HR predictions for 2026: Technology, AI and C-suite value
Three shifts will define HR in 2026: smarter employee monitoring that raises real risks, AI moving from experiments to everyday performance, and HR stepping further into the core of business strategy.
The common thread is accountability. Decisions about data, tooling and skills must tie directly to trust, output and commercial results.
Improved monitoring tech will test trust
Productivity tools and "bossware" will get more precise this year. That precision cuts both ways. As Jonathan Lord warned, "Employee-monitoring technologies are risky because they directly affect trust, dignity and power at work. Once employees feel 'monitored' rather than supported, the cultural damage can outweigh any efficiency gains."
There are legal and reputational stakes too. The ICO has cautioned that excessive or covert monitoring is unlikely to meet UK GDPR standards, especially where less intrusive options exist. Lord's advice: slow down, treat monitoring as a governance and culture decision, and build proper safeguards before rollout.
- Start with purpose: define a clear, proportionate business case and the specific decisions data will inform.
- Run a DPIA, test less-intrusive alternatives, and document why monitoring is necessary at all.
- Consult employees or unions early; co-design policies, notices and feedback loops.
- Be transparent: what's collected, when, how it's used, who sees it, and retention rules.
- Embed guardrails: role-based access, audit logs, bias checks, and strict vendor terms.
- Train managers to support performance, not micromanage. Review metrics quarterly and kill what doesn't help.
Useful reference: ICO guidance on worker monitoring and UK GDPR expectations can help shape your approach. Read the ICO guidance.
2026 is the year of applied AI
Last year was about learning tools. This year is about using them daily. As Miika Mäkitalo put it, "Employees who build AI into their everyday workflows will work faster, make better decisions and deliver higher-quality outcomes; those who fail to embrace it at scale will fall behind."
One-off training won't cut it. "Organisations need ongoing, role-specific development, clearer expectations around how AI should be used, and managers who are confident coaching teams on effective use… Those that fail to build AI fluency at scale will struggle to compete on speed and quality."
- Define role-by-role AI use cases, quality bars and red lines. Turn them into simple playbooks.
- Shift to practice-first learning: short sprints, real tasks, peer reviews, and weekly prompts.
- Coach managers to set standards, review outputs and measure impact on time, quality and cost.
- Track ROI: tasks automated, cycle times cut, error rates lowered, customer/employee outcomes improved.
- Govern usage: data classification, privacy, bias checks, and vendor risk management.
- Create internal "AI champs" to support teams and keep examples current.
If you need ready-to-go curricula and role-based paths, explore these resources: AI courses by job.
HR's value to the C-suite will accelerate
Expect sharper questions from executives: how is HR driving revenue, productivity and margin? Elizabeth Wallace summed it up well: "A business-centric HR function shapes people strategies around the commercial objectives of the organisation, rather than alongside them."
Data is the bridge. Link people metrics to sales performance, delivery speed and customer outcomes. That's how HR earns bigger bets and influences growth.
- Tie hiring, mobility and skills to priority revenue lines and product roadmaps.
- Build a skills graph and redeploy talent faster than you hire. Measure time-to-productivity, not just time-to-hire.
- Run quarterly People x Business Reviews with clear KPIs and actions.
- Forecast headcount, skills gaps and cost scenarios for different demand curves.
- Prove ROI: show which programs move revenue per FTE, quality, retention of critical roles, and customer NPS.
- Upskill HRBPs in finance, data storytelling and AI so they can challenge and advise peers credibly.
What to do this quarter
- Monitoring: pause any new tool until a DPIA, consultation and transparency plan are complete.
- AI: publish role-level playbooks, run one hands-on sprint per team, and set three usage KPIs.
- C-suite: select five metrics that link people to commercial results and review them monthly.
Keep it simple, prove impact quickly, and scale what works. That's how HR leads in 2026.
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