AI in the Workplace: How Employers Can Prepare Their Business for AI Adoption

Parliament’s House of Commons Business and Trade Committee has launched an inquiry into “Artificial Intelligence, business and the future of the workforce” to examine the opportunities and costs of Artificial Intelligence (AI) for employers and workers, and to shape future government priorities.

With the pace of firm clarity and guidance for employers being slower to develop than workplace adoption of AI, employers need to make judgment calls now to embrace inevitable change driven by AI and stay ahead of the curve.

In this article, we provide a practical overview of the considerations employers should address as AI becomes more widely adopted.

Act now to build the foundations for safe and effective AI adoption

The inquiry’s questions highlight the issues organisations should already be planning for: how AI will evolve, what infrastructure and governance is needed for safe adoption, how work and workers will be affected, what skills will be required, and how regulation and rights may change.

1. Track how AI is likely to evolve (and build it into business planning)

• Assign ownership and accountability: (for example, by way of a cross-functional AI steering group) to monitor how AI capabilities are developing over the next decade and what that could mean for your products, services and operating model. Upskill members of the steering group to ensure a good understanding of how AI works across functions.
• Map augmentation and automation: AI augmentation is a human-centric approach to AI that focuses on using technology to enhance, support and amplify human capabilities, rather than replacing them. The inquiry explicitly considers both automation and augmentation—so map where AI could support better decisions, faster turnaround, and higher quality.
• Scenario plan: Create best-case, expected and worst-case adoption scenarios and identify triggers for when you would scale, pause or redesign aspects of your AI strategy.
• Supplier due diligence: As models evolve quickly, maintain a clear view of supplier AI adoption and the implications for security, training, and workplace controls by building AI due diligence into procurement activities.

2. Get your adoption foundations right: infrastructure, governance and “safe AI”

• Define “safe, responsible and effective”: Clarify what the use of AI meansto your business and translate this into internal processes, including approved tools, permitted data, human oversight requirements, and clear accountability for decisions influenced by AI.
• Technical guardrails: Put theright infrastructure in placeby considering access controls, identity management, logging or audit trails, secure environments for experimentation, and clear rules for using personal data and confidential information.
• Define an AI governance model:Decide who can approve new AI use cases; how risk is assessed; and how policies are communicated and enforced across the business.
• Change management: AI adoption is not just a technology programme—treat it as a programme of organisational changeto be developed between all relevant stakeholders within the business.

3. Assess the impact on work and workers (before the tech rolls out)

• Analyse work at task level: The inquiry asks which tasks and occupations are most exposed to automation or augmentation. Break roles into tasks (rather than job titles) andidentify where AI might (a) fully automate, (b) partially automate, or (c) augment decision-making. This helps you redesign work realistically and enables informed communication and consultation with the workforce.
• Set accountability: Where AI influences decisions (for example, performance, discipline, selection, pay), ensure human accountability by defining what must be reviewed by a human and what evidence the decision-maker should record.
• Manage productivity expectations: If AI increases productivity, consider how you will manage expectations on output, workload and performance targets—and how job redesign affects grading and pay structures.
• Wellbeing, health, safety and trust: The inquiry highlights health and safety and wellbeing concerns associated with widespread adoption of AI. Consider how to manage work intensification, monitoring or surveillance concerns, and the risks of overreliance on AI outputs (including errors and bias) that could increase stress, affect worker wellbeing, undermine trust or create unsafe decisions.
• Document AI use in recruitment: The inquiry specifically refers to risks associated with AI use in recruitment and HR, and the safeguards needed for fairness and transparency. Practical steps include: documenting where AI is used in the process; testing for unfair outcomes; providing meaningful explanations to candidates and employees where decisions are AI-influenced; and ensuring there is an effective route to challenge decisions.
• Consultation and voice: Consult employees and, where relevant, recognised trade unions or employee representatives to identify risks, manage change and build trust—particularly where AI changes job content, performance assessment or monitoring.

4. Invest in skills and transitions: managers, workers and job redesign

• Core skills for AI-enabled work: The inquiry asks which skills managers and workers need to “work effectively with AI”. Common themes employers should plan for include: AI literacy; critical thinking and verification; data handling; prompt and workflow design; and knowing when to escalate to a human expert.
• Prepare managers: Managers will make day-to-day calls about performance expectations, AI adoption, acceptable use, and how roles are redesigned. Upskill managers to supervise AI-augmented work fairly and consistently.
• Reskilling models: The inquiry asks which reskilling and upskilling models are most effective. Choose reskilling models which suit your workforce, such as blending short, practical learning (for immediate adoption) with deeper pathways for those moving into redesigned roles.
• Consider time required to learn: When introducing AI, map how work will change, update role profiles and capability frameworks, and provide time and support for people to learn new ways of working—rather than expecting adoption “on top of the day job”.

5. Stay ahead of regulation and employment rights (and be ready to evidence your approach)

• Prepare to evidence fairness and transparency: The inquiry is examining whether the existing regulatory framework sufficiently addresses the employment impacts of AI and whether changes are required. Employers should assume increased expectations around transparency, fairness and accountabilityfor tasks carried out by or with the support of AI.
• Document research and changes: Don’t let speedy adoption of AI get ahead of human oversight.Keep a clear record of AI use cases, risk assessments, testing, training, and oversight. If challenged by regulators, tribunals, auditors, employees or candidates, documentation showing consideration and understanding of AI will be the difference between good and fair decision making and an unmanaged risk.
• Refresh relevant policies: Regularly refresh policies on acceptable use of AI tools, confidentiality, data handling, and who can authorise new AI-enabled processes – particularly for recruitment, selection, performance management and other people decisions.

Quick employer action checklist for AI adoption

1. Appoint clear ownership for AI strategy and workforce impacts.
2. Map AI opportunities and risks at task level (both automation and augmentation).
3. Implement governance for “safe, responsible and effective” AI adoption, including controls for data use and human oversight.
4. Audit and safeguard any AI use in recruitment and HR for fairness and transparency.
5. Assess impacts on job quality, health & safety and wellbeing; consult employees and representatives early.
6. Create a skills plan (including manager capability) and fund time for upskilling/reskilling and job redesign.
7. Maintain documentation and monitor legal/regulatory developments affecting employment-related AI issues.

A roadmap for employer AI readiness

AI adoption is moving from experimentation to normal working practice. The themes highlighted by the Business and Trade Committee’s inquiry – the evolution of AI, adoption infrastructure, impacts on work and workers, skills transitions, and the direction of regulation and rights – provide the starting point for a useful roadmap for employer readiness.

Watch our podcast on the benefits of AI in the workplace

Further reading on AI in the workplace

Mitigating the risk of AI in the workplace

AI in Employment Tribunals

The role of AI in workplace safety: hazard identification

Employee brain health in the age of AI

General guidance on HR teams’ use of AI