Blog 10 - The Future of HR: Human + AI, Not Human vs AI

The Future of HR: Human + AI, Not Human vs AI

Across this blog series, Artificial Intelligence (AI) has repeatedly appeared in discussions about recruitment, job design, skills, employee engagement, performance, diversity, organisational culture, ethics and privacy. One conclusion now seems increasingly clear: the future of work cannot be understood through a simple competition between humans and machines.

AI can automate tasks, analyse enormous quantities of information and support decisions at a speed that human employees cannot match. Human beings, however, continue to contribute contextual judgement, empathy, leadership, ethical reasoning, creativity, relationships and responsibility.

The strategic HR challenge is therefore not to choose between humans and AI. It is to design organisations in which human capability and technological capability strengthen one another.

AI Is Transforming Jobs More Often Than Simply Eliminating Them

The International Labour Organization’s refined global index of generative-AI exposure estimates that approximately one in four workers worldwide are employed in occupations with some degree of exposure to generative AI. However, the ILO emphasises that transformation rather than complete replacement is the most likely outcome for most exposed occupations because human input remains necessary (Gmyrek et al., 2025).

This distinction matters enormously for HRM. If AI simply removed whole jobs, the HR challenge would mainly concern redundancy and replacement. If jobs are instead being transformed task by task, HR must manage a much broader process involving job redesign, reskilling, employee engagement, workforce planning and change management.

The World Economic Forum (2025) similarly expects substantial labour-market movement rather than a one-directional collapse in employment. Its Future of Jobs Report 2025 projects 170 million new roles and 92 million displaced roles by 2030 across major technological, economic, demographic and environmental changes, producing a net gain of 78 million jobs.

This does not mean disruption will be painless. Forty-one per cent of employers surveyed by the World Economic Forum expected to reduce workforce numbers where AI automates tasks. At the same time, 77% planned to upskill employees and almost half expected to move workers from AI-exposed roles into other parts of their organisations.

The future of work is therefore likely to involve several processes at once:

Automation of some tasks + augmentation of others + new roles + redesigned roles + reskilling + redeployment.

The Future HR Challenge Is Not Simply Learning to Use AI

It would be easy to conclude that HR professionals simply need more technical training. Recent CIPD evidence suggests a more interesting problem.

In a 2026 survey of more than 1,300 senior leaders and HR professionals, the CIPD found that many people professionals were relatively confident in learning AI tools and understanding their limitations. Among HR practitioners, 67% were confident in learning how to use AI tools and 64% in understanding their limitations.

Confidence fell significantly when the challenge moved from using AI to redesigning the organisation around AI. Among HR leaders, only around one third felt confident estimating future workforce needs created by AI; 40% were confident designing reskilling pathways, and 46% were confident leading job redesign (CIPD, 2026).

Figure 1. Selected HR capability confidence levels in the AI transition. Author’s illustration based on CIPD (2026).

This finding changes how the future HR role should be understood. HR’s greatest value may not come from becoming the organisation’s technical AI expert. It may come from applying established people-management expertise—workforce planning, job design, employee relations, skills development and change management—to a faster and more uncertain technological environment.

The CIPD identifies three priorities: move from static to dynamic workforce planning, strengthen job and work-design capability, and work more closely across functions because many AI decisions originate outside HR even though their workforce consequences affect the whole organisation.

The future HR professional does not need to become a software engineer. HR needs enough technological understanding to ask the right people questions before, during and after AI adoption.

Most Employees Will Need AI Literacy, Not AI Engineering

The same principle applies to the wider workforce.

The OECD (2026) reports that fewer than 1% of workers are likely to require advanced AI-specific skills such as programming or model development. Most workers instead need digital capability and the ability to use, analyse and interpret data. At the same time, management skills and human skills—including problem-solving, creativity and innovation—remain important.

Figure 2. The changing workforce skill mix in the AI era. Author’s illustration based on OECD (2026).

This is important because public discussion often creates the impression that every future employee must become a coder. The evidence points instead towards a hybrid capability model.

Employees need enough technological literacy to work effectively with AI, but they also need capabilities that help them question, interpret and apply AI output. An employee who can generate an answer quickly but cannot judge whether that answer is appropriate may not create value for the organisation.

This also explains why human skills remain important. The World Economic Forum (2025) expects technology skills such as AI, big data and cybersecurity to grow rapidly, while human capabilities including analytical thinking, resilience, leadership and collaboration remain critical.

