HR Professionals: The Seven Most Important Areas in 2026

It stands to reason that you have already prioritised your HR activities for the coming year. Obviously, no one can predict what may happen in the year ahead. This is especially the case given the unprecedented pace at which inventions and innovations are improving the HR tech landscape. The ‘alphabet soup’ is getting new ingredients with every product release from tech companies—case in point: AI, ML, DL, LLMs, GenAI, RPA, Agentic AI, MCP, and so on. This will obviously impact the recipe of our HR strategy for this year.

During the previous year, we have seen companies experimenting with AI pilot projects in several areas with varying degrees of success. Giving us immense insights into where we should and should not implement these new products. During 2025, we have also seen announcements from Google about adding AI agents to Google Workspace, and from Microsoft about adding agents to (Agent 365) Microsoft 365. 

 

According to various HR tech analysts, we are moving towards integration. Essentially, determining the effective mix of human and machine intelligence. It offers an opportunity for HR professionals to rethink and improve our HR function, enabling us to become indispensable to the success of our company by moving from tactical support to strategic value creators. However, we hope that while implementing Agentic AI in the capacity of a Change Agent, HR professionals will not neglect their most important duty of being an Employee Champion.

We are considering seven important areas that will mainly impact various HR functional processes. Since the implementation of AI is now table stakes, the emphasis will shift towards redesigning work, leadership, and culture for an AI-based environment.

1. AI-First HR Model

The advent of artificial intelligence in general and GenAI and Agentic AI in particular has significant implications for organisations. We may have to reinvent our existing HR model for better efficiency and effectiveness, moving from administrative support to strategic value creation. While accommodating these new technologies, we have to think through various angles, such as our industry, products, culture, values, locations, etc., while achieving alignment with our organisational strategy. Also, streamline productization of our HR offerings, ensuring better and improved services to our stakeholders. Although consultancies are offering their impressive models, such as McKinsey, Gartner, etc. We could better devise a bespoke alternative to our unique situation. Dave Ulrich offers perspicacious and valuable perspectives on this point; see the link here.

One HR model (design or structure) does not fit all situations. The structure of the HR department should match the structure and strategy of the business. —Dave Ulrich

Various HR experts suggest developing 'Talent Orchestration Hubs' wherein AI-driven tools instantly match skills to projects and opportunities. It will provide the necessary impetus to address rigid hierarchies. We need to implement an 'AI-infused' structure, moving away from a transactional pecking order towards a transformative approach across the organization. It will also optimize the reallocation of resources, ensuring the structural evolution of the people function. 

Various HR experts suggest several ways to steward this process, ultimately leading to the same objective. However, we have painted them with a broad brush below:

Evolved Centers of Expertise (CoE)

• Monitor AI transformation across the organization, while ensuring strategic coherence and reducing risk. 
• Devise bespoke options, processes, and HR products for enhancing employee engagement and creating value for stakeholders. 

AI-based Service Centres

• Steward and improve AI systems to deliver services to employees and stakeholders.
• Ensure sparing utilization of (human and machine) resources while delivering value for money. 
• Improve latency and scalability.

Augmented HR People Partners 

• Develop capabilities to leverage AI and deliver enhanced alternatives as strategic partners to leaders. 
• As talent value leaders, represent employee interest and enable human-centric transformation. 

While businesses increasingly rely on AI tools, many leaders point to a lack of advanced technological solutions in people processes. Since these processes are not immutable, HR must modernize its anachronistic legacy systems. In doing so, HR should ensure clear ownership and defined service levels for new AI-based alternatives, leveraging the combined capabilities of humans and machines to enhance organizational efficiency.

In the days ahead, value creation will be achieved through the flawless integration of clean data, RPA, agents, and a human-centric, coherent system. Every day, employees are saving hours with the help of advanced AI copilots and agents. Appropriately utilizing this reclaimed time for capability development will be essential to value creation.

2. Redesigning Work 

No organization is impervious to recent technological advancements. It has appreciable implications and impact on how work is performed. The workflows and processes are developed from the ground up for effective human and machine collaboration. However, instead of implementing any off-the-shelf tools, companies need to redesign the processes / workflow for AI-first implementation. 

