11 HR Trends for 2026: Shaping What’s Next

HR is entering one of its most defining moments yet. AI has already begun to reshape how organizations make decisions, design work, and deliver value. At the same time, uncertainty rises, skills gaps are growing, and the pressure for speed and adaptability is increasing. HR has a unique opportunity to lead organizational transformation by rethinking how it operates, building new capabilities, and helping the business stay aligned, resilient, and people-centered through change.

In 2026, the most effective HR professionals will be those who act as architects of adaptability, trust, and innovation. We explore 11 trends that will shape the future of the HR function, what they mean for you as an HR professional, and the practical steps you can take to position yourself as a leader in this new era of work.

Based on these trends, we’ve identified five strategic priorities for HR leaders in 2026. These are clear focus areas that will help translate market shifts into action. You can download the full report below.

1. AI leadership coalition emerges with HR at the table

AI has moved out of the IT department and into the boardroom. As disruption cuts across industries and functions, leadership teams are recognizing that AI is not simply a question of system integration but of business transformation. It has become a front-and-center business priority that is redefining how organizations set strategy, make decisions, and measure and deliver value.

AI’s rising importance is reflected in new leadership appointments: 48% of FTSE 100 companies now have a Chief AI Officer, and on average, organizations designate two senior leaders to manage AI. But titles alone don’t guarantee progress on the AI front. The real shift happens when senior leaders—CEOs, CAIOs, CHROs, CFOs, COOs, and CTOs—work together to embed AI into business strategy, decision-making, and culture. When that kind of cross-functional alignment happens, organizations are more likely to move beyond pilots and turn AI into a lasting transformation.

In this coalition, HR cannot be a passive bystander, as the impact of AI transformation is deeply human. 92% of HR leaders already report at least some level of participation in AI implementation. However, only 21% are closely involved in AI strategy decisions. This gap shows that many HR functions still lack the influence, mandate, or capabilities to claim a seat at the table. To shift that, HR needs to proactively build credibility, develop relevant skills, and position itself as a strategic partner in AI transformation. The earlier HR engages, the better it can shape how AI impacts jobs, skills, and trust across the workforce.

Organizations that bring HR into AI strategy from the outset are more likely to balance speed with sustainability, translating tech-driven change into measurable outcomes without compromising culture.

→ The bottom line: The era of HR “supporting” technology initiatives is over. HR is now expected to co-strategize AI transformation, safeguarding the people side of change and making sure decisions translate into real-world adoption and impact.

HR actions to take

• Contribute to strategic planning: Bring workforce data, skill forecasts, ethical considerations, and trust-building expertise into AI decision-making forums.
• Build alliances with the C-suite: Partner with the CAIO, CFO, and CTO to align AI deployment with workforce readiness, culture, and business outcomes.
• Translate tech into people impact: Use clear language to show how AI affects roles, skills, and culture, ensuring leadership decisions stay grounded in reality.

2. Human-centered governance guides AI deployment

As AI becomes deeply embedded in hiring, learning, and performance management, new risks are emerging—not only from the technology itself, but also from how people use it. Poorly designed prompts, blind trust in outputs, and biased data can quietly shape real-world outcomes, influencing who gets interviewed, how performance is assessed, or what information employees rely on to make decisions. This makes governance both a technical and a workforce issue requiring safeguards for systems as well as responsible practices in daily use.

Already, 78% of organizations are deploying AI in at least one function. As adoption grows, so does concern: According to McKinsey, more than half of U.S. workers cite cybersecurity, inaccuracy, or personal privacy as top concerns about generative AI. A third of employees also worry about explainability, equity, and fairness. These concerns are grounded in everyday experience: an inaccurate AI-generated document sent to a client, a tool recommending biased hiring decisions, or unclear AI explanations in feedback systems.

While IT and Legal provide technical and regulatory safeguards, HR plays a distinct role: translating those safeguards into everyday practices that employees understand and trust. By partnering across functions, HR ensures governance is not only compliant but also human-centered and credible for the workforce. This includes reviewing recruitment algorithms for bias, stress-testing performance tools for fairness, and identifying where AI might unintentionally drive burnout or erode wellbeing. These efforts help make responsible AI use part of the lived employee experience.

→ The bottom line: The biggest risks of AI aren’t technical—they’re human. Without guardrails, AI can quietly undermine fairness, accuracy, and wellbeing in day-to-day decisions. HR needs to guide human-centric governance by embedding responsible use into everyday tools, processes, and behaviors.