From Human Resources to Human Capability

The traditional term “Human Resources” can sometimes encourage an administrative view of people: employees are resources that must be acquired, allocated, measured and controlled.

Strategic HRM offers a broader perspective. Boxall, Purcell and Wright (2008) place HRM within the creation of organisational capability and performance. Purcell and Boxall (2022) similarly emphasise the connection between strategy and the way organisations manage their people.

In an AI-enabled organisation, this strategic perspective becomes even more important. If technology can perform more routine activity, the organisation needs to decide where human contribution creates the greatest value.

Human capability may increasingly concentrate in areas such as:

• complex judgement where information is incomplete;
• leadership and relationship building;
• creative problem-solving;
• ethical decisions;
• cross-cultural understanding;
• negotiation and conflict resolution;
• coaching, mentoring and employee support;
• responsibility for decisions that affect people.

The Future HR Function Will Need to Govern the Relationship Between Humans and AI

Throughout this blog series, one issue has appeared repeatedly: technology itself does not determine whether the outcome is good or bad.

AI in recruitment can improve efficiency or reproduce discrimination. AI in performance management can provide useful feedback or become intrusive surveillance. AI in learning can accelerate development or create dependency. AI in job design can reduce repetitive tasks or simply intensify workload.

The CIPD (2026) argues that people professionals can contribute to AI governance, skills planning and workforce planning wherever transformation has a people impact. This is significant because AI decisions are often led by IT, operations or senior leadership, while their consequences appear in employees’ jobs, careers and working conditions.

Figure 3. A Human + AI operating model for the future HR function. Author’s synthesis informed by CIPD, OECD, ILO and World Economic Forum evidence.

The future HR function can therefore act as a bridge between technological possibility and organisational responsibility.

AI asks: “What can be automated?”

Strategic HR should additionally ask: “What should be automated, what should remain human, what skills will change, and what will the employee experience become?”

Productivity Is Not the Only Measure of Successful AI

Business leaders naturally care about productivity. If AI allows employees to complete work faster, that can create significant organisational value. However, HR should ensure that productivity does not become the only measure of success.

The CIPD’s Good Work Index 2025 found that employees generally welcomed using AI to complete repetitive tasks and often associated it with better performance, job satisfaction and mental health. The CIPD therefore recommends focusing AI on repetitive activities so that employees can spend more time on higher-value or more enjoyable work.

This is an important principle because an efficiency gain can be used in different ways. If AI saves an employee five hours each week, management can use all five hours to increase targets. Alternatively, some of that capacity can support learning, better customer service, innovation or reduced administrative burden.

The question is not only whether AI makes people faster. It is whether AI helps create better work and stronger organisational capability.

Dynamic Workforce Planning Will Replace Static Headcount Planning

Traditional workforce planning often begins with headcount: how many employees will the organisation require next year?

AI makes that question less sufficient because the number of employees may remain stable while the content of their jobs changes substantially. The CIPD (2026) therefore recommends moving towards dynamic workforce planning based on changing tasks and skills rather than headcount alone.

For example, an organisation may not need fewer HR professionals overall, but it may need fewer hours devoted to routine reporting and more capability in workforce analytics, change management, employee relations and AI governance.

This creates a more sophisticated strategic planning process:

Step 1: Identify which business processes are changing.
Step 2: Identify which tasks AI can automate or augment.
Step 3: Redesign jobs around the remaining and emerging tasks.
Step 4: Identify future capability gaps.
Step 5: Decide whether to reskill, redeploy, recruit or restructure.
Step 6: Monitor employee experience and organisational outcomes.

The Future HR Professional Must Work Across Functions

AI also weakens traditional departmental boundaries. A decision made by an IT team about an AI platform may affect recruitment, employee monitoring, performance, training and data privacy simultaneously.

The CIPD (2026) therefore argues that HR should work more closely across functions and become involved earlier in AI decisions. This requires people professionals to communicate effectively with technology teams, operations, legal specialists, finance and senior leadership.

The future HR professional will therefore need enough technological literacy to participate confidently in these discussions while maintaining the people-management perspective that other functions may not naturally prioritise.

A Global HRM Perspective

The Human + AI model becomes more complicated in multinational organisations. Brewster et al. (2017) emphasise that International HRM operates across different cultures, labour markets, institutional systems and legal frameworks.

