Global Human Capital Trends 2026 by Deloitte: Re-recording an Organization for an Age of Symbiosis

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Introduction: From overcoming contradictions to creating a symbiotic organization

In 2025, the human capital landscape was defined by a series of fundamental contradictions. Deloitte’s report «Global Human Capital Trends 2025: Turning contradictions into a triumph» accurately captured this state of tension in which leaders around the world found themselves.¹ The organization was forced

balance between seemingly mutually exclusive imperatives: the need to provide stability for employees in conditions that require unprecedented flexibility from business (concept of «Stagility»);
the desire to empower teams while maintaining control; and the choice between automation for efficiency and enhancement for human capacity.²

These contradictions were not a sign of weakness, but the inevitable symptoms of an initial, somewhat chaotic phase of adaptation to powerful but not yet fully meaningful technologies, primarily to generative artificial intelligence.

The forecast for 2026 indicates a qualitative shift. The focus shifts from the management of these individual contradictions to their resolution through a purposeful and profound «re-scanning» (rewiring) of the entire organization. It is no longer a question of seeking compromises, but of creating a new, holistic operating model - a symbiotic organization. In this model, human and machine intelligence do not simply coexist or compete, but enter into a synergistic partnership where each enhances the capabilities of the other, creating value that is unattainable for each individually.

The catalyst of this transition will be the explosive development and introduction of an agent AI (Agentic AI). Unlike generative AI, which mainly creates content on demand, agent systems are able to autonomously plan, make decisions and perform complex, multi-step tasks by interacting with the digital environment.⁵This turns AI from a passive assistant into an active participant, and sometimes a workflow coordinator.

This report explores how this fundamental shift will manifest itself in the key trends of 2026. The analysis is built around three domains, inherited from the Deloitte structure:

Work ,
Workforce and Organization & Culture. ²

Each domain will show how the trends and contradictions of 2025 are being transformed into more mature and integrated 2026 paradigms, shaping the contours of the organization of the future.

Table 1: Evolution of human capital trends from 2025 to 2026

This table is a conceptual map of the report, showing the logical continuity and evolution of key ideas. It shows how every problem or contradiction identified in 2025 finds its resolution or integration in the projected trends of 2026, emphasizing the transition from tactical response to strategic design.

Part I: WORK: Designing value creation flows in hybrid intelligence

In 2025, organizations mainly focused on optimizing existing business processes around new AI tools, trying to fit them into the usual framework. In 2026, there is a fundamental shift: companies begin to redesign the work with AI, viewing it not as an auxiliary tool for improving efficiency, but as a full-fledged partner in creating value. It is a transition from adaptation to collaborative design, where workflows, command structures and decision-making processes are created initially for a hybrid environment of people and intelligent machines.

Trend 1: Active AI as a new team member: from task automation to process orchestration

This trend is a direct development of the 2025 theme «AI revolutionizes work». 1 Whereas in 2025 the focus was on generative AI capabilities in content creation, in 2026 the focus is on agent AI. This is the next evolutionary step: autonomous systems that can not just respond to requests, but independently plan, make decisions and perform complex, multi-stage work processes.⁵ Agent AI becomes not just a tool, but a «virtual colleague» or even a whole «digital workforce», able to coordinate actions, interact with various software applications and even manage other, more specialized AI agents.⁶ PwC exactly calls this technology «exponential multiplier of the workforce», highlighting its ability to dramatically increase productivity.⁹

According to the McKinsey analysis, an agent AI is a system that «perceives reality... resolves, applies judgment and performs something», which can eventually lead to creating a «digital copy of the entire organization’s workforce». 5 This means moving from an AI that responds to an AI that shows initiative. Examples of this approach have already started to appear in 2025: in recruiting, one AI agent can analyze a huge pool of candidates, the other - to conduct their checking and ranking for further human consideration.5 By 2026, this practice will become widespread and spread to such complex areas as supply chain management, where AI agents will coordinate logistics, procurement and demand forecasting; project management, where they will track progress and allocate resources; and financial analysis, where they will conduct comprehensive risk assessment and prepare reports.

