Once AI has been implemented, there are a range of considerations which organisations should focus on to ensure the tool remains aligned with its original purpose and risk assessment. This includes ongoing monitoring for discrimination and bias risks through regular testing, auditing and human oversight, particularly where AI influences decisions affecting employees.
Employers should also guard against "scope creep" by introducing clear controls around new use cases, datasets and functionalities, as material changes to the AI system may trigger fresh legal, privacy or employee representative information and consultation obligations. Strong frameworks should address confidentiality and legal privilege risks, including restrictions on the information that may be input into AI systems, safeguards to prevent the inadvertent disclosure of sensitive or privileged material, and clear rules regarding reliance on AI-generated outputs.
Finally, organisations should establish defined access controls, specifying who can use the AI tool, who can view outputs, the purposes for which outputs may be used, and the approval and accountability mechanisms that apply to higher-risk use cases. This aligns with the need for ongoing AI governance, privilege and confidentiality safeguards, and continuous discrimination-risk management.
Responsible AI in recruitment
The use of AI throughout the recruitment lifecycle can create significant legal and employee relations risks, particularly where systems are used to source candidates, screen applications, conduct assessments, rank candidates, or support hiring decisions. Employers need to consider whether AI tools may disadvantage particular groups, rely on biased or unrepresentative data, or create barriers for candidates with disabilities. Increasingly, regulators are focusing on the transparency of automated recruitment processes, the explainability of decisions, and the extent to which meaningful human oversight is maintained.
Key considerations include discrimination risks, accessibility requirements, data protection obligations, candidate notification requirements, and the governance of third-party recruitment technology providers. Organisations should also consider how AI-driven hiring practices align with broader diversity, equity and inclusion (DEI) objectives and workforce planning strategies.
Performance management and employee monitoring
AI is increasingly being used to support performance evaluation, productivity measurement, workforce analytics, and employee monitoring. These tools can assist employers in identifying trends and driving efficiencies, but they may also influence promotion, compensation, disciplinary action, work allocation, or dismissal decisions. Where employees are subject to significant automated assessments, legal risks may arise in relation to discrimination, privacy, fairness, transparency, consultation obligations, and employee trust.
Employers should carefully assess the purpose and proportionality of monitoring activities, the quality and accuracy of underlying data, and the extent to which AI-generated outputs are reviewed by managers before decisions are taken. Particular attention should be given to the risk of over-reliance on algorithmic outputs and the potential for seemingly neutral systems to produce discriminatory outcomes.
Diversity, Equity and Inclusion (DEI)
AI can both support and undermine DEI objectives. While organisations may seek to use AI to identify workforce trends, improve representation, or reduce human bias, poorly designed systems may replicate or amplify existing inequalities. AI may affect recruitment, promotion, performance management, compensation, succession planning, and workforce restructuring, creating discrimination risks.
Employers should evaluate whether AI systems have a disproportionate impact on protected groups, establish appropriate testing and audit mechanisms, and ensure that DEI considerations are embedded throughout the AI lifecycle. The intersection between AI governance and DEI strategy is becoming an increasingly significant area of regulatory and litigation risk globally.
Workforce management
Many organisations are using AI-powered tools to support workforce planning, scheduling, task allocation, attendance management, and operational decision-making. In some sectors, AI-driven systems may have a direct impact on employees' working conditions, workload, performance expectations, or access to opportunities.
Employers should consider whether workforce decisions are being materially influenced by automated systems and whether appropriate safeguards exist to ensure fairness, consistency, and accountability. This includes assessing the role of human review, providing effective mechanisms for employees to challenge decisions, and ensuring that legal obligations relating to consultation, collective rights, and employee representation are respected where applicable.
Whistleblowing, investigations and employee relations
The adoption of AI may generate new categories of whistleblowing concerns and employee complaints. Employees may raise issues relating to algorithmic bias, unfair treatment, excessive monitoring, inaccurate data, discriminatory outcomes, or failures to comply with legal or ethical AI standards. Organisations may also seek to deploy AI tools within internal investigations, case management processes, or compliance monitoring activities.
Employers should ensure that whistleblowing frameworks and investigation procedures are capable of addressing AI-related concerns and that employees are able to report issues confidently and without fear of retaliation. Clear governance arrangements, escalation procedures, and investigation protocols will be increasingly important as AI becomes more embedded in workplace operations.
Employee use of generative AI
Employees are increasingly using generative AI tools to draft documents, conduct research, analyse information, and support day-to-day activities. While these tools can improve efficiency and productivity, they also create risks relating to confidentiality, data security, intellectual property, accuracy, regulatory compliance, and employee accountability.