AI exposure also differs across economies. The ILO (2025) shows that occupational exposure to generative AI is generally higher in high-income economies because of differences in occupational structure. Lower-income economies may currently face less immediate exposure but may also have weaker access to digital infrastructure, training and productivity-enhancing technologies.

This creates an important global HR question: how can multinational organisations ensure that the benefits of AI are shared across locations rather than concentrated only among employees who already have the strongest technology access and skills?

Global HR should therefore consider equitable access to training, local language and cultural differences, employee voice, local regulation and the possibility that the same technology may create different effects in different labour markets.

What Should Always Remain Human?

Perhaps the most important question for the future of HR is not what AI will eventually be capable of doing, but what organisations should continue to keep under meaningful human responsibility.

In my view, decisions involving significant consequences for a person’s livelihood, dignity or career should maintain human accountability. AI may provide evidence, identify patterns and suggest options, but a person should remain responsible for important employment decisions.

Human responsibility is particularly important for:

• final hiring and rejection decisions;
• disciplinary and termination decisions;
• sensitive employee-relations issues;
• ethical judgements;
• employee wellbeing and support;
• conflict resolution;
• leadership and culture building.

This does not reject technology. It recognises that responsibility should remain visible when decisions have serious human consequences.

🎥 Recommended Video

CIPD HR People Pod – Agentic AI, Entry-Level Careers and the Future of the People Profession

This CIPD discussion considers how agentic AI is changing work, careers and the responsibilities of people professionals, making it a suitable final resource for this blog series.

▶ Watch on YouTube

My Final Reflection

When I began this blog series, I largely viewed AI as a new HR technology. After examining recruitment, jobs, learning, engagement, performance, diversity, organisational culture and privacy, my perspective has become broader.

AI is not simply another tool that HR must learn to use. It changes the content of work, the skills employees require, the information managers can access and the balance of power between people and organisations.

I have also learned that the most important AI questions are often not technical questions. They are questions about people:

• Will employees be trained or displaced?
• Will technology increase autonomy or surveillance?
• Will AI reduce bias or reproduce historical inequality?
• Will productivity gains improve work or simply increase targets?
• Will employees have a voice in how their jobs change?
• Who remains accountable when an AI-supported decision is wrong?

These are exactly the kinds of questions HR professionals are positioned to address.

My final conclusion is therefore that AI may reduce the value of some traditional administrative HR activities while increasing the importance of strategic HRM. Workforce planning, job design, employee voice, learning, culture, ethics and change management become more—not less—important when technology develops quickly.

The future of HR is not Human vs AI.

It is Human + AI—guided by responsible Human Resource Management.

💬 Final Discussion

After considering the opportunities and risks of AI, what responsibility in Human Resource Management do you believe should always remain human?

Do you believe the future workplace will be better because of AI, or will the outcome depend mainly on how organisations choose to manage it? Share your final perspective in the comments.

References

Boxall, P., Purcell, J. and Wright, P. (eds.) (2008) The Oxford Handbook of Human Resource Management. Oxford: Oxford University Press.

Brewster, C., Sparrow, P., Vernon, G. and Houldsworth, E. (2017) International Human Resource Management. 4th edn. London: CIPD.

CIPD (2026) AI and technology. Available at: https://www.cipd.org/uk/knowledge/factsheets/ai-technology/ (Accessed: 12 August 2026).

CIPD (2026) Futureproofing your skills: AI is changing how HR skills are applied. 29 April. Available at: https://www.cipd.org/en/views-and-insights/thought-leadership/insight/futureproofing-skills-ai/ (Accessed: 12 August 2026).

Gmyrek, P., Berg, J., Kamiński, K., Konopczyński, F., Ładna, A., Nafradi, B., Rosłaniec, K. and Troszyński, M. (2025) Generative AI and Jobs: A Refined Global Index of Occupational Exposure. ILO Working Paper 140. Geneva: International Labour Organization. Available at: https://www.ilo.org/publications/generative-ai-and-jobs-refined-global-index-occupational-exposure (Accessed: 12 August 2026).

OECD (2026) AI and skills: What we know so far. Paris: OECD Publishing. Available at: https://www.oecd.org/en/publications/ai-and-skills_f843b352-en.html (Accessed: 12 August 2026).

Purcell, J. and Boxall, P. (2022) Strategy and Human Resource Management. London: Palgrave.

World Economic Forum (2025) The Future of Jobs Report 2025. Geneva: World Economic Forum. Available at: https://www.weforum.org/publications/the-future-of-jobs-report-2025/ (Accessed: 12 August 2026).