There is a veritable smorgasbord of options available these days for HR professionals to effectively organize work through automation. However, the actual concern is where we should and should not apply RPA or Gen AI + Agentic AI. Since it is a nascent technology, one can only advocate proceeding advisedly in that direction. There will be certain processes that will be better handled by human beings. However, the repetitive processes can be better managed through suitable alternatives such as RPA or Agentic AI. 

To optimise human-machine collaboration, we can ensure strategic categorization as follows: 

• Automation - Automate repetitive tasks
• Augmentation - Enhance human productivity with Copilot. 
• Redefinition - Optimise work for effective Human-AI collaboration 

For redefinition, we need to consider work at the task level: who is doing what, how many times, and how each activity aligns with organizational objectives. Theoretically, for comprehensive analysis, we could consider 'job task analysis', mainly identifying daily tasks and requisite skills. However, to practically identify automation opportunities, 'Task intelligence' (aka 'Task mining') can provide valuable insights on the tasks suitable for automation versus human expertise. 

To get a better and complete view, we can also consider skills data (available and essential). According to Dave Ulrich 

"Doing worktask rather than workforce planning helps HR and business leaders focus on how to improve performance using AI. Ask: What work tasks can I now do better or faster using AI?"

3. Orchestrating Leadership for Transformation  

Take any annual HR trends report from major consultancies and, unsurprisingly, you’ll find leadership listed as an important topic. This can largely be attributed—among other factors—to issues such as attrition and leadership transitions, which affect the development of leadership bench strength. 

 

It has become a strategic necessity due to the unprecedented pace of change, not to mention its impact on organizational adaptability due to continuous and overlapping disruptions. Gartner suggests that in 2026, 'Your leaders must routinize — not just inspire — change.' They emphasise that leaders should help employees see change as a normal process while developing intuitive responses to new situations. Taking this approach helps organizations succeed while also ensuring employee wellbeing. It also enables the healthy implementation of change. 

“Leaders are not born; they are grown,” as Peter Drucker observed. Developing leadership bench strength is always a pivotal mandate for HR professionals. No one can gainsay the fact that it is a sine qua non for successful strategy implementation. This is primarily due to the indispensable part leaders play in demonstrating and shaping culture, values, and norms, as well as in their day-to-day engagement using proven tactics to cultivate intuitive responses to change.

McKinsey suggests that, while developing leadership capabilities, we should not let technology lead our organisation. In this new era of work, we should prioritize investment in human capabilities. We need leaders to provide robust support showing empathy and genuine care for our employees, while also actuating them to enhance their productivity. 

Does the organization have exceptional leaders, consistently across all levels, who inspire confidence, make smart decisions, and boldly steer the organization toward success? - Mckinsey

Mckinsey

To effectively steward this process, we can leverage AI coaching and develop the following leadership capabilities:

Coaching and mentoring

• Training teams to manage bots - agents. 
• AI interaction to monitor and evaluate output. 
• Develop analytical thinking.

Creating a secure environment

• Ensure stability in technological uncertainty. 
• Demonstrate empathy and genuine care.
• Employee appreciation and recognition.

Strategic Nimbleness 

• Decentralization of decision-making. 
• Investing in data-based decisions.
• Foster innovation and creativity.

Improved judgement

• Clarify ambiguity and enhance sense-making.
• Develop systems thinking and managing change.
• Pattern recognition and contextual awareness.

Decisive initiative

• Action orientation and shaping culture.
• Assessment of employee potential.
• Devise and implement development interventions.

4. Culture in the AI era.

Authenticity in culture is non-negotiable, according to McKinsey. An incontrovertibly authentic culture is pivotal from a strategic implementation perspective—especially when stewarding an AI-first transformation. According to Great Place to Work, the biggest hurdle to transformation isn't technology—it's people. That is to say, while implementing advanced technologies such as AI, we must not neglect our people.

