Yes, the next wave of tech lawsuits will be substantially larger than previous privacy settlements—and it’s already happening. In 2025, the top 10 class action settlements alone exceeded $70 billion for the first time, with the total reaching nearly $80 billion across all litigation types. But the most significant shift isn’t just the scale—it’s the expansion beyond privacy violations into copyright infringement, antitrust violations, and biometric data abuse. Google alone settled $833 million in three major cases in 2026 (Play Store, Google Assistant voice recording, and Android data collection), while Anthropic reached a landmark $1.5 billion copyright settlement over AI training data, one of the largest copyright cases in U.S. history.
The evidence is clear: litigation against major tech platforms has entered a new era. Companies that once faced isolated privacy complaints now face coordinated attacks across multiple legal fronts: biometric privacy violations, algorithmic discrimination, copyright infringement, and anti-competitive conduct. These cases are larger, more complex, and harder to resolve quietly with standard payouts. The days of $50 million settlements making headlines are over; now we’re measuring damages in hundreds of millions to billions.
Table of Contents
- Why Tech Lawsuits Are Accelerating Beyond Privacy Settlements
- Record-Breaking Settlement Payouts in 2025 Set New Baseline
- Google, Meta, and Apple Lead the 2026 Settlement Wave
- Emerging Categories: Copyright, Antitrust, and Biometric Data
- Data Privacy Class Actions Continue Growing at Accelerating Rate
- How These Lawsuits Differ from Previous Tech Litigation
- What’s Next: The Future of Tech Litigation in 2026–2027
Why Tech Lawsuits Are Accelerating Beyond Privacy Settlements
The original wave of tech litigation—roughly 2015 to 2020—centered almost entirely on privacy violations: unauthorized data collection, location tracking, and selling user information to third parties. Those cases were significant but often reactive, addressing specific past breaches or practices. The new wave is different because it’s multi-dimensional. Instead of filing one lawsuit about one violation, plaintiffs’ attorneys are now bundling multiple harms: Google faced litigation simultaneously for app store monopoly practices, voice assistant recording without consent, and systematic data collection from third-party apps even after users disabled permissions.
Anthropic’s $1.5 billion copyright settlement marks the transition to entirely new legal terrain. The case alleged that large language models trained on copyrighted material without permission constituted mass infringement—a theory that extends liability far beyond the data privacy framework. This opened the door to similar claims against other AI companies, effectively creating a new litigation category that didn’t exist five years ago. Similarly, Amazon’s facial recognition class action, which alleges violations of Illinois’ Biometric Information Privacy Act (BIPA), targets a specific statutory framework that was designed long before modern AI systems existed but is now being weaponized against them.
Record-Breaking Settlement Payouts in 2025 Set New Baseline
The sheer volume of settlements in 2025 signals a fundamental shift in how courts and regulators treat tech company misconduct. Reaching nearly $80 billion in total class action payouts—with the top 10 settlements alone exceeding $70 billion—wasn’t an anomaly; it reflects the accumulated weight of years of legal discovery, regulatory pressure, and juries’ willingness to impose substantial damages. This baseline matters because it resets expectations for what a “serious” tech settlement looks like. A $200 million payout, which would have been career-defining for any plaintiff’s firm a decade ago, now barely cracks the top 50.
However, these record payouts obscure a critical problem: the actual harm suffered by most plaintiffs is rarely compensated in full. When 100 million users file claims in a settlement, the average payout per person typically ranges from $5 to $50, while the attorney’s fees (usually 25–30% of the settlement) amount to hundreds of millions. This creates an uncomfortable incentive structure where massive settlements generate massive legal fees even if individual consumers see minimal benefit. The 2025 record wasn’t achieved because more people were harmed—it was achieved because the harm to fewer people was quantified in much larger dollar amounts.
Google, Meta, and Apple Lead the 2026 Settlement Wave
Google’s 2026 settlements totaling $833 million represent the company’s largest coordinated payout across multiple platforms in a single year. The breakdown reveals the breadth of liability: $630 million for Play Store antitrust practices (where Google allegedly favored its own apps and charged unfair commissions), $68 million for Google Assistant voice recording without proper disclosure, and $135 million for unauthorized Android data collection from third-party applications even after users disabled location and activity tracking. Each settlement addressed a distinct harm, but together they demonstrated that Google’s business practices created systematic patterns of violation rather than isolated incidents.
meta and Facebook have now accumulated over $3 billion in cumulative settlements related to privacy violations, biometric data collection, and user tracking. The $725 million user privacy settlement (with payouts beginning in September 2025) addressed unauthorized data harvesting for advertising targeting, while the $1.4 billion Texas settlement (2025) specifically targeted the collection of biometric data from photos without explicit consent—a practice that affects every user who uploaded a photo to Facebook or Instagram. Apple’s Siri settlement ($95 million) is particularly significant because payouts already began in January 2026, meaning affected users started receiving checks within weeks of the agreement. For comparison, many older settlements required years of processing before distribution began, during which money earned interest in court-held accounts while plaintiffs waited.
