ARTICLE
30 January 2026

Top 10 Privacy, AI & Cybersecurity Issues For 2026

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Jackson Lewis P.C.

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Focused on employment and labor law since 1958, Jackson Lewis P.C.’s 1,100+ attorneys located in major cities nationwide consistently identify and respond to new ways workplace law intersects business. We help employers develop proactive strategies, strong policies and business-oriented solutions to cultivate high-functioning workforces that are engaged, stable and diverse, and share our clients’ goals to emphasize inclusivity and respect for the contribution of every employee.
As Data Privacy Day 2026 approaches, organizations face an inflection point in privacy, artificial intelligence, and cybersecurity compliance. The pace of technological adoption, in particular AI tools, continues...
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As Data Privacy Day 2026 approaches, organizations face an inflection point in privacy, artificial intelligence, and cybersecurity compliance. The pace of technological adoption, in particular AI tools, continues to outstrip legal, governance, and risk frameworks. At the same time, regulators, plaintiffs, and businesses are increasingly focused on how data is collected, used, monitored, and safeguarded.

Below are our Top 10 Privacy, AI, and Cybersecurity Issues for 2026.

1. AI Governance Becomes Operational and Enforceable

AI governance in 2026 will be judged less by aspirational principles and more by documented processes, controls, and accountability. Organizations using AI for recruiting, managing performance, improving efficiency and security, and creating content, among a myriad of other use cases, will be expected to demonstrate how AI systems are developed, deployed, and governed, considering a global patchwork of existing and emerging laws and regulations affecting AI and related technologies.

Action items for 2026:

  • Maintain an enterprise AI inventory, including shadow or embedded AI features.
  • Classify AI systems by risk and use case (HR, monitoring, security, consumer-facing)
  • Establish cross-functional AI governance (legal, privacy/infosec, HR, marketing, finance, operations)
  • Implement documentation and review processes for high-risk AI systems.

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2. AI-Driven Workplace Monitoring Under Scrutiny

AI-enabled monitoring tools (dashcams, performance management solutions, wearables, etc.) are increasingly used to track productivity, behavior, communications, and engagement. These tools raise heightened concerns around employee privacy, fairness, transparency, and proportionality, especially when AI generates insights or scores that influence employment decisions.

Regulators and plaintiffs are paying closer attention to whether monitoring is over-collection by design, and whether AI outputs are explainable and defensible.

Action items for 2026:

  • Audit existing monitoring and productivity tools for AI functionality.
  • Assess whether monitoring practices align with data minimization principles.
  • Update employee notices and policies to clearly explain AI-driven monitoring.
  • Ensure human review and appeal mechanisms for AI-influenced decisions.

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3. Biometrics Expand and So Does Legal Exposure

Biometric data collection continues to expand beyond fingerprints and facial recognition to include voiceprints, behavioral identifiers, and AI-derived biometric inferences. Litigation under Illinois' Biometric Information Privacy Act (BIPA) remains active, but risk is spreading through broader definitions of sensitive data in state privacy laws.

Action items for 2026:

  • Identify all biometric and biometric-adjacent data collected directly or indirectly.
  • Review vendor tools to ensure compliance.
  • Update biometric notices, consent processes, and retention schedules.
  • Align biometric compliance efforts with broader privacy programs.

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4. CIPA Litigation and Website Tracking Technologies Continue to Evolve

California Invasion of Privacy Act (CIPA) litigation related to session replay tools, chat features, analytics platforms, and tracking pixels remains a major risk area, even as legal theories evolve. AI-enhanced tracking tools that capture richer interactions only heighten exposure. Organizations often underestimate the privacy implications of seemingly routine website and chatbot technologies.

Action items for 2026:

  • Conduct a comprehensive audit of website and app tracking technologies.
  • Reassess consent banners, disclosures, and opt-out mechanisms.
  • Evaluate AI-enabled chatbots and analytics for interception risks.
  • Monitor litigation trends and adjust risk tolerance accordingly.

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5. State Comprehensive Privacy Laws Enter an Implementation and Enforcement Phase

Organizations are no longer preparing for state privacy laws, but they are living under them. The California Consumer Privacy Act (CCPA), along with other state laws, imposes increasing operational obligations.

California's risk assessment requirements, cybersecurity audit mandates, and automated decision-making technology (ADMT) regulations represent a significant shift toward proactive compliance.

Action items for 2026:

  • Comply with annual review and update requirements.
  • Conduct CCPA-mandated risk assessments for high-risk processing.
  • Prepare for cybersecurity audit obligations and documentation expectations.
  • Inventory and assess ADMT used in employment, monitoring, and consumer contexts.