HR actions to take

• Audit key workflows: Review how AI is used in hiring, learning, and performance to flag bias, misapplication, or exclusion risks.
• Set ethical guardrails: Partner with IT and Legal to design standards for bias-prevention, explainability, and human oversight.
• Educate the workforce: Provide plain-language training and forums so employees understand how AI is used and what safeguards are in place, building trust through clarity.

3. Businesses invest in AI Centers of Excellence

Even though 98% of organizations are accelerating AI integration, very few feel truly ready to scale it in a way that delivers real value. Projects often stall after the pilot stage, ethical risks go unmanaged, and employees feel alienated or unsure about what AI means for their roles. Without a clear structure, organizations struggle to move from ambition to impact.

This is where AI Centers of Excellence (CoEs) are starting to make a difference. These well-resourced, cross-functional teams align technology, talent, and trust. CoEs coordinate efforts across departments, define success metrics, manage risks, and create the governance needed to implement AI in a way that is both scalable and sustainable. For example, Siemens’ AI Lab acts as a Center of Excellence by bringing together experts to develop, test, and scale AI-driven solutions that accelerate innovation across industrial use cases.

Beyond IT and business experts, leading organizations increasingly bring HR into these CoEs, not just to manage change, but to shape it. Data shows that companies ahead in AI adoption are 2.5 times more likely to involve HR in helping employees identify tasks suited for automation, which helps accelerate adoption and reduce resistance. HR contributes insight into job design, role transitions, reskilling needs, and ethical implementation, all of which are critical to sustaining transformation.

Organizations with strong AI CoEs and active HR involvement are more likely to scale innovation, strengthen culture, and deliver measurable business outcomes. They move faster because they align strategy and workforce impact from the start, and avoid the pitfalls of fragmented, tech-led transformation.

→ The bottom line: AI CoEs are becoming the defining feature of successful AI adoption. Organizations that invest in them—and include HR as a core partner—are the ones turning ambition into measurable outcomes: faster adoption, stronger culture, and more resilient teams.

HR actions to take

• Claim your seat: Join or advocate for HR representation in AI CoEs to ensure workforce needs are central to adoption.
• Map workforce impact: Use the CoE AI implementation planning to proactively analyze which skills and roles will change, and lead tailored reskilling efforts.
• Champion trust: Drive communication strategies from within the CoE to build transparency, ethical guardrails, and employee confidence.

4. AI capacity gains fuel collective growth

AI is transforming work not only by how much time it saves, but by changing the very nature of what people spend their time on. While automation has long been positioned as a cost-cutting lever, organizations are now recognizing that the real value of AI lies in how it enables humans to redirect effort toward higher-value activities. Even when time savings are modest, particularly in technical or specialist roles, the ability to shift away from repetitive tasks creates space for problem-solving, collaboration, and innovation.

Research shows AI can free up more than 120 hours per employee per year. If reinvested wisely, this reclaimed capacity becomes a growth engine, fueling skills development and new career pathways. Some organizations are already taking this approach: a leading Belgian telecom provider reinvested time savings into reskilling, giving employees the space and support to transition into new roles.

Leading companies are going even further. More than 80% of their AI investments have gone toward redesigning core functions and launching new offerings, not just cutting costs. This signals a shift in mindset: AI capacity is now a lever for reinvention.

But when saved time is not deliberately redirected, teams risk becoming overburdened with new tasks, losing focus, or even needing to rehire for roles that were downsized too soon. A fintech company, Klarna, laid off around 700 customer service employees with the expectation that AI agents could fully replace them. However, leadership later acknowledged that relying on AI alone “was not the right fit.” The company ended up rehiring human staff to restore the balance.

With 39% of current skills expected to be disrupted in five years, how organizations reinvest this time will directly shape workforce adaptability, competitiveness, and long-term success.

→ The bottom line: AI is best understood as a “thinking partner” or “extra set of hands,” amplifying, not replacing, human capability. But time savings alone don’t drive progress. HR’s role is to turn freed-up capacity into a strategic asset by guiding how it’s reinvested. That means using it to unlock learning, fuel innovation, and support long-term workforce resilience.

HR actions to take

• Track and redirect time savings: Identify where AI reduces admin tasks and work with business leaders to reallocate saved time toward strategic initiatives like innovation, transformation, or customer experience, so the gains directly support core business goals.
• Design new pathways for employees: Build reskilling pilots and transparent career alternatives for roles disrupted by automation.
• Help managers turn time savings into progress: Enable managers with checklists or discussion guides to turn capacity gains into specific initiatives, such as cross-training, continuous workflow improvement, or new team-driven experiments.