Organisations should establish clear expectations regarding acceptable use, oversight requirements, approval processes, and the handling of sensitive information. Training and awareness programmes can help employees understand both the benefits and limitations of AI tools and reinforce the importance of human judgment when relying on AI-generated outputs.
Workforce transformation
AI adoption is likely to reshape job roles, skill requirements, and organisational structures. Employers may need to introduce new training programmes, redesign workflows, create new governance functions, or manage workforce transitions resulting from automation and augmentation. These changes can raise employment law considerations relating to consultation, employee communication, reskilling, redeployment, and organisational change management.
A successful AI strategy requires not only technological implementation but also workforce readiness. Employers should consider how AI impacts employees across the organisation and ensure that change programmes are supported by effective communication, training, and engagement initiatives.
Litigation and disputes
The use of AI creates both substantive employment law risks and new litigation challenges for employers. AI-supported recruitment, performance management, monitoring, disciplinary and dismissal decisions may be scrutinised in discrimination, privacy, whistleblowing, unfair dismissal and other workforce-related claims, particularly where employers cannot clearly explain how an AI-assisted outcome was reached. At the same time, employees, applicants, trade unions and regulators are increasingly using AI tools themselves to analyse workplace practices, prepare complaints, draft pleadings, identify potential causes of action and pursue claims at scale.
AI also raises important issues around evidence, disclosure and legal privilege. Employers should assume that prompts, inputs, outputs, chat logs and other records generated through AI systems may be disclosable in litigation or regulatory investigations unless appropriate controls are in place. Particular care should be taken when using public or third-party AI tools for legal advice, investigations, employee relations matters or dispute management, as the use of such tools may create confidentiality, privilege and data protection risks. Organisations should establish clear protocols governing AI use in contentious matters and maintain robust audit trails, documentation and human oversight processes to support the defence of employment claims and regulatory enquiries.
Key actions to consider
Identify and assess where AI is used across the employment lifecycle and whether it influences employment decisions.
Embed safeguards to ensure AI-supported processes remain fair, transparent and subject to meaningful human oversight.
Establish clear policies and training to support the responsible use of AI by employees and managers.
Maintain effective reporting and escalation channels for AI-related concerns, complaints and investigations.
Identify and assess where AI is used across the employment lifecycle and whether it influences employment decisions.
Embed safeguards to ensure AI-supported processes remain fair, transparent and subject to meaningful human oversight.
Establish clear policies and training to support the responsible use of AI by employees and managers.
Maintain effective reporting and escalation channels for AI-related concerns, complaints and investigations.
© Eversheds Sutherland. All rights reserved. Eversheds Sutherland is a global provider of legal and other services operating through various separate and distinct legal entities. Eversheds Sutherland is the name and brand under which the members of Eversheds Sutherland Limited (Eversheds Sutherland (International) LLP and Eversheds Sutherland (US) LLP) and their respective controlled, managed and affiliated firms and the members of Eversheds Sutherland (Europe) Limited (each an "Eversheds Sutherland Entity" and together the "Eversheds Sutherland Entities") provide legal or other services to clients around the world. Eversheds Sutherland Entities are constituted and regulated in accordance with relevant local regulatory and legal requirements and operate in accordance with their locally registered names. The use of the name Eversheds Sutherland, is for description purposes only and does not imply that the Eversheds Sutherland Entities are in a partnership or are part of a global LLP. The responsibility for the provision of services to the client is defined in the terms of engagement between the instructed firm and the client.
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© Eversheds Sutherland. All rights reserved. Eversheds Sutherland is a global provider of legal and other services operating through various separate and distinct legal entities. Eversheds Sutherland is the name and brand under which the members of Eversheds Sutherland Limited (Eversheds Sutherland (International) LLP and Eversheds Sutherland (US) LLP) and their respective controlled, managed and affiliated firms and the members of Eversheds Sutherland (Europe) Limited (each an "Eversheds Sutherland Entity" and together the "Eversheds Sutherland Entities") provide legal or other services to clients around the world. Eversheds Sutherland Entities are constituted and regulated in accordance with relevant local regulatory and legal requirements and operate in accordance with their locally registered names. The use of the name Eversheds Sutherland, is for description purposes only and does not imply that the Eversheds Sutherland Entities are in a partnership or are part of a global LLP. The responsibility for the provision of services to the client is defined in the terms of engagement between the instructed firm and the client.
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