In today’s fast-evolving digital landscape, generative artificial intelligence (AI) has become a powerful tool that employees increasingly rely on for a variety of tasks. From drafting emails and producing reports to generating creative content and analyzing data, these technologies are reshaping how work gets done. As organizations integrate AI into their daily operations, employers face the challenge of managing its use effectively. Balancing innovation with accountability and legal compliance is critical to ensuring that AI enhances productivity without significant drawbacks.
Data Privacy and Confidentiality
One of the foremost legal challenges is ensuring that the use of AI complies with data privacy requirements. As employees input sensitive or confidential information into AI systems, there is an increased risk of data exposure — especially if third-party platforms are involved. Employers must establish protocols that protect sensitive information and comply with privacy laws.
In addition to international frameworks such as the General Data Protection Regulation (GDPR) in the European Union, several U.S. states have enacted robust privacy laws that may be implicated by AI use. For example, the California Consumer Privacy Act (CCPA), along with its successor, the California Privacy Rights Act (CPRA), imposes strict requirements on how personal data is collected, processed, and shared. These laws can affect employers who use generative AI to handle employee data, as any inadvertent exposure or misuse of sensitive information could trigger compliance issues making it essential for employers to evaluate the data flows associated with AI tools and implement measures to mitigate risks.
One particular risk to employer privacy stemming from AI use in the workplace is the use of AI systems that do not strictly limit how user inputs can be used — for example, for further training or fine-tuning of the model. Examples of such systems include certain commercial versions of OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Bard. Information that is entered into these systems might be shared with another unintended user and retained in the AI’s network. For these reasons, businesses should exercise caution whenever inputting sensitive or confidential information into an AI tool and should understand whether such information is used to train the AI model or if it is transmitted or stored outside the business’s network.
Oversight and Accountability
Integrating AI into work processes raises important questions about employee oversight and accountability. Although AI can automate and streamline tasks, employees are ultimately responsible for verifying the accuracy of its outputs. This dual responsibility can blur the lines between machine assistance and human oversight, potentially leading to errors or omissions. Employers must develop clear guidelines specifying how AI outputs should be reviewed and validated to mitigate risks that could lead to operational or legal challenges.
Moreover, as noted above, employers should implement guidelines prohibiting employees from inputting confidential information into AI systems such as certain commercial versions of ChatGPT, Claude, and Bard that do not strictly limit how user inputs can be used, in order to protect such information from potential disclosure.
Overtime Classification
Generative AI can change the nature of an employee’s work by redistributing tasks and shifting job responsibilities, with direct implications under the Fair Labor Standards Act and its state equivalents. As AI tools assume repetitive functions, employees may take on managerial responsibilities such as monitoring, verifying, or supplementing AI-generated work. Employers must carefully assess whether these new responsibilities warrant adjustments in employee classifications. Indeed, under the FLSA an employee whose primary duty is the performance of office or non-manual work directly related to the management or general business operations of the employer and who exercises discretion and independent judgment with respect to matters of significance may qualify under the administrative exemption, allowing employers to classify such employees as exempt from overtime pay.
Employee Monitoring
The National Labor Relations Act safeguards employees’ rights to engage in protected concerted activities, including discussing wages, working conditions, and unionizing efforts. As employers increasingly deploy generative AI to monitor productivity and manage workflow, it is critical to examine how such technology intersects with these NLRA protections.
When AI systems are used to analyze employee communications or monitor work patterns, there is a risk that the technology could inadvertently capture or suppress protected activities. For instance, if an AI tool scans internal emails, chat messages, or other digital communications to assess productivity, it might also detect conversations about working conditions or collective grievances. Such monitoring could be considered to discourage employees from discussing issues that they are legally entitled to discuss. Employees may become reluctant to express concerns or engage in discussions about their rights if they believe their communications are subject to constant AI analysis — risking a violation of the NLRA.
Conclusion
Managing use of generative AI is not a one-time effort; it requires continuous assessment and policy refinement. Organizations must adopt a proactive, collaborative approach that involves HR, IT, legal, and — when applicable — labor representatives. Developing policies that are responsive to technological advancements and regulatory changes is essential. Regular training sessions, routine audits of AI outputs, and transparent communication with employees are all critical components of an effective management strategy. By fostering a culture of continuous improvement, employers can ensure that AI tools are used responsibly to enhance performance while safeguarding the organization against legal risks.
The integration of generative AI into the workplace presents both exciting opportunities and complex challenges. Employers who proactively manage the use of these technologies can drive innovation and boost productivity while mitigating legal risks related to data privacy, employee monitoring, and accountability. Comprehensive policies, continuous training, and a culture of transparent communication are essential to navigating this evolving landscape. As generative AI continues to reshape work processes, staying informed and adaptable remains the key to transforming potential risks into sustainable competitive advantages.
For guidance on adapting to the developing legal landscape use of generative AI in the workplace, consult your Akerman Labor and Employment attorney.