Perspective

10 Jun 2026

10 minute read

Deloitte 2026 Global Human Capital Trends Through a Workday Lens

Authors:

Jannine Zucker

Dan Sundt

Kurt Proctor-Parker

Deloitte 2026 Human Capital Trends Through a Workday Lens

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From tensions to tipping points: Choosing the human advantage

Technological advancement is converging with economic fluctuations, geopolitical tensions, societal expectations, and a rapidly shifting workforce, challenging organizations to adapt to change at record speed. As further asserted in Deloitte’s 2026 Global Human Capital Trends report, from tensions to tipping points: Choosing the human advantage, what makes this moment different is that these pressures are no longer sequential, but compounding. The boundary between planning and execution is collapsing, even as cost pressures, efficiency mandates, and questions of trust and clarity intensify. Many leaders feel overwhelmed—aware of the challenges but struggling to act decisively. Tensions once manageable over time are now tipping points, where hesitation risks missed opportunities and lasting consequences for organizations, their people, and society.

In 2026, three tipping points stand out as especially important: from human + machine to human x machine; from cost efficiency to value creation; and from static plans to dynamic orchestration. Each tipping point represents a shift that organizations can no longer defer. They are not distant possibilities but present realities, demanding choices that should define how organizations create value, build trust, and unleash human potential in an AI-powered world.

To inform those choices, many leaders are seeking workforce management systems that can unify data and generate insights to help them reimagine how works get done. This means offering capabilities and leading practices that support them in deliberately designing human and machine interactions; orchestrating capability and capacity at speed; managing change effectively and continuously; and building trust and protecting human agency—all while getting more value from their core functions like HR, finance and IT. As the leading enterprise AI platform for orchestrating people, money, and agents, Workday addresses these requirements and offers additional capabilities.

Deloitte’s 2026 Global Human Capital Trends report offers readers suggestions for unlocking value from AI by bringing of humans and machines together in concert: this companion document examines those suggestions through a Workday lens. Read on to discover what sets Workday apart as a trusted AI platform and Deloitte as the preferred adviser for delivering data-driven insights, elevating the potential of your people, and boosting productivity across your organization through human-machine collaboration.

Tipping Point #1

From human + machine to human x machine

The boundaries between human and machine work is blurring. Organizations may need to redesign work to harness human–machine synergy, moving beyond having humans and machines work side by side. This includes a rethinking of culture, decision rights, and trust in data itself. The questions are fundamental: How does culture evolve when people and intelligent agents work side by side? Who has the authority to decide when algorithms act and when humans intervene? And how can organizations protect themselves against misinformation and untrustworthy outputs in a world where AI is both a collaborator and a risk?

Getting human and machine relationships right

Many organizations take a tech-focused approach to AI, layering it onto legacy systems and processes, rather than intentionally designing how humans and AI interact, collaborate, and make decisions. To succeed in multiplying human potential with AI, deliberate choices need to be made both at the macro level, encompassing design principles, governance, and strategy, and the micro level, comprising specific interactions for particular workflows, workers, and teams. Intentional design should also consider both hardwiring and softwiring. Hardwiring includes formal elements such as redesigned roles, accountability, decision rights, and clear escalation protocols that dictate when work shifts from AI to a human. Softwiring includes informal elements such as leadership behaviors, culture, and psychological safety that give people the trust and confidence to question, escalate, experiment, and learn with AI.

Fact or fabrication?

AI is blurring the line when it comes to people and work

AI is making it increasingly difficult to distinguish between authentic and fabricated work, especially in talent processes. Generative AI can create fake résumés, deepfake interviews, and "workslop"—AI-generated content that undermines productivity and trust. Emerging paths for addressing these risks include effecting a mindset shift from cybersecurity to disinformation security and taking steps to help workers evaluate what’s real and what’s not. The former involves implementing AI lineage mapping and real-time dynamic identity authentication protocols, while the latter entails developing human judgment skills in the workforce and promoting transparency in work outputs.

AI and the future of human decision-making

Many organizations say it is important to address the implications of AI on decision-making such as unclear accountability, diminished human agency and potential for bias or error, but few have made significant progress toward doing so. Leading organizations design for human agency and elevate decision-making as a discipline, using frameworks to classify choices and pre-assign owners, data, and guardrails for different types of decisions as defined by risk, urgency, importance and other key elements. Technology can accelerate analysis and clarify uncertainty, but it cannot replace human purpose, values, and judgment behind choices. This is the path to AI as a trusted advisor improving the speed, scale, and quality of decisions while keeping humans firmly in charge of the “why.”