The emergence of agent AI will lead to the formation of a completely new organizational layer - «digital middle management». These systems will take over much of the functions that previously required human control, coordination and administration. The Deloitte report for 2025 noted that managers spend almost 40% of their time on current problems and administrative tasks, and only 13% on developing their employees.8 Agent AI directly solves this problem. Its main function is orchestration and coordination: distribution of tasks among team members (both people and other AI), monitoring the progress of execution, realtime allocation of resources and ensuring information flow. This not only «unloads» the human manager, but also fundamentally changes the nature of management. Organizations will create entire ecosystems of AI agents that will take over routine coordination, allowing human teams to work more autonomously and flexibly. The role of human manager will shift from controller to strategist, coach and specialist in solving non-standard, creative and ethically complex problems that require human intuition and empathy.

Trend 2: «Stable dynamics» (Evolved Stagility): creation of adaptive operational models

This trend represents the evolution of the concept «Stagility» proposed by Deloitte in 2025.1 If in 2025 it was the search for a delicate balance between stability and flexibility, then in 2026 «stable dynamics» becomes a fully operational model, implemented through technology and new organizational principles. Companies are moving massively from rigid hierarchical structures to dynamic, project-oriented models where teams are formed for specific tasks and are dispersed upon completion, and employees are constantly moving between projects.¹⁰

The concept of «stagility» emerged as a response to the disappearance of traditional sources of stability for employees - such as static job instructions, long-term teams and linear career paths.⁷ In 2026 this problem is solved systematically. Flexibility (Agility) is provided by AI platforms, which in real time analyze the needs of the business and select the optimal teams for each project. These platforms take into account the skills, current load, previous experience and even work styles of employees, and can also include the necessary AI agents in the teams. Stability (Stability), in turn, comes not from the immutability of structure, but from transparency and consistency of «rules of the game». New stability anchors are becoming:

Clear and understandable ethical framework for the use of AI.
Objective and transparent criteria for assessing contributions to projects.
A strong psychological safety culture that allows people to work confidently and creatively in ever-changing teams.
Research has already shown that levelling out hierarchies is not just a trend, but a process that actively changes the composition and expectations of the workforce.¹²

This transition to adaptive operational models fundamentally changes the role of HR-functions. From an administrative center dealing with human resources processing and annual appraisals, HR becomes a strategic «Talent Orchestration Hub» (Talent Orchestration Hub). The basis of its work becomes the internal talent marketplace (AI-managed platform), which dynamically compares employees with projects. Traditional HR processes, such as job-specific hiring or annual performance appraisals, are no longer relevant in a design-oriented environment. Instead, the HR system analyzes in real time what skills are needed to solve current business problems and finds the bearers of those skills within the organization. HR business partners from administrators become «talent brokers», which help project leaders quickly assemble effective teams, and employees find projects that match their career goals and development plans. This marks the final transition from post management to skill orchestration.

Trend 3: Rethinking Productivity: From Measuring Effort to Estimating Total Contribution

Back in 2025, Deloitte pointed out the need to move from measuring productivity (number of tasks completed) to assessing human performance, which includes well-being, Innovation and adaptability.⁴ In 2026, this concept expands and deepens into the idea of «synergistic performance». The focus shifts from assessing individual contributions, whether human or AI, to measuring the aggregate value created by their collaborative work.

Data confirms this shift. The PwC study found that in the most AI-intensive industries, revenue growth per employee is three times higher than in low-adoption industries.⁹ This convincingly proves that AI is not just a tool to reduce costs, a powerful driver of new value and growth. At the same time, Gartner warns that a blind «AI-first» approach, focused solely on technology without taking into account human factor, can paradoxically reduce productivity due to increased cognitive load on employees and resistance to change.¹¹

Thus, in 2026 companies will begin to introduce new, more complex performance metrics. Instead of counting the working hours or the number of closed tickets, they will measure:

Speed of solving complex, unstructured problems with hybrid teams.
Quantity and quality of innovations generated (new products, improved processes).
Measurable impact on customer experience and satisfaction.
Ability of the team (man + AI) to adapt quickly to new challenges and market changes.

This new approach to productivity means the ultimate collapse of traditional performance management systems. Deloitte questioned their value as early as 2025, arguing that more than a formal evaluation process is needed to unlock human potential.²In a dynamic, project-oriented environment, annual evaluation becomes meaningless. Value is created in synergy, and to evaluate a person and an AI separately means to miss the most important thing.