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6. Data Minimization Becomes One of the Most Challenging Compliance Obligations

Data minimization has moved from an abstract compliance principle to a central operational challenge. Modern AI systems, monitoring tools, and security platforms are frequently architected to collect and retain expansive datasets by default, even when narrower data sets would suffice. This design approach increasingly conflicts with legal obligations that require organizations to limit data collection to what is necessary, proportionate, and purpose-specific, not only in terms of retention, but at the point of collection itself. As regulatory scrutiny intensifies, organizations must be prepared to explain why specific categories of data were collected, how those decisions align with defined business purposes, and whether less intrusive alternatives were reasonably available.

Action items for 2026:

  • Reassess data collection across AI, HR, and security systems.
  • Implement retention limits and transfer restrictions tied to business necessity and legal risk.
  • Challenge "collect now, justify later" deployments that rely on large-scale or continuous data exports.
  • Integrate data minimization and Bulk Data Transfer rule analysis into AI governance and system design reviews.

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7. Importance of the DOJ Bulk Transfer Rule

In 2026, bulk sensitive data transfers are no longer a background compliance issue but a regulated risk category in their own right. Under the Department of Justice's Bulk Data Transfer Rule, which took effect in 2025, organizations must closely assess whether large-scale transfers or access to U.S. sensitive personal or government-related data involve countries of concern or covered persons. The rule reaches a wide range of transactions, including vendor, employment, and service arrangements, and imposes affirmative obligations around due diligence, access controls, and ongoing monitoring.

Action items for 2026:

  • Update data mapping activities to include sensitive data collection and data storage.
  • Catalog where bulk data transfers occur, including transfers between internal systems, vendors, and cross-border environments. Develop a compliance program that includes due diligence steps, vendor agreement language, and internal access controls.
  • Evaluate the purpose of each bulk transfer.

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8. UK and EU Data Protection Laws Reforms

Recent and proposed amendments to UK and EU data protection laws are designed to clarify or simplify compliance obligations for organizations, regardless of sector. Changes will impact both commercial and workplace data handling practices.

UK: Data Use and Access Act (DUAA)

The UK has enacted the Data Use and Access Act, which amends key provisions of the UK General Data Protection Regulation (UK GDPR) and the Privacy and Electronic Communications Regulations (PECR). These reforms relate to subject access requests and complaints, automated processing, the lawful basis to process, cookies, direct marketing, and cross-border transfers, among others. Implementation is occurring in stages, with changes relating to subject access requests, complaints, and automated decision-making taking effect over the next few months.

EU: Digital Omnibus Regulation

The European Commission has proposed a Digital Omnibus Regulation, which introduces amendments to the EU General Data Protection Regulation. Proposed changes include redefining "personal data", simplifying the personal data breach notification process, clarifying the data subject access process, and managing cookies.

Action items for 2026:

  • Review forthcoming guidance from the UK Information Commissioner's Office.
    • Implement a data subject complaint process.
    • Review existing lawful bases and purposes for processing.
    • Prepare any necessary updates for employee training.
  • Monitor the progress of the proposed Digital Omnibus Regulation.
    • Review data inventories in the event the definition of personal data is revised.
    • Update data subject access response processes.
    • Review the use and nature of any cookies deployed on the organization's website.

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9. Vendor and Third-Party AI Risk Management Intensifies

Most organizations buy rather than build AI technologies. They buy from vendors such as recruiting platforms, notetaking tools, monitoring applications, cybersecurity providers, and analytics services—whose systems depend on large-scale data ingestion. From procurement to MSA negotiation to record retention obligations, novel and challenging issues as organizations seek to minimize third-party and fourth-party service provider risk. Importantly, vendor contracts have not kept pace with the nature of AI models or how to allocate risk.

Action items for 2026:

  • Update vendor diligence to include privacy, security, and AI-specific risk assessments.
  • Revise contracts to address AI training data, secondary use, audit rights, and allocation of liability.
  • Monitor downstream data sharing, model updates, and cross-border or large-scale data movements.

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10. Privacy, AI, and Cybersecurity Fully Converge

In 2026, the lines between privacy, cybersecurity, and AI will continue to blur, leaving organizations that silo these disciplines to face increasing regulatory, litigation, and operational risk.

Action items for 2026:

  • Integrate privacy, AI governance, and cybersecurity leadership.
  • Harmonize risk assessments and reporting structures.
  • Align training and compliance messaging across functions.
  • Treating privacy and AI governance as enterprise risk issues.

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As Data Privacy Day 2026 highlights, the challenge is no longer identifying emerging risks, but it is managing them at scale, across systems, and in real time. AI, biometrics, monitoring technologies, and expanding privacy laws demand a more mature, integrated approach to compliance and governance.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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