Emerging Categories: Copyright, Antitrust, and Biometric Data
The $1.5 billion Anthropic copyright settlement represents entirely new legal territory. Rather than suing over the collection of user data, authors and publishers sued over the use of their work as training material for AI systems. The precedent is consequential because it establishes that companies cannot freely use copyrighted content to train valuable systems without permission or compensation—a standard that may now apply to OpenAI, Google, Meta, and other companies running large language models. If similar settlements materialize across the AI industry, the liability could dwarf existing privacy litigation, since the training data for a single large model can encompass billions of copyrighted works.
Amazon’s facial recognition litigation and the FTC’s antitrust lawsuit against Amazon’s marketplace practices represent another frontier. The facial recognition case alleges that Amazon’s Rekognition service and Amazon Photos feature violated Illinois’ Biometric Information Privacy Act by collecting and using face data without explicit consent. The antitrust case, scheduled for trial in February 2027, alleges that Amazon used its market position to disadvantage third-party sellers and manipulate search algorithms to favor Amazon-branded products. Both cases target the mechanisms by which tech companies accumulate power and extract value from users—not just the incidental harms, but the structural advantages built into their business models.
Data Privacy Class Actions Continue Growing at Accelerating Rate
The volume of data privacy class actions filed in 2025 reached 1,800+, representing a 25% increase over 2024 and a 200% increase since 2022. This acceleration reflects both genuine increases in harmful practices and the emergence of new litigation targets. Session replay technology, which records user interactions on websites for quality assurance but can capture passwords and sensitive information, became a major litigation category. Website chatbots and tracking pixels used for behavioral advertising similarly became lawsuit magnets. Each of these technologies was largely unregulated a few years ago; now they’re presumed to be legally risky until proven otherwise.
The growth in data privacy litigation creates a paradox for tech companies. Settling cases confirms liability and invites copycat lawsuits; fighting cases in court is expensive and risks even larger jury verdicts. Several tech companies have found themselves facing simultaneous lawsuits in multiple states over the same practice, since each state has its own privacy law with different definitions of consent and harm. This fragmentation means that a practice permitted in California might expose a company to liability in Illinois (which has the strict BIPA law), Texas, or Colorado. The rational response is defensive overengineering—implementing privacy controls and disclosure mechanisms far more extensive than legally required—which paradoxically makes other companies’ practices look worse by comparison.
How These Lawsuits Differ from Previous Tech Litigation
Earlier tech litigation (roughly 2010–2020) typically targeted a specific company for a specific violation discovered through investigation or whistleblowing. Yahoo settling user data breaches, or Facebook settling the Cambridge Analytica scandal, fit this pattern. Those cases were significant but episodic. The current litigation wave is systemic: it assumes that major tech companies have built misconduct into their core business models and files lawsuits to extract the value of that misconduct through damages. The Rodriguez v.
Google verdict ($425 million awarded, with plaintiffs pursuing $2.36 billion on appeal) exemplifies this shift. The case alleged that Google was deliberately collecting data from third-party apps even after users had disabled location tracking and activity history. This wasn’t a data breach or a rogue employee; it was alleged to be a deliberate architectural choice designed to maximize data collection. If plaintiffs succeed on appeal in claiming the full $2.36 billion, it would establish that tech companies face liability not just for data they expose, but for data they knowingly collected in violation of stated user preferences. That standard, if widely applied, would fundamentally change how companies engineer their systems.
What’s Next: The Future of Tech Litigation in 2026–2027
The immediate litigation horizon includes Amazon’s FTC antitrust trial, scheduled for February 2027, which could fundamentally reshape how platforms manage third-party sellers and rank search results. A loss for Amazon could trigger similar antitrust litigation against Google’s search ranking practices, Apple’s App Store policies, and Meta’s preferential treatment of its own content. Beyond that, expect accelerating litigation around AI training data (extending the Anthropic model to OpenAI, Google, and others), biometric privacy (facial recognition, fingerprint scanning, iris recognition), and algorithmic discrimination (algorithms that make lending, hiring, or insurance decisions with disparate impact on protected groups).
The financial scale of these lawsuits will likely exceed anything seen in 2025, not because individual cases are dramatically larger, but because the number of simultaneous lawsuits will increase. A tech company facing 15 parallel lawsuits in different states—each with different legal standards and damage models—faces total potential liability that could exceed the company’s annual revenue. This creates enormous pressure to settle early, which paradoxically generates more litigation because competitors and copycat plaintiffs’ firms will immediately file similar cases. We may be entering a phase where major tech companies budget for litigation costs the way they budget for infrastructure or salaries: as an ongoing, permanent expense of doing business.