Why is the future of work an HR priority now?

For years, "the future of work" was a conference theme. It is now an operational reality. Generative AI and AI agents are embedded in the software employees use every day. Employers report both enthusiasm and anxiety: adoption is rising quickly, yet confidence that AI is being used well is far from universal, as our analysis of HR's confidence in AI shows. Some organisations that cut roles in anticipation of AI have had to rehire, a pattern explored in the AI layoff reversal.

At the same time, the debate over where work happens continues. Return-to-office mandates have tightened in some sectors while hybrid remains the norm in many others, and experiments with shorter working weeks are gaining attention. Regulation is catching up too: AI used in hiring and people management is increasingly treated as high-risk. For HR, the challenge is to make sense of these shifts and translate them into practical policies, skills programmes and ways of working.

None of this means HR must have every answer. The organisations adapting best treat the future of work as a series of experiments: they pilot new tools and ways of working in a few teams, measure results honestly, involve employees in redesigning their own work and scale what works. HR's distinctive contribution is to keep people outcomes — fairness, wellbeing, growth and trust — at the centre of those experiments.

This hub combines timely analysis of developments with evergreen guides. It is organised into five tracks, from AI agents in HR to remote and hybrid work.

What are the biggest shifts in how we work?

Across industries and countries, six shifts stand out. Each changes what HR needs to do.

How should HR think about AI and jobs?

The most useful lens is tasks, not jobs. Most roles are bundles of tasks; AI automates some, augments others and leaves many untouched. Mapping tasks role by role shows where productivity gains are likely, where skills need to change and where new roles may emerge — for example people who design, supervise and evaluate AI-assisted workflows.

Workforce decisions based on hype are risky. Cutting roles before AI can reliably do the work damages service and morale, and rehiring is expensive. A better approach combines pilots that measure real productivity, transparent communication with employees, reskilling pathways and careful attention to groups who may be affected disproportionately, such as older workers — see our analysis of AI and older workers. Our guide to strategic workforce planning provides the planning framework.

What makes a good hybrid work policy?

A good hybrid policy explains why the organisation brings people together, not just how many days they must attend. It defines expectations by team or role, sets core collaboration times, clarifies eligibility and exceptions, covers equipment, expenses and security for home working, explains how performance is assessed fairly regardless of location and is reviewed regularly against evidence.

Mandates without purpose tend to produce resentment and attrition, particularly among high performers with options elsewhere. Policies built around specific in-person activities — onboarding, team planning, mentoring, client work — and applied consistently tend to work better. Our guides to remote work policies and culture, managing hybrid teams, remote work stipends and monitoring laws cover the details, and our analyses of stricter RTO mandates track the debate.