A people-first culture prioritizes employee wellbeing, development, and engagement, based on the belief that when employees thrive, the organization thrives. A vibrant, healthy culture boosts morale, drives productivity and performance, and ultimately improves the bottom line. Forward-thinking companies will integrate technological advancements in ways that reinforce a robust people-first culture. Consider this open-source approach —an innovative and new way of stewarding culture. 

Over the coming years, it will become increasingly clear how AI is radically reshaping the way we work. To navigate this transformation effectively, organizations must foster healthy human connections—where employees feel cared for, nurtured, valued, recognized, and appreciated for meaningful work. To realize our company’s AI vision, HR professionals can conjecture future skills requirements, lead upskilling and reskilling initiatives, and cultivate a culture that galvanizes employees to be enthusiastic about AI.

A growth mindset, conveying that people can grow and improve with effort, good strategies, and good mentoring: We call this a “culture of development.” — CAROL DWECK

Developing culture is a perennial, evolving process. As an organization grows, leaders initially establish the culture and then continuously evolve it. Leaders must clearly demonstrate and exemplify cultural norms and values at every level of the organization.

Establishing a sustainable culture requires leaders to devise clear processes, mechanisms, and unequivocal guidelines that foster a healthy work environment. Robust cultures mold behaviors, mindsets, and beliefs, shape how people work, and influence workplace interactions.

Design onboarding and orientation processes that ensure cultural absorption of the company’s values and history through manuals, videos, and internal communication channels. Support this with mentorship initiatives, pairing seasoned employees with new hires to ensure integration. To reinforce culture, consistently recognize and celebrate desired behaviors and actions.

Because culture is an ongoing process, it requires periodic maintenance and fine-tuning. To take stock, organizations must assess the existing culture using a multi-pronged approach that blends quantitative data with qualitative insights—numbers with stories, data with anecdotes. According to Achievers, there are seven effective ways to measure culture: employee surveys, performance management tools, people analytics, exit interviews, behavior observation and recognition, focus groups, and organizational assessment systems.

5. Establishing Skills-Based infrastructure

Whether we are hiring or developing our people, skills have now become the currency of work, and skill-first talent management is gaining traction. The advent of technological advancements has magnified inconsistencies between the skills required and those possessed by the workforce. To address this mismatch, companies essentially have to hire or develop these skills. It is not uncommon for them to rely on structured internal mobility strategies to address the issue and even reduce hiring costs.

Certain vital positions in every organisation may still require hiring. As skills have become the new currency, LinkedIn suggests that "skills-first hiring isn't simply an industry trend; it's the new competitive advantage." By shifting attention to potential, this approach also democratizes access to jobs, expanding the talent pool to include individuals without formal degrees. While we cannot predict the jobs of the future, we do know the skills they will require. According to LinkedIn, 93% of talent acquisition professionals believe that improving the quality of hire requires greater accuracy in skills assessment. The good news is that AI can support this process by prioritizing skills in résumé screening, automating assessments, standardizing interviews, and reducing bias. Explore how LinkedIn is developing the agentic future of recruiting. 

Vendors such as Darwinbox suggest implementing a “talent marketplace” to enable skill-first talent management, foster internal mobility, reduce hiring costs, and improve retention. Based on skills and talent data, it allows employees to move vertically, horizontally, or across functions by developing bespoke career paths for them. However, companies need to invest in AI-based tools, skills taxonomies, a culture of managerial support, and reskilling options geared toward employees.

Developing employees through upskilling and reskilling is an equally essential element of skill-first talent management. AI-based solutions address this need through bespoke content recommendations, AI coaching, and the ability to locate suitable mentors within the organization. However, it is incumbent upon HR professionals to develop and foster a learning culture ingrained in the flow of work.

Organizations can also provide the necessary tools, resources, and opportunities to develop core skills, as well as adjacent and complementary skills. Ultimately, the onus lies with employees to drive their growth. According to HiBob, companies can cultivate AI-first, skills-based learning to realize the potential of every employee, ultimately helping organizations adapt, thrive, and create a better future of work.