Superintelligence for work: The future of human-machine collaboration

As AI becomes part of everyday work, most organizations still aren’t intentionally designing how humans and machines interact, limiting returns and reinforcing outdated processes. Deloitte research shows that those who intentionally redesign roles, workflows, and decision-making to support human-AI collaboration is more likely to exceed expectations on investment returns and deliver meaningful work. With AI access widening, intentional design, not technology alone, is becoming the real differentiator.

Workday has long moved beyond simple integration; it is coupling AI with the deterministic foundation required for important HR and finance functions where there is little margin for error. Workday’s AI technology, Sana, understands not just the data, but the full business context—the why or how behind each process. Unlike disconnected chatbots, Sana agents have relevance. They are directly tied to the HR organization’s own data and processes, and they are embedded into the natural flow of work, moving the enterprise from software that simply records interactions to AI that performs them.

With Sana, Workday is, in essence, delivering superintelligence for work. Sana helps to transform the employee experience into a frictionless, conversational interface that acts as a single front door to the entire enterprise. These aren't standalone assistants; they are agentic teammates that handle common tasks, generate real-time analyses from company knowledge, and provide a secure and transparent environment to orchestrate work at scale—while operating within the trusted guardrails and permissions Workday provides.

Even with this level of AI-enablement, work still needs to be intentionally redesigned in order for humans to interact with AI effectively. Deloitte, as a leading human capital consultancy and Workday alliance collaborator, can help HR organizations to purposefully redesign roles, workflows, and decision-making to support human-AI collaboration. More specifically, Deloitte offers road-mapping sessions, maturity assessments, and customized labs to optimize the experience and performance of the humans in the system so they can perform high-value activities that machines cannot replicate, like spending more time with stakeholders, developing talent, making decisions, providing oversight, and building relationships. Deloitte can also help leaders address important matters of psychological safety and human agency through its Trustworthy AITM framework, which spans seven dimensions: transparency, fairness, robustness, privacy, security, responsibility, and accountability.

Tipping Point #2

From cost efficiency to value creation

Sustained cost pressures, changing consumer and worker behaviors, and geopolitical shifts have pushed many organizations toward efficiency. But as that model tips, the focus should shift toward value. This means evolving functions to be fit-for-purpose, investing in innovation, and prioritizing growth through adaptability rather than simply reducing expense. At the same time, demographic shifts and disappearing workforces are making human capacity itself a scarce resource, elevating the need to invest where humans create irreplaceable value. Organizations that succeed may not be those that automate the fastest, but those that channel efficiency into reinvestment, fueling new forms of value creation and worker performance.

Have organizational functions outlived their

purpose?

Functions such as human resources, finance, information technology, legal, and procurement were originally designed for dependability, efficiency, and specialization. These days, traditional functions may be misaligned with the dynamic, multidisciplinary needs of modern organizations. Leaders recognize the need to move beyond rigid silos, but most have made only incremental changes. Options for transforming corporate functions include enhanced collaboration, solution-based teaming, and reimagination. The latter is the most complex. The first step involves separating elements that support running the business day to day from those that support growing the business. “Run the business” capabilities can then be brought together under common leadership and enabled by integrated technology and agentic AI, and “grow the business” capabilities can then be organized into solution-based teams or corporate services partners who are supported by domain specialists and augmented with AI.

Dealing with AI’s cultural debt

Many organizations are overlooking AI’s impact on human-to-human behaviors, enabling misalignment, distrust, and unaddressed norms to accumulate as “cultural debt.” With workers questioning what counts as effort, ownership, fairness, and accountability—and most organizations rarely evaluating AI’s cultural effects—trust and cohesion can erode just when they matter most. To mitigate this quiet deterioration, leaders should intentionally reinforce and evolve culture so that AI strengthens, rather than undermines, shared values and performance. This may entail designing interventions and rituals that encourage connection and trust as AI is adopted, and actively redesigning work to embed AI with a focus on both human-to-human and human-to-machine interactions. Forward-thinking companies often frame AI as a collaborative partner, even redesigning job descriptions to emphasize uniquely human skills like creativity, empathy, and complex problem-solving alongside technical agility.

Fueling new forms of value creation: Insights from the Workday perspective

As cost efficiency gives way to value creation, core functions like HR, finance, and IT should evolve to be fit for purpose. Traditional functions are increasingly too slow and siloed for today’s business demands, yet few organizations are making progress in moving beyond them. As work becomes more multidisciplinary and AI and innovation require seamless collaboration, organizations may need to deconstruct these rigid structures and reassemble capabilities around outcomes.

Workday can catalyze this shift by moving the enterprise from software that simply records work to AI that performs it. This transformation is powered by an open and connected data ecosystem where Sana agents act on information across the entire enterprise. Through Workday Data Cloud, Sana gains a bidirectional, zero-copy connection to platforms like Salesforce and Snowflake[SS1.1]. This ensures that Sana’s agentic teammates are anchored in real-time, governed data from every corner of the business— without the need for data exports or stale duplicates. By integrating capabilities like Pipedream, Workday helps empower Sana to initiate workflows and execute tasks across numerous business applications, making it the central orchestrator for cross-platform productivity.

