations approach workforce planning and decision-making. The traditional view of human resources as solely an operational function must evolve to integrate a robust, proactive legal risk management framework.
Earlier and Integrated Legal Review: The most critical takeaway is the imperative for earlier and more thorough legal review in virtually all workforce planning initiatives. Actions that were once considered purely operational or strategic, such as mass layoffs, the implementation of return-to-office mandates, or changes to employee benefits packages, now demonstrably carry significant class action risk. Legal counsel should be engaged not merely as a reactive measure once a decision is made but as an integral partner from the conceptualization phase of any major workforce change. This ensures that legal implications are identified and addressed proactively, rather than retrospectively.
Tighter Documentation and Data Integrity: In an increasingly litigious environment, meticulous and consistent documentation is paramount. For every workforce decision, particularly those involving layoffs, performance management, disciplinary actions, or policy changes, organizations must maintain clear, defensible, and comprehensive records. This includes documenting the legitimate, non-discriminatory business reasons for decisions, any analyses conducted (e.g., disparate impact analyses for layoffs), communications with employees, and the application of policies. Furthermore, with the rise of AI, ensuring the integrity and unbiased nature of the data used to train and operate these systems becomes critical, requiring rigorous data governance protocols.
Closer Coordination with Counsel: The survey findings emphasize the need for ongoing, collaborative relationships between HR teams and in-house or external legal counsel. This partnership should extend beyond specific transactions to include regular consultations on emerging legal trends, proactive policy development, and the review of HR practices. Legal teams can provide invaluable guidance on compliance with complex state-level regulations, interpretation of new AI-related laws, and best practices for mitigating litigation risk across the employee lifecycle.
Rigorous Oversight of AI Vendors and Testing Protocols: For organizations deploying AI in hiring and workforce management, the due diligence process for selecting and managing vendors must be significantly enhanced. This includes thoroughly vetting vendors for their commitment to ethical AI development, transparent methodologies, and robust bias testing capabilities. Employers must demand evidence of independent audits of AI tools for bias and discrimination, ensure compliance with evolving regulatory requirements (like NYC’s AEDT law), and establish internal protocols for monitoring the performance and impact of AI systems. Regular evaluations, coupled with human oversight, are crucial to identify and rectify any discriminatory outcomes that may emerge from algorithmic decision-making.
Enhanced Training and Awareness: HR professionals, managers, and executives need ongoing training on the evolving legal landscape, including state-specific employment laws, anti-discrimination statutes, and the legal implications of using AI in HR. Such training should foster a culture of compliance, emphasize bias awareness (both human and algorithmic), and equip leaders with the knowledge to make legally sound workforce decisions.
Robust Internal Grievance Mechanisms: Establishing and promoting effective internal complaint and dispute resolution mechanisms can serve as an early warning system and potentially resolve issues before they escalate into formal litigation. A transparent and trusted process for employees to raise concerns can demonstrate an organization’s commitment to fairness and often de-escalate potential class actions.
In conclusion, the Norton Rose Fulbright survey paints a clear picture of an employment litigation landscape in flux, characterized by a dual threat: the enduring complexity of workforce decisions and the nascent but rapidly growing risks associated with AI adoption. For organizations navigating this intricate environment, a proactive, legally informed, and strategically integrated approach to human capital management is no longer merely best practice—it is an existential necessity for safeguarding against significant financial, reputational, and operational repercussions. The onus is on employers to adapt swiftly, ensuring their HR strategies are not only efficient and effective but also robustly defensible in the face of an increasingly vigilant legal and regulatory framework.