As discussed earlier, there is a discernible trend toward a shift from skills- to task-level insights. This granular approach emphasizes concrete, observable, and relatable tasks. AI-based task intelligence provides a continuously updated and validated view of skills and tasks across the organization, delivering a live feed through dashboards for leaders.

Some vendors are experimenting with a skills intelligence layer—a systemic approach that connects and unifies various HR technologies while concurrently ingesting and standardizing their skills data (and feeding the data back into those systems). Rather than replacing the existing tech stack, it enhances the stack with a unified skills language supported by an AI-driven skills layer.

A core competence represents the sum of learning across individual skill sets and individual organizational units. — HAMEL AND PRAHALAD

6. Total wellbeing - Health and Work-Life Balance.

Workforce wellbeing is no longer a ‘nice to have’; it is a core driver of business performance and competitive advantage, according to McKinsey. Now more than ever, total wellbeing is a strategic necessity, especially when leading an AI-first transformation. Drawing on the extensive discourse on this topic, it is clear that these developments have significant implications for our conscientious employees. These technological advancements demand constant change and adaptability, while also creating uncertainty—impacting employee health, wellbeing, productivity, absenteeism, engagement, morale, and work–life balance.

It stands to reason that a healthier workforce drives higher productivity. To navigate an increasingly uncertain environment and develop organisational resilience, companies must prioritise investment in employee health. This requires a holistic approach—supporting physical wellbeing, mindfulness, stress management, financial wellbeing, family wellbeing, spiritual wellbeing, and social wellbeing. McKinsey emphasises that employees with robust health consistently demonstrate superior performance, greater innovative behaviours, and improved work–life balance, with these benefits sustained over time.

To ensure our company stands the test of time, we must adumbrate a clear action plan. Yet, amid the proliferation of available options, important questions arise: Where do we start? Which interventions deliver the greatest impact? Which are the easiest to implement? To address these questions, McKinsey analyzed 115 evidence-based workplace interventions. Their rigorous, reductionist analysis offers perspicacious insights into the most effective interventions for improving organisational outcomes and employee health and wellbeing.

To improve multiple dimensions of health and enable employees to survive and thrive, McKinsey identified a set of proven, evidence-based interventions. These interventions:

• Reinvigorate basic enablers such as coworker support, adaptability, job autonomy, and visible leadership commitment.
• Integrate support into the flow of work, increasing participation and ensuring sustained impact beyond initial implementation.
• Are accessible and scalable when there is limited dependence on specialist expertise, thereby supporting widespread acceptance and sustained outcomes.
• Deliver compounding benefits by melding physical and social elements, improving coworker connections, promoting physical activity, and enhancing physical and spiritual health.
• Analyse outcomes for employees and the organisation, enhancing credibility and leadership support through demonstrable, sustainable impact.

People are happy when you give them what they ask for. People are delighted when you anticipate what they didn't think to ask for. It's proof that they're wholly visible to you as people, not just as workers from whom you're trying to squeeze productivity. — LASZLO BOCK

Employers increasingly recognise the importance of wellbeing initiatives and prefer to invest with precision and scale. However, success depends on designing a compelling employee experience informed by design thinking. This includes offering benefit alternatives that enable employees to choose options—or bespoke benefits—based on their individual needs and preferences. Achieving this requires a disciplined focus on outcomes, prioritising areas of maximum impact, and developing initiatives that integrate seamlessly into the flow of work.

In this new wave of AI transformation, we are moving from generative AI toward agentic AI—where intelligent agents can:

• Identify individual needs
• Provide bespoke, context-aware support
• Manage tasks around multiple systems
• Deliver timely nudges and prompts
• Coach and guide employees and managers
• Support everyday decisions to improve wellbeing
• Continuously learn from feedback to enhance support over time

[HR Professionals, please read] 

Dave Ulrich once said that the cobbler’s children should not go unshod. Read his blog on this topic. 

7. People Analytics and Agentic AI

Peter Drucker said, “What gets measured gets managed.” Software and apps of every description now inherently provide analytics capabilities, with dashboards ingrained with graphs and charts. People analytics, once considered a luxury, is now evolving into a necessity for delivering perspicacious insights. AIHR suggests analytics software and tools to support our people analytics team.