As the intuitive front door to the enterprise, Sana is a true differentiator. It provides a frictionless conversational interface that orchestrates multi-step workflows across both internal and third-party systems. By acting as the central brain, Sana orchestrates complex cycles—such as always-on recruiting where Sana sources talent, manages global scheduling, and generates offer letters. Crucially, these actions remain tightly coupled to Workday’s deterministic foundation. This provides the necessary guardrails and auditable outcomes that important work demands, ensuring AI is always grounded in security, compliance, and business context.

While these advancements are significant, multidisciplinary capabilities across HR, finance, and IT are often needed to move from cost efficiency to value creation. Deloitte is one of the few consultancies that offers end-to-end implementation and advisory services across developing AI strategies, designing technology architectures, reimagining functions, and building trust and human connection into workflows. Drawing upon these broad capabilities, Deloitte can further help leaders to quantify the value of their AI deployments based on outcomes so they can more fully understand the return on investment.

Tipping Point #3

From static plans to dynamic orchestration

The future is both here and unknown, making curiosity a core organizational capability. Staying relevant means continually reimagining how workers change, learn, and grow. And as strategy and execution merge, organizations may need to move beyond structured jobs and workers, orchestrating capacity and capabilities to meet shifting demands. This means building systems for perpetual learning, experimentation, and reinvention, where workers are not only adapting to disruption but also empowered to shape it.

Staying relevant in a world that won’t sit still

Traditional change management and training may be too slow to help organizations and workers adapt as the pace of change accelerates. Few organizations manage change effectively, and even fewer meet continuous learning needs. AI is reshaping both, helping to enable workers to learn, adapt, and apply new skills directly in the flow of work. With AI, organizations can also “contextualize” at the unit of one, localizing and hyper-personalizing their initiatives to resonate with individual needs. Organizations that build this individualized, real-time adaptability can avoid stalled transformations and disengaged talent, turning workforce growth and responsiveness into a new competitive advantage.

The orchestration advantage

Competitive advantage today increasingly depends on how organizations can steer intent into action, fluidly reconfiguring capabilities and capacity as business conditions, customer demand, or technologies shift. Scale still matters, but the edge is tilting toward speed and agility. In fact, the ability to dynamically orchestrate work ranks with 88% of leaders saying it is extremely or very important to accelerate how people, skills, and resources are orchestrated to get work done. Yet, only 7% say they are making great progress toward this goal (figure 1). Achieving this “orchestration advantage” often requires four important actions:

1) identify and create capability and capacity;

2) place the right decisions with the right people at the right time;

3) create plug and play modularity; and

4) use AI to help orchestrate capability and capacity.

View The Orchestration Graph in larger size

Enabling orchestration at speed: Insights from the Workday perspective

AI is accelerating how work happens, and the advantage is shifting from allocating talent in static structures to real-time orchestration of a hybrid workforce. Speed and scale are becoming central considerations, yet many organizations are still determining how best to respond. Organizations are exploring ways to continuously reconfigure capabilities around outcomes with the aim of improving financial performance and create meaningful work, turning volatility into opportunity. But for many, the question remains: How can we orchestrate capacity and capability at speed?

Workday is built for this challenge, providing the platform to build, orchestrate, and run AI alongside human talent. By unifying workforce planning and advanced analytics on a single platform, Workday helps enable leaders to move beyond siloed data to a state of continuous readiness. This integrated approach enables organizations to surface deep insights into skills gaps and performance trends, modeling virtually unlimited scenarios to help ensure they are allocating the right capacity, human and agentic, at the right time.

As the definition of workforce expands, Workday’s Agent System of Record (ASOR) provides the essential governance for a joint human-agent workforce. ASOR gives organizations a single, transparent view to manage the life cycle, costs, and performance of AI agents, whether they are Workday-native agents for recruiting and payroll or third-party agents like Zora AI™ by Deloitte. This helps ensure that as orchestration scales, it remains grounded in Workday’s deterministic foundation, providing the visibility and control needed to lead with confidence in an AI-powered world.

As a leader in both human capital management and digital transformation, Deloitte offers organizations the process, governance, and change-management know-how needed to orchestrate humans and AI agents responsibly as well as dynamically. Through its multidisciplinary capabilities across finance, HR, risk and compliance, and cybersecurity, Deloitte can assist organizations in evaluating their AI readiness, to help ensure human and machine accountability, and turning change management into “changefulness”—the capacity to “cultivate workers’ abilities to adapt, experiment, learn, and evolve as a daily muscle embedded in work, not as a disruption.

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