The old systems are replaced by value creation management (VCM). They are based on continuous data collection and analysis from working platforms (such as Jira, Slack, GitHub, Teams) to track value creation flows in real time. Instead of a retrospective question

«Did the employee achieve their KPI?», the new system will answer questions:
«What contribution did this team, including its AI agents, make to the advancement of project X?»,
«What interactions and communication patterns led to the breakthrough solution Y?»,
«Where are the bottlenecks in the process that slow down the creation of value?».

It is a transition from the evaluation of people to the analysis of the work system, which allows not to penalize but to constantly improve processes in order to achieve maximum synergy.

Part II: WORKFORCE: Shaping talents and career paths in the age of AI

In 2025, the main task was to adapt the existing workforce to the emergence of AI, mainly through retraining and digital literacy programs. By 2026, this task is becoming much more challenging and ambitious. It is no longer a question of adaptation, but rather of the purposeful design of new career trajectories, development models and motivational systems that initially imply a deep and permanent symbiosis between man and AI at each stage of the professional journey. Organizations are moving from a reactive smoothing of skill gaps to a proactive creation of a future-ready ecosystem of talent.

Trend 4: New competence model: development of «interaction skills» with AI

The emphasis in talent development is shifting from general «digital skills», such as the ability to use office programs, to highly specialized competencies required for effective symbiosis with advanced AI systems. It is no longer simply the possession of a tool, but the ability to manage, direct, critically evaluate and ethically control the work of autonomous intellectual agents.

Demand for such skills is growing exponentially. The PwC study showed that in professions affected by AI, the set of required skills changes 66% faster than in other areas. Moreover, having specialized AI skills such as leapfrogging or working with machine learning models already gives a wage premium of 56% on average. 9 This indicates a huge shortage and high value of such competences in the market.

The key skills that will determine the value of a specialist in 2026 will be:

Orchestration of AI agents: Ability to decompose a complex business task into sub-tasks, distribute them among several autonomous AI agents, coordinate their joint work and control the end result.
Interpretation and verification: The ability not just to accept on faith results generated by AI, but to critically evaluate them, identify hidden biases, logical errors and potential «hallucinations» of models.
Ethical oversight: A deep understanding and practical application of ethical principles when working with AI. This includes ensuring the fairness of algorithms, data protection, transparency in decision-making and preventing discrimination.
Synergistic synthesis: The ability to combine intuitive human knowledge, experience and contextual understanding with vast amounts of data processed by AI to make better, more holistic and wise decisions.

As work is increasingly performed by hybrid teams of people and AI, and the effectiveness of these teams depends directly on the quality of interaction between them ⁶, there is a need for a new professional role. As with the development of software, UX/UI-designers responsible for user-friendly interaction with interfaces appeared, in 2026 a new category of specialists will appear - «AI interaction designers» (AI Interaction Designers) or «hybrid intelligence interaction managers». Their task will not be the development of AI-models themselves, but the design of efficient, safe and intuitively understandable processes of joint work of people and AI-systems. These specialists will develop «communication protocols» with AI, train employees in the best practices of interaction, optimize work processes for maximum synergy and act as intermediaries between technical teams and business users, ensuring that technology serves people, not the other way around.

Trend 5: A solution to the «paradox of experience»: creating alternative career paths

This trend is a direct consequence and deepening of the «experience gap» issue, which Deloitte identified as one of the key ones in 2025.¹ Automation of routine tasks and reduction of traditional entry-level roles that served as the «entry point» in the profession, create a serious paradox: to get experience, you need work, but jobs where you can safely and gradually get basic experience, is becoming less.⁸In 2025, 66% of managers complained that recent graduates are not ready for real work due to lack of practical experience, and 73% of organizations recognized the need to create more opportunities to receive it.⁸

In 2026, leading organizations move from problem statement to its systemic solution, introducing alternative paths of professional development that do not depend on the existence of traditional starting positions:

Digital Apprenticeship (Digital Apprenticeship): New employees start working in pairs with an AI mentor. This instructor analyzes their actions in real time, gives tips, corrects errors, offers relevant learning materials and helps to learn the necessary skills more quickly in the context of real work tasks.
Hyper-realistic simulations: AI is used to create complex and dynamic business simulations in which employees can safely practice decision making, negotiation, crisis management or launch new products. This allows you to gain valuable experience without risk for real business.
Skill-based project rotations: Instead of linear career progression, staff members move between different projects, purposefully acquiring the skills they lack. The AI career planning system helps to draw up an individual development plan and selects projects that best contribute to its implementation.¹⁴