Earlier analytics tools (e.g., SQL) required meticulous queries and knowledge of data science, and mathematics. The advent of Generative AI has culminated in the democratization of data science in general, and people analytics in particular. With simple and intuitive interfaces and a shallow learning curve, Generative AI allows access to valuable insights through asking the right prompts. Instead of waiting days, employees can instantly obtain perspicuous explanations along with actionable recommendations that even a layperson can understand.

As James Thurber said, “It is better to know some of the questions than all of the answers.” This insight has become an indispensable capability, paving the way for the emergence of the Prompt Engineer position. To effectively harness the actual potential of Generative AI for deriving accurate and meticulous insights, one must ask the right prompts. Providentially, well-crafted prompts can now be generated with the help of Generative AI itself.

The AI today is now able to show you the data and prompt you the next question, because the purpose of analytics is not to answer questions, it’s to get people to ask better questions. — PAUL RUBENSTEIN

 

HR professionals are striving to develop an analytics culture predicated on a data-based HR function. As data can now be accessed easily from anywhere, it saves time, effort, and valuable resources. However, obtaining clean and reliable people data remains a major concern for improving accuracy and analysis. Creating such a culture within the people team is an evolving process that requires continuous effort and fine-tuning to normalize evidence-based decision-making at all levels.

Nevertheless, it helps us better understand our most valuable asset—our people. In pursuit of this objective, we can implement various tools, including interactive dashboards, trend analysis, and predictive modeling. AIHR suggests five dashboard software tools to equip our team. Despite the plethora of HR tech applications, the need for upskilling remains a constant concern—particularly in data interpretation, analytical thinking, and change management. This presents an opportunity for HR professionals to support business leaders in achieving their objectives by simplifying complex and irreplaceable human elements such as creativity, empathy, and human judgment.

Developing an impressive data-based HR function indubitably requires compliance with the laws of the land. Countries are increasingly legislating to secure data privileges for their citizens, particularly through recent regulations related to AI, algorithms, explainability, pay transparency, data privacy, and data protection. HR must strive to foster ethical AI through reducing algorithmic bias and ensuring compliance with these evolving requirements, while establishing clear data governance and visibility through integrated systems. Typically, vendors secure sensitive data through protections such as RBAC combined with rules-based access. This ensures that employees can access only the information pertinent to their position and authority.

The most important question now is: which direction are we moving in—particularly with respect to the future of work, analytics, and agent-driven insights? Many progressive vendors are developing capabilities such as multi-agent orchestration, leveraging the Model Context Protocol. This approach improves the quality of agent-driven insights by delivering comprehensive analysis—not only what is explicitly asked—consequently reducing unnecessary prompt-and-response exchanges. It works like a human data science professional at your beck and call, perspicuously expatiating the complete analysis with the depth and judgment of an experienced analyst. This represents the culmination of agentic systems—those that anticipate, reason, and amplify human intelligence.

Conclusion

Despite the significant hype surrounding AI transformation, much ink has been spilt on this subject, and the jury is still out. Since it's a nascent technology, one can only advocate proceeding advisedly in that direction. While pursuing sublime AI-first talent management, we should place less emphasis on technology itself and instead generously invest in cultivating human capabilities. That is to say, invent empathetic processes that foster a caring organizational culture. Leaders will disseminate verve and enthusiasm among employees through empathy and genuine care, while also enhancing their productivity.

It will stand us in good stead to strike the right balance between human and machine intelligence while pursuing AI-based transformation. While holding brief for employees as an employee champion, HR ensures their betterment, development, and growth through targeted interventions. Concurrently, galvanizing them to achieve organizational objectives through enhanced productivity. This approach positions HR to become indispensable to the organization, transitioning from a provider of tactical support to a creator of strategic value. It is incumbent upon HR professionals to rise to the occasion and provide the necessary impetus to ensure effective implementation—at which point, the world genuinely becomes their oyster.

One machine can do the work of fifty ordinary men. No machine can do the work of ONE extraordinary man. — ELBERT HUBBARD