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Data as Value – and Risk: Litigation Issues Facing Technology Providers and Their Customers

Published
Score
16

Why it matters

Organizations across all sectors are facing a wave of litigation over their data practices and AI systems. According to a Baker Donelson report, these legal challenges now extend well beyond technology companies and data brokers to affect organizations of every size that rely on data for operations, network security, regulatory compliance, and contractual obligations. The disputes involve civil liberties groups, workers' advocates, and privacy organizations pursuing claims centered on data privacy violations, algorithmic bias, unauthorized data use, AI system liability, and worker surveillance.

The legal landscape governing these disputes remains fragmented and incomplete. GDPR and HIPAA provide foundational protections in their respective domains, but significant gaps persist in how AI systems are regulated—particularly regarding transparency, algorithmic accountability, and cross-border data flows. Courts are currently establishing precedents on data ownership rights, contractual obligations in AI procurement, and corporate accountability for algorithmic harms, meaning the rules are still being written.

Organizations should treat this moment as urgent. As AI adoption accelerates, liability exposure is unprecedented, and early litigation is establishing the legal standards that will govern data use and algorithmic systems for years to come. Attorneys advising clients on data strategy, vendor contracts, and AI implementation should prioritize understanding these emerging obligations before costly disputes arise.

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