5. Technostress and FOBO enter the HR agenda

The same forces that create opportunity are also fueling anxiety. While some organizations use AI to drive innovation and reskilling, others focus narrowly on efficiency and cost-cutting. Employees are caught in between: excited by the potential, but also feeling the pressure of technostress and FOBO (fear of becoming obsolete) as digital change accelerates. These concerns are already affecting how employees show up at work.

According to Pew Research, 52% of workers are worried about AI’s future impact in the workplace, and one in three believe it will reduce job opportunities for them. These fears are grounded in what’s already happening: the World Economic Forum reports that 41% of employers plan to reduce headcount in the next five years due to AI.

Yet, 75% of employees report that they don’t feel confident using AI in their day-to-day work. The result is rising uncertainty, falling engagement, and hidden resistance to transformation. Left unsupported, employees may withdraw, lose motivation, or struggle to see a future for themselves in their organization. FOBO in particular undermines confidence, as workers question their relevance and career prospects in a world where machines perform more of their tasks.

HR cannot afford to treat these issues as “soft” concerns. If organizations don’t address these concerns now, they risk stalled adoption, growing resistance, and talent loss at a time when adaptability matters most. HR’s role is to acknowledge these fears, make space for honest conversations, design interventions to reduce technostress, and turn anxiety into agency through clarity, coaching, and continuous learning.

→ The bottom line: AI will only succeed if employees feel supported and secure. Tackling FOBO and technostress is now central to sustaining long-term workforce health.

HR actions to take

• Build confidence with AI through hands-on learning: Give employees a safe space to explore and experiment with AI tools. Combine this with training, feedback, and peer support.
• Monitor new risks: Add technostress and FOBO indicators to pulse surveys and track alongside productivity and engagement.
• Make reskilling paths visible and achievable: Provide clear communication on reskilling, career alternatives, and opportunities for growth as AI reshapes roles.

The trends highlight what’s shifting. But what should HR leaders actually do next? We’ve outlined five strategic priorities for 2026 based on these market signals.

6. Cross-functional structures replace HR silos

Traditional HR structures, organized around silos like recruitment, learning, rewards, and performance, are becoming increasingly outdated in an AI-powered work environment. In fact, 89% of HR functions have already restructured or plan to do so in the next two years, signaling a widespread push to modernize.

AI capabilities in platforms like Workday, SAP Joule, and Microsoft Copilot are accelerating this shift by connecting data and workflows across the entire employee life cycle. As these tools automate handoffs and surface insights across different HR domains, they naturally blur functional boundaries and raise the bar for integration and collaboration.

Leading organizations are shifting away from traditional HR Centers of Excellence, such as dedicated teams for Talent Acquisition, Learning & Development, Total Rewards, or Performance Management, that often operate in isolation. Instead, they’re forming agile, cross-functional teams where HR professionals from different specialties work on shared business challenges.

These multidisciplinary pods focus on priority areas like onboarding redesign, retention improvement, or leadership pipeline development. Rather than handing off work between siloed functions, they integrate their efforts using shared platforms, data, and feedback loops. The result is faster decisions, more cohesive employee experiences, and stronger alignment with business outcomes.

The shift is as much cultural as it is structural. It requires HR professionals to let go of function-first mindsets and adopt outcome-focused approaches, supported by data literacy and systems thinking. When HR reorganizes into flexible, cross-functional capability networks, it becomes a driver of speed, innovation, and relevance.

These evolving structures also better position HR to use AI in meaningful ways, whether by co-piloting new tools or applying insights to shape the broad HR strategy and holistic employee experience. There’s momentum building, but more is needed: while 42% of marketing teams already use AI, only 13% of HR teams do.

→ The bottom line: Fluid HR structures are now the foundation of adaptability. In companies embracing AI at scale, this approach helps HR deliver business value faster, with greater alignment to real-time talent and transformation needs.

HR actions to take

• Join or form agile squads: Work alongside colleagues in talent, learning, analytics, and IT on outcome-focused challenges like onboarding, skills development, or retention.
• Build on your data literacy: Strengthen your ability to interpret cross-functional data and translate those insights into workforce strategy based on business goals.
• Redefine your role: Position yourself not as a siloed expert but as a strategic partner blending HR expertise with consulting and design thinking.

