Baker McKenzie announced in January 2026 that it would eliminate approximately 1,000 positions across its global offices, citing the firm's investment in AI systems that now perform work previously done by associates, paralegals, and support staff. The announcement was framed as a strategic transformation. It will be remembered as the opening shot in the AI displacement litigation wave. For related analysis, see our coverage of algorithmic hiring discrimination. For related analysis, see our coverage of agentic AI in finance.
Baker McKenzie is not the first company to lay off workers because of AI. But it is the first global law firm, the world's largest by headcount, to do so at this scale and to say so publicly. That candor may prove to be a litigation gift. When a company explicitly attributes layoffs to AI adoption, it answers the causation question that plaintiffs in displacement cases usually struggle to prove. Baker McKenzie told us why these people lost their jobs. Now the courts will decide whether the way those decisions were made was lawful.
The Wrongful Termination Angle
At the most basic level, affected employees will argue wrongful termination. The specific legal theories vary by jurisdiction, but the core questions are consistent. Did the firm follow its own policies and contractual obligations regarding termination? Were employees given adequate notice under the WARN Act, which requires 60 days' written notice for mass layoffs affecting 100 or more employees at a single site? Were severance agreements and non-compete provisions handled lawfully?
The WARN Act question is particularly interesting. Baker McKenzie's global structure, with employees spread across dozens of offices, may complicate the threshold analysis. But for offices where the layoffs are concentrated, WARN Act compliance will be scrutinized. The firm's decision to announce the layoffs publicly before notifying all affected employees individually could itself create liability.
Beyond statutory requirements, some affected employees will have contractual claims. Associates at major firms often have employment agreements that specify termination procedures, notice periods, and severance terms. If Baker McKenzie's AI-driven restructuring did not follow these contractual procedures, the breach of contract claims will be straightforward.
Disparate Impact: The Statistical Case
The more significant litigation will involve disparate impact claims under Title VII and the Age Discrimination in Employment Act (ADEA). This is where AI expert witnesses become essential.
When a company uses AI to determine which positions to eliminate, the selection process is not neutral. AI systems that evaluate employee productivity, identify "redundant" roles, or assess which functions can be automated all make decisions that correlate with protected characteristics. Older workers are more likely to be in roles that involve routine document review, a task AI performs well. Women are disproportionately represented in paralegal and administrative support roles, the categories most affected by Baker McKenzie's cuts. Workers with disabilities who rely on accommodations that structured their workflow around traditional processes may find their roles classified as "automatable" at higher rates.
The disparate impact framework does not require proof of discriminatory intent. It requires statistical evidence that a facially neutral employment practice disproportionately affects a protected group, combined with a showing that the practice is not justified by business necessity. If the demographic data shows that Baker McKenzie's layoffs disproportionately affected workers over 40, or women, or members of any other protected class, the firm will bear the burden of demonstrating that its selection criteria were job-related and consistent with business necessity.
When a firm uses AI to decide which humans to keep and which to let go, the algorithm's selection criteria become employment practices subject to Title VII scrutiny. Every variable the AI considered is a potential vector for disparate impact.
Age Discrimination: The ADEA Problem
The age discrimination claims may be the strongest. The ADEA prohibits employment practices that discriminate against workers aged 40 and older. AI-driven workforce restructuring creates age discrimination risk in several ways.
First, the roles most susceptible to AI automation tend to be occupied by more experienced, and therefore older, workers. Senior paralegals, experienced document reviewers, and veteran support staff have spent decades developing expertise in processes that AI can now replicate. Their seniority, which correlates directly with age, makes them both more expensive and more replaceable from the firm's perspective.
Second, if Baker McKenzie used any AI system to evaluate employee performance or determine which roles to eliminate, the system's training data likely reflects historical patterns that correlate with age. Metrics like "adaptability to new technology" or "efficiency per billable hour" may systematically disadvantage older workers without explicitly considering age.
Third, the firm's public framing of the layoffs as a forward-looking technological transformation implicitly devalues the skills of workers whose expertise is rooted in traditional practice. This framing, while not direct evidence of discriminatory intent, creates a narrative that plaintiffs' attorneys will use to establish a culture of age-based preference for younger, more "tech-native" workers.
Why AI Expert Witnesses Are Essential
Litigating these claims requires understanding how the AI systems actually work. If Baker McKenzie used AI to identify positions for elimination, the plaintiffs need an expert who can examine the system's methodology, training data, and decision criteria. If the firm used AI productivity metrics to evaluate employees, the expert needs to assess whether those metrics are valid measures of job performance or proxies for protected characteristics.
On the defense side, Baker McKenzie will need experts who can demonstrate that its AI systems were designed and validated to avoid discriminatory outcomes, that the selection criteria were job-related, and that the firm conducted adverse impact analyses before implementing the layoffs. If the firm did not conduct such analyses, that omission itself becomes evidence of negligence.
The expert witness role in AI displacement cases is technically demanding. It requires understanding both the AI systems involved and the statistical methods used to detect disparate impact. The expert must be able to explain to a jury how an algorithm that never explicitly considers age or gender can nonetheless produce outcomes that systematically disadvantage older workers or women. This is not intuitive, and the cases will turn on the quality of the expert testimony.
The Coming Wave
Baker McKenzie is the first. It will not be the last. Every major professional services firm is evaluating how AI will reshape its workforce. The consulting firms, the accounting firms, the banks, the insurance companies: they are all running the same analysis Baker McKenzie ran. They are all reaching the same conclusion. And they will all face the same legal exposure when they act on it.
The difference between Baker McKenzie and the firms that follow will be preparation. Firms that conduct rigorous adverse impact analyses before implementing AI-driven layoffs, that document their selection criteria and validate them against disparate impact, that provide meaningful retraining opportunities and comply with every procedural requirement, will face litigation but will be better positioned to defend it. Firms that move fast and figure it out later will find themselves in the position Baker McKenzie is in now: defending decisions that were made with more attention to efficiency than to legal compliance.
For employment attorneys, this is the new frontier. AI displacement litigation will be a defining practice area for the next decade. The claims are novel, the damages are significant, and the need for AI expert witnesses is urgent. Baker McKenzie just proved the concept. The rest of the docket is coming.
The Criterion AI provides expert witness services and litigation support for matters involving artificial intelligence, machine learning, and algorithmic decision-making. For a confidential consultation on an active or anticipated matter, contact us at info@thecriterionai.com or call (617) 798-9715.