This article is part of a recurring series highlighting recent talent mobility industry reports. If you would like the WERC editorial team to consider covering a specific industry report, email mobility@talenteverywhere.org.
Deloitte's 2026 Global Human Capital Trends report emphasizes that organizations are now standing at a tipping point in the way they leverage people, technology, and data to achieve competitive advantage. The report is based on a survey that included more than 3,000 business and HR leaders across 15 countries, supplemented by surveys of 6,000 workers, managers, and executives, and more than 50 executive interviews.
Deloitte found that rapid technological advancements, particularly in AI and the accelerating pace of change in markets and workforce expectations, are compressing the traditional S-curve of organizational growth. Organizations must now leap to the next curve faster, relying not only on technology but on cultivating a human advantage that technology alone cannot replicate.
From Tensions to Tipping Points: Choosing the Human Advantage
The report identifies three core tipping points shaping the future of work: speed and agility, human-AI collaboration, and cultural adaptation. About 70% of business leaders see their primary strategy over the next three years as being fast and nimble. The key drivers of success include orchestrating people and resources effectively and building workforce adaptability. Organizations that treat technology as the primary lever, without strengthening the human edge, are less likely to realize returns on AI investments.
Human and Machine Relationships
Nearly 60% of workers intentionally use AI at work, according to a recent study by the Melbourne Business School, yet only 14% of leaders said they were adept at shaping these interactions, Deloitte found.
The report stresses that AI should not simply be treated as a separate digital workforce but as a multiplier of human productivity and creativity, where the combination of human judgment and AI capability yields exponential outcomes. This approach, known as the human-AI blend, is increasingly critical as organizations evaluate workforce composition and plan human and machine collaboration strategically.
Fact or Fabrication? AI and Workforce Data
The rise of AI presents new challenges in trustworthiness and authenticity of workforce data. Organizations are increasingly questioning the reliability of information about worker skills and performance. The report found that only 5% of organizations are making great progress in addressing these issues, despite more than 60% recognizing their importance. AI-generated content, synthetic identities, and AI-assisted candidate applications can distort talent markets, creating risks of misrepresentation, poor hiring decisions, and potential malicious infiltration.
AI and Decision-Making
AI is reshaping organizational decision-making, yet oversight remains insufficient. Only 5% of organizations report leading in AI decision governance, though 64% acknowledge its importance. Challenges include unclear accountability, human disengagement from AI decisions, and ethical or regulatory complexities.
To address these, organizations must elevate decision-making as a discrete capability, intentionally designing how humans and AI interact. Strategies include defining decision rights dynamically, implementing oversight frameworks, and monitoring both AI and human outcomes.
Australian-American proprietary software company Atlassian, for example, recognized that unclear boundaries between AI-led and human-led decisions were creating bottlenecks. The company chose to treat decision rights as evolving rather than instituting strict rules. They now routinely review where AI should handle routine tasks and where humans need to step in.
IBM, meanwhile, uses dedicated ethics boards to review high-impact uses, blending policy, cross-disciplinary review, and compliance-tracking tools. Treating governance as a design system and not just a control, the company is able to scale AI while maintaining trust.
Cultural Debt and AI
The adoption of AI has created cultural debt, as workers feel less connected and trust erodes both ways between employees and leadership. Deloitte's report cites a 2025 Gallup poll that found just 1 in 5 U.S. workers feels strongly connected to their company culture, with a decline in employer trust noted in the 2025 Edelman Trust Barometer, the first drop since 2018.
Organizations are beginning to recognize culture as a strategic asset rather than a static backdrop. The report recommends mapping current cultural strengths against desired states, building trust through visible AI integration, and enhancing collaboration and innovation. Successful cultural adaptation involves preserving core elements such as purpose and belonging while evolving recognition, communication, and innovation practices.
Orchestration Advantage
Organizations need to orchestrate capabilities and capacity effectively to stay competitive. This involves four core actions: build, borrow, buy, and bot, where “bot” refers to leveraging AI and digital workers. Blending human and AI capabilities unlocks value beyond mere automation.
Examples include rehiring employees alongside AI chatbots to enhance customer service outcomes and reducing nonessential work to allow employees to focus on high-value tasks. Bridging talent across organizational boundaries and redesigning roles can further extend capacity, as illustrated by Cleveland Clinic’s task redesign to address healthcare talent shortages.
A workforce planning group at Cleveland Clinic determined whether tasks could be automated, performed remotely, reassigned, or rescheduled. The analysis led to a shift of 37 of 40 tasks to lower credentialed or non-clinical staff and automating or augmenting others with technology. This created the capacity equivalent of 430 full-time employees and generated upwards of $2 million in savings, while enabling staff to spend more time on patient care instead of paperwork.
Staying Relevant in a World That Won’t Sit Still
Continuous learning and adaptability are critical. The report advocates “changefulness”—embedding adaptability, experimentation, and learning into daily work rather than treating them as separate activities. AI enables personalization of learning, providing real-time guidance, micro-challenges, and AI-powered coaching. Organizations are implementing surround-sound systems of adaptive experiences, combining team mix optimization, peer coaching, hands-on practice, and digital learning sandboxes to ensure workers develop skills in the flow of work. This approach has been shown to increase both organizational performance and employee engagement.
Rethinking Organizational Functions
Traditional functions like HR, finance, and IT may be too siloed and slow for today’s dynamic needs. The report argues that organizations should deconstruct rigid functions and reassemble capabilities around outcomes. HR, for example, can act as a connector between technology and people, enabling cross-functional collaboration and visibility. Leadership must balance maintaining critical expertise with enabling constructive friction to ensure innovation while preserving organizational stewardship.
Mobility as a Strategic Enabler of the Human-AI Workforce
For talent mobility professionals, the implications of these trends are significant. As organizations move faster between growth curves and redesign work around human-AI collaboration, mobility will become a strategic lever rather than simply an operational function. Global mobility teams will increasingly help organizations deploy the right talent, skills, and capabilities where they are needed most—whether through international assignments, cross-border project teams, remote work arrangements, or short-term skill deployments.
In an environment where adaptability and human judgment are critical advantages, mobility programs can accelerate knowledge transfer, support cultural cohesion across distributed teams, and ensure that leadership pipelines develop global perspectives. At the same time, mobility professionals will need to work closely with HR, technology, and risk teams to address emerging challenges around workforce data integrity, AI governance, and trust.
By aligning mobility strategies with the broader orchestration of human and digital talent, mobility leaders can help organizations remain agile, resilient, and competitive in a rapidly evolving world of work.