These changes lead to the fact that the concept of «career ladder» finally gives way to the model of «career portfolio». The value of a staff member is not determined by his or her position, grade or experience, but by the unique set of proven skills and portfolio of successfully completed projects. Linear promotion «up» loses its meaning; instead, employees seek to «expand» their portfolio by adding new experiences from various projects. It also stimulates the growth of «polyworks» (polyworking), when specialists simultaneously participate in several projects, often in different roles, which allows them to develop faster and bring more benefits to the company.¹⁵ HR and managers in this new paradigm act as career consultants, Helping employees shape a portfolio that fits both their personal ambitions and the strategic needs of the organization. This, in turn, requires a complete overhaul of reward systems, which should be tied to skill sets and real contributions to projects rather than formal positions.

Trend 6: Evolution of employee value proposition (EVP): from balance to integration and reinforcement

In 2025, Deloitte called on organizations to create a new value proposition for the employee (EVP), adapted to the AI era.¹ By 2026, this new EVP is crystallized around the powerful idea of «supergeniality» (Superagency), proposed by McKinsey and LinkedIn co-founder Reid Hoffman.¹⁶ The essence of this approach is that the value proposition is not about protecting employees from AI or finding a balance between work and technology, Providing them with the tools and opportunities to multiply their own intelligence, creativity and business impact.

EVP moves away from the traditional promise of "We will give you a good work-life balance and a stable salary" to a new, much more ambitious one: «We will provide you with AI-super power, so that you can do the best job in your life, solve the most complex tasks and grow exponentially as a professional».

The key components of this new, enhanced AI value proposition are:

Access to advanced AI tools: Provide employees with not just standard, but best-in-class, customized AI agents and platforms that give them a real competitive advantage.
Culture of experimentation and innovation: Actively encourage employees to find new, non-standard ways to use AI to solve business problems and create new products and services.
Focus on uniquely human skills: Targeted investments in the development of what AI cannot replace yet: critical thinking, creativity, emotional intelligence, empathy and strategic vision.
Influence and autonomy: Giving employees significantly more autonomy in decision-making, as AI takes over routine control and micro-management, freeing a person for strategic work.

This shift in EVP fundamentally changes the dynamic of «talent wars». If previously companies competed mainly at the expense of wage level, bonuses and social package, then in 2026 the main field of battle becomes «computing resources» and «quality AI-partners». Productivity and, as a consequence, the value of an employee increasingly depend on the quality of its interaction with AI.⁹A talented specialist, equipped with advanced, specially trained for the tasks of the company’s AI agent, will be able to achieve by far greater results than the same specialist, using a public tool. Therefore, when choosing an employer, the key factor for the best employees will be the «technological stack» provided to them. Candidates in the interviews will ask questions:

«Which AI models will I work with?»,
«How deeply are your AI agents customized to the industry?»
«What computing power and data volumes do you provide for experiments?».

Thus, the employee’s value proposition becomes largely a technological proposition, and HR and IT must work closely together to create and promote it in the labor market.

Part III: ORGANIZATION AND CULTURE: Building trust and resilience in the digital environment

As AI becomes more autonomous and deeply integrated into the fabric of organizations, so-called soft aspects - culture, leadership, trust and human relationships - paradoxically become «solid», critical success factors. Technological transformation is doomed to fail without a parallel and equally profound cultural transformation. In 2026, the organization’s ability to build trust in its digital systems and strengthen human connections in a hybrid environment will directly determine its resilience and competitiveness.

Trend 7: Proactive governance and AI ethics as the foundation of corporate culture

As the use of agent AI scales, issues of ethics, transparency, fairness and reducing bias are no longer a narrow task for the corporate or legal services. They become the centerpiece of corporate culture, employer brand and foundation for building trust both inside and outside the organization.¹⁷Trust in how a company develops and uses AI is becoming one of its key intangible assets.