7. HR’s AI spending is accelerating

AI-enabled HR technology is fast becoming the backbone of how organizations plan, decide, and deliver value. HR tech budgets are on the rise—55% of companies are increasing their HR technology spend, and by 2030, the AI HR technology market size is expected to triple. AI-powered HR platforms now underpin everything from recruitment and onboarding to performance, learning, and workforce planning. But as investment grows, so does the pressure to deliver business impact.

Adoption and impact, however, are still uneven. While 49% of HR teams use AI in recruitment, fewer than 15% apply it to other areas like performance management, development, or onboarding. The returns also vary widely—top performers report an ROI of 55% or more, while others lag far behind, with returns as low as 5%.

The reality is that technology spend alone does not equal impact. As AI budgets increase, HR teams need the capabilities and decision-making frameworks to use these tools effectively. That includes aligning investments to real workforce needs, building the skills to integrate AI into daily work, and creating structures that support adoption across functions. Organizations that take a strategic, prepared approach will be better positioned to turn their investment into measurable impact.

→ The bottom line: As AI investment accelerates, HR teams need strong skills, adoption structures, and sharp decision-making about where AI can deliver the greatest value. Readiness in these areas will determine whether investments lead to real impact.

HR actions to take

• Prioritize high-impact use cases: Work with stakeholders to identify where AI can solve real problems, such as streamlining onboarding, improving internal mobility, or reducing bias in performance reviews.
• Pressure-test vendor claims: Ask for real benchmarks, validate AI capabilities through pilots, and involve end-users before committing to full implementation.
• Track adoption and outcomes early: Set clear goals for each HR tech rollout (e.g., time savings, quality improvements, experience metrics) and monitor usage patterns to guide improvements.

8. AI fluency becomes a baseline HR competency

AI is no longer a specialized domain reserved for tech specialists. As organizations adopt AI across functions, HR professionals are expected to speak the language too, whether it’s prompting generative AI tools, interpreting algorithmic recommendations, or making ethical decisions about automation. This shift is already showing up in the job market. While only 2% of HR job postings currently list AI skills as a requirement, demand is growing faster than any other hotspot sector, with a 66% increase year over year.

That means early movers will stand out, both on an individual and organizational level. For individual HR professionals, building AI fluency—understanding how to use, question, and apply AI tools in everyday HR work—early offers a real career advantage in a market where demand is accelerating. Yet today, only 35% of HR professionals say they feel equipped to use AI technologies. At the same time, HR teams that invest in building fluency now will be better positioned to lead AI adoption across the business, rather than being sidelined by more tech-literate functions.

The path to AI fluency is also changing. Long formal courses are giving way to hands-on, continuous learning. Self-exploration is the most common approach at the moment: 38% of HR practitioners are building AI skills by experimenting with tools, trialing features, testing prompts, and learning by doing. These low-stakes environments help teams build confidence and share lessons with peers. Such an iterative approach mirrors how AI itself evolves: through experimentation, feedback, and refinement.

→ The bottom line: In an AI-enabled world, the ability to understand and responsibly apply AI has become table stakes for HR’s relevance and impact.

HR actions to take

• Experiment in safe spaces: Use sandbox tools or pilots to practice prompting and interpreting AI outputs.
• Share peer learning: Build internal forums or communities of practice where teams exchange insights and tips.
• Apply responsibly: Balance experimentation with ethical guardrails, ensuring transparency, bias prevention, and human oversight.

9. Human strengths will define HR’s future impact

As AI takes on more technical and transactional work, the distinct value HR brings is increasingly rooted in human capabilities. Empathy, ethical judgment, communication, and culture-building are emerging as critical differentiators in workplaces where machines handle much of the routine. These human skills are not “nice to have” soft attributes, but are becoming essential to guiding organizations through change, maintaining trust, and sustaining culture in an era of rapid automation.

This shift is already visible in the broader talent market. Nearly three in five employers say soft skills are more important today than they were five years ago, and demand for social and emotional skills is expected to grow 26% by 2030. Within HR, this means capabilities like coaching, influencing, and emotional intelligence are moving from the sidelines to the core of what the function must deliver.

These skills are especially important in moments of uncertainty, where HR is called on to guide leaders, support employees, and hold space for complex conversations about change. And while digital and analytical skills are rising in demand, emotional intelligence, adaptability, and influence are now just as important for HR professionals who want to remain credible, trusted, and effective.

