28 Dec How AI and Demographics Are Changing the Way Talent Moves Globally

Artificial intelligence is often framed as a productivity breakthrough—a way for organizations to do more with fewer people. At the same time, employers across advanced economies are facing a different, more immediate reality: fewer workers are entering the labor force just as large numbers of experienced employees are preparing to retire. These two developments are usually discussed separately. Increasingly, they are colliding.

Together, they are reshaping how organizations think about talent, work, and global mobility.

In a constrained labor environment, competitive advantage will belong to organizations that integrate AI, workforce planning, and global mobility into a single strategy—one designed not just to automate work, but to keep capability moving in a changing world. A new global survey from Deloitte, drawing on responses from more than 11,000 workers across 17 countries, helps explain why this integration is becoming necessary rather than optional.

Demographics are tightening the labor supply

The demographic picture is becoming harder to ignore. In the United States and much of Europe, workforce participation is under pressure as fewer people enter the labor market and more experienced workers retire. High school graduate populations are peaking and expected to decline, driven by long-term drops in birth rates. By 2030, one in six people globally will be over the age of 60.

For sectors that rely on steady labor replenishment—healthcare, construction, hospitality, manufacturing—this is not a temporary hiring challenge. It is a structural constraint. Many of these roles require physical presence, licensing, and local knowledge. They cannot be easily automated, offshored, or filled through remote work alone.

At the same time, labor-force growth is accelerating elsewhere. By 2030, roughly two-thirds of new workforce entrants are expected to come from Sub-Saharan Africa, with Africa projected to become the world’s largest labor pool by 2040. Yet this demographic growth does not automatically translate into relief for aging economies. Immigration systems, credential recognition, language requirements, and political constraints continue to limit large-scale labor mobility—especially for frontline roles.

This mismatch—between where workers are growing and where workers are needed—is now a defining feature of the global labor market.

AI changes tasks, not labor reality

This is where AI enters the picture. Research from McKinsey Global Institute offers an important clarification: AI is not eliminating work at scale, but it is changing what people do during the workday. While existing technologies could automate tasks that make up more than half of U.S. work hours, most jobs will not disappear. Instead, they will be reshaped internally.

McKinsey’s analysis shows that more than 70 percent of the skills employers value today are used in both automatable and non-automatable tasks. What changes is not the relevance of human skills, but how they are applied. As AI takes on routine activities such as information sorting, drafting, and basic coordination, workers spend more time on judgment, problem-solving, relationship-building, and decision-making.

This helps explain why AI adoption has not yet translated into widespread productivity gains. Fewer than 40 percent of companies report measurable profit impact so far, largely because many have layered new tools onto workflows designed for a different era. The value emerges only when work itself is redesigned so humans and AI operate together.

Deloitte’s survey shows that this redesign is already underway. Routine tasks are increasingly automated, while more complex responsibilities are supported by generative and agentic AI systems. By 2027, Deloitte projects that half of organizations currently using generative AI will be piloting agentic AI capable of executing multi-step workflows with limited supervision.

For global mobility, the significance is not just efficiency. AI allows organizations to operate with smaller teams, shorten learning curves, and move expertise digitally when people cannot easily move physically. In a world where labor supply and labor demand are increasingly misaligned across regions, this flexibility matters.

However, Deloitte’s findings also underscore a clear boundary. AI does not eliminate the need for human presence where work is physical, regulated, or relational. Manufacturing floors, hospitals, construction sites, and care settings remain labor-constrained despite technological advances. AI can augment these roles, but it cannot replace the people who perform them.

The entry-level challenge

One emerging risk highlighted by Deloitte is the narrowing of entry-level pathways. As AI absorbs tasks traditionally assigned to junior workers—such as note-taking, basic analysis, and scheduling—fewer roles remain that combine low risk with high learning value. A majority of respondents believe AI could reduce the availability of entry-level jobs, making it harder for new workers to gain experience.

This has direct implications for global mobility. Entry-level roles have long served as a key access point for international graduates, migrant workers, and early-career professionals building cross-border careers. If those roles shrink without being replaced by structured development pathways, organizations risk weakening future talent pipelines.

There is a potential counterbalance. Deloitte’s data shows that 61 percent of workers believe AI can support upskilling, particularly for early-career employees. Used intentionally, AI can function as a real-time coach—accelerating learning and reducing time to proficiency. McKinsey reinforces this point, noting that demand for AI fluency has surged, with job postings requiring AI skills rising nearly sevenfold in just two years.

Human oversight and knowledge transfer still matter

Despite AI’s speed advantage, both Deloitte and McKinsey find enduring trust in human judgment. Workers consistently rate human collaboration higher for quality, feedback, and core decision-making. Deloitte recommends keeping humans “on the loop”—supervising AI outputs much like managers oversee junior staff. This approach mirrors how global teams already operate across borders and time zones.

Another underappreciated risk is knowledge loss. As experienced workers retire, organizations face the erosion of tacit expertise that is difficult to document and even harder to replace. Deloitte’s survey indicates strong interest in using AI to support knowledge transfer through mentorship, skill-matching, and intelligent documentation. For global mobility, this allows expertise developed in one market to be transferred, adapted, and reused elsewhere without constant relocation.

Read together, McKinsey and Deloitte are describing the same shift from different angles. AI is changing what work looks like inside organizations. Demographics are determining where labor pressure is most acute. Global mobility is increasingly the system that must reconcile both.

AI will not solve demographic decline, nor will it replace the need for people where physical presence matters. But it can extend productive careers, accelerate learning for new entrants, and allow skills to move even when people cannot. In today’s labor-constrained environment, the organizations that succeed will be those that treat AI, workforce planning, and global mobility as one connected strategy—focused not just on automation, but on keeping capability moving as the workforce continues to change.