Concerns about AI are the main barrier to its implementation. Research shows that leaders are most concerned about the bias of algorithms (45% of respondents), data confidentiality (40%) and lack of transparency in AI decision-making.¹⁸ Ignoring these issues leads not only to legal and reputational risks, but also to internal resistance, undermining the effectiveness of any technological initiative.

In 2026, leading companies will move from reactive response to problems to proactive creation of integrated frameworks for ethical AI. Such frameworks will include several mandatory components ²¹:

AI Ethics Committees (AI Ethics Committees): Cross-functional teams comprising representatives from HR, legal, IT, business and external experts who will conduct risk assessments of all new AI projects prior to their launch.
Mandatory human control (Human-in-the-loop): Introduction of the principle that all critical decisions, especially those relating to people (recruitment, promotion, dismissal) must be verified and approved by a person.
Transparency and explainability (Explainable AI, XAI): Ensuring that employees can receive a clear and understandable explanation as to why the AI made a decision regarding their work, evaluation or career prospects.

It is important to note that, according to Gartner research, employee activism will play a key role in shaping and implementing responsible AI standards, making companies more open and accountable.11

The effectiveness of human-AI symbiosis depends directly on the trust that a person has in their AI partner. If the employee does not trust the data, recommendations or solutions offered by AI, he will not use them and all the multi-million dollar investment in technology will be useless. This mistrust may be caused by the opacity of the «black box» operation, fears about algorithm bias or fear that AI is being used for total control and surveillance.18 Therefore, organizations will need to systematically measure and manage this trust. This will lead to the emergence of a new indicator of health of the organization - «AI Trust Index» (AI Trust Index). Companies will regularly conduct surveys and use analytical tools to assess the level of confidence of employees in the AI systems used.
The questions in such questionnaires will include:

«How sure are you about the fairness of AI decisions in your team?»
«Do you understand how the AI system comes to its conclusions?»
«Do you think that AI helps you work better, not just controls you?».

The low index will serve as an early warning of serious cultural and operational issues requiring immediate intervention. This indicator will become as important for HR and management as the Employee Engagement Index (eNPS) or Satisfaction Index today.

Trend 8: Redefining the role of leader: from manager to interaction coach

This trend is a logical conclusion to the discussion on the «reinvention of the role of manager» started by Deloitte in 2025 ⁴, and develops the priority of Gartner for the development of leaders.²⁷ In 2026 the role of leader is completely transformed from «manager» (the person who manages tasks and supervises their execution) into an «orchestra of hybrid intelligence». Its main task is not to distribute work, but to create and maintain an environment in which people and AI agents can cooperate as effectively as possible to achieve common goals.

In 2025, research has shown that managers are overloaded, not ready for the future and spend most of their time on administrative routine.⁸ AI, especially agent, takes over this routine, freeing the leader to perform new, More complex functions.⁷ The key competencies of a leader in 2026 are:

Creating psychological security: In the face of constant technological change, team reorganization and uncertainty, a leader must be the main source of stability, trust and support for his team.

AI Interaction Coaching: The leader should become an expert in how to work effectively with AI, and train his team. This includes the skills to correctly set AI tasks, critically interpret its results and integrate machine-related information into the human decision-making process.

Strategic and systemic thinking: Instead of micromanaging and monitoring the execution of tasks, the leader focuses on long-term goals, finding new opportunities that the synergy between man and AI opens up, and removing the systemic barriers that prevent hybrid teams from working effectively.

The McKinsey analysis clearly states: «The biggest barrier to success [in AI implementation] is leadership». ¹⁶

Technologies such as active AI evolve exponentially, while human habits and established management models are highly inert. Leaders accustomed to the hierarchy, control, and directive style of governance will, even unconsciously, sabotage the transition to more autonomous, flexible, and trust-based models of work that are necessary for an age of symbiosis.

It follows that the success of the organizational transformation in 2026 will depend by 80% not on the IT department, but on the HR function and its ability to quickly and extensively retrain all management. Organizations that are the first to create effective development programs for «hybrid team leaders» will gain a decisive competitive advantage. These programs should include not only technical knowledge of AI capabilities, but also deep work with thinking (mindset), developing emotional intelligence, coaching skills, and facelifting complex dialogues about the future of work, ethics, and human role in the new reality.

Continued 👉🏻 Global trends in human capital 2026: Overwriting the organization for an age of symbiosis (continued)