As businesses change, HR will increasingly be expected to put human skills into daily practice and model them for the broader organization. To credibly guide transformation, HR professionals must invest in their own development, actively building skills like empathy, coaching, trust-building, and ethical judgment. These should be visible in everyday interactions with employees and leadership, not just outlined in strategy documents.

→ The bottom line: The more technology shapes the workplace, the more human skills define HR’s value. For HR to stay influential and impactful, doubling down on emotional intelligence, ethical judgment, and communication is becoming just as important as learning to use AI tools.

HR actions to take

• Continuously develop your human capabilities: Treat skills like active listening, coaching, and cultural awareness as core—not nice-to-haves.
• Lead by example: Demonstrate emotional intelligence, ethical judgment, and adaptability in daily HR work, especially during moments of change or ambiguity.
• Integrate human touchpoints: In HR programs, from onboarding to performance, purposefully embed space for reflection, discussion, and connection.

10. Workforce planning expands beyond jobs and roles

The way organizations approach workforce planning is undergoing a fundamental shift. Traditional job-based models, which focused on headcount, titles, and cost, are giving way to more flexible, skills-first approaches. Instead of simply filling roles, leaders are asking what capabilities are needed for specific initiatives and how they can be assembled across employees, gig workers, partners, and even AI agents to deliver on evolving business priorities.

This move toward skill-based planning is already showing measurable impact. Research indicates that skill-based organizations are 57% more likely to anticipate and respond effectively to change. For example, three-quarters of Mastercard’s workforce is now registered on its internal talent marketplace, helping the company unlock 100,000 hours of capacity and $21 million in savings through internal mobility alone.

By organizing work around skills instead of rigid roles, leading companies are increasing agility, accelerating innovation, and providing employees with new pathways for growth that go beyond traditional hierarchies. For HR, this shift calls for new ways of thinking and operating—moving beyond static job descriptions and embracing tools like dynamic skills taxonomies, AI-powered talent marketplaces, and performance models that reflect contributions across projects, not just roles.

→ The bottom line: The future of workforce planning is less about filling roles and more about assembling the right skills and capabilities—across people and technology—to meet evolving business needs with speed and precision.

HR actions to take

• Map skills dynamically: Use AI-enabled platforms to identify current skills, adjacencies, and gaps across all talent sources, from employees to contractors and AI systems.
• Launch skills-based pilots: Form teams based on capabilities, not job titles, to test new ways of working.
• Enable internal mobility: Build clear, skills-focused pathways that let employees shift roles and take on new challenges as they grow.

11. Leadership expands as management shrinks

Organizations have been steadily streamlining structures to boost efficiency and reduce layers, part of a broader shift often referred to as The Great Flattening. The effects of this shift are becoming increasingly visible. As AI systems take over tasks like coordination, tracking, and scheduling, middle management layers are being re-evaluated or removed entirely. For instance, Google has reduced its population of small-team managers by more than a third, citing efficiency gains. More broadly, the number of managers globally has dropped by over 6% in the past three years, with executive roles also in decline.

The combination of cost pressure and AI maturity is changing how organizations define management and distribute leadership. But while the administrative side of management is shrinking, the human side of leadership is becoming more essential than ever. Organizations are moving toward informal, distributed, and situational leadership, where responsibility for guiding teams is shared across levels and contexts. The impact of informal leadership is already observable in practice: a study comparing formal and informal leaders across 161 variables found that informal leaders consistently scored higher on shared vision, communication, relationships, and character.

→ The bottom line: AI and the push for efficiency may be rewriting the role of the manager, but they’re also elevating the value of human-centered leadership in driving trust, performance, and culture.

HR actions to take

• Redesign leadership programs: Focus learning on influence, empathy, and collaboration rather than just oversight.
• Recognize distributed and informal leadership: Update performance and rewards to celebrate leadership behaviors at every level.
• Support managers in transition: Help traditional managers let go of admin-heavy tasks and embrace the coaching and trust-building roles AI cannot replace.

Over to you

These 11 trends offer a practical roadmap for what HR needs to prioritize in 2026 and beyond. They highlight the key shifts reshaping work, from how AI is influencing decisions and how skills and roles are being redefined to the evolving employee experience.

Whether it’s contributing to AI strategy, strengthening human capabilities, or redesigning workforce planning, the opportunity for HR is clear. These changes are already underway, and the way HR responds will shape both business outcomes and the future of work. Now is the time to act with confidence, bring others along, and build the kind of HR function that creates lasting value for both the organization and its people.

You can read about 2025 HR trends here.