From displacement to hybridization: artificial intelligence and the redistribution of jobs in the digital economy

AI and Job Redistribution: Between Displacement and Hybridization

Artificial intelligence is driving a profound transformation in global labor markets—one that is not limited to “stealing” jobs or “creating” others, but rather redistributing and reshaping them according to a new logic: hybridization between human and machine capabilities. This article, based on the latest reports from the International Labour Organization and the World Economic Forum, reviews the various dimensions of job redistribution resulting from AI—from its sectoral and gender impacts to geographic and skills gaps—while analyzing the deep paradox between the displacement of routine tasks and the creation of new opportunities requiring higher skills.

First: Between Displacement and Integration — The Net Jobs Balance

Contrary to pessimistic narratives portraying an “end of work,” accumulated data point to a more complex and balanced picture.

1. Global Figures: Net Gains

The Future of Jobs Report 2025, issued by the World Economic Forum, projects that technological transformations this decade will create 170 million new jobs against the displacement of 92 million jobs, yielding a net gain of 78 million jobs globally. This means the overall impact is not negative but positive in terms of job numbers—though the qualitative transformation is what raises concern.

In the Arab region, International Labour Organization (ILO) estimates indicate that about 14.6% of jobs (nearly 8 million) could benefit from AI augmentation, where technology enhances rather than replaces human work, while only 2.2% (about 1.2 million jobs) face the risk of full automation. AI integration in the region is expected to deliver an economic return of $14.1 billion in GDP by 2035, with a net creation of 118,000 additional jobs.

2. The Dual Effect: When the Two Trends Conflict

An academic study covering 36 OECD countries between 2005 and 2022 reveals a fundamental paradox: while AI enhances the digital economy’s overall effect on employment, its direct effect on jobs is negative (due to displacement), whereas the direct effect of technological innovation is positive (due to new job creation). This means AI redistributes jobs—eliminating some and creating others—while broader innovation expands the overall job pie.

Second: Patterns of Sectoral and Skills Redistribution

AI’s effects are not distributed evenly; they are reshaping labor markets according to clear and predictable patterns.

1. Most Affected and Most Benefiting Sectors

Jobs relying on routine and repetitive tasks are particularly affected, as AI can automate them efficiently:

In ASEAN, clerical jobs face the highest levels of exposure, reaching 93.7% in the Philippines, 93.9% in Indonesia, and 64.9% in Vietnam. However, the vast majority face partial task automation rather than full displacement, meaning the nature of jobs will change rather than disappear.

2. The Higher Education Paradox: Exposure Does Not Mean Risk

Data show that workers with higher education are the most exposed to AI, not the least. This reflects that professional and administrative occupations requiring university degrees—such as data analysis, documentation, and report preparation—include tasks that AI can augment or partially automate. But high exposure here often means an opportunity for augmentation and productivity, not necessarily job loss. Specialized skills may also become “less distinctive” as smart tools enable less experienced workers to perform tasks that previously required experts, redefining the concept of “expertise.”

Third: Gender and Geographic Redistribution — Compounding Gaps

ILO analysis reveals unexpected dimensions of inequality in AI’s impact:

1. The Gender Gap: Women Between Risk and Opportunity

In the Arab region, women bear more than three times the share of jobs at risk of automation compared to men (5.3% versus 1.6%), due to their concentration in routine clerical roles. Yet the paradox is that women also benefit more from augmentation, with 22.7% of jobs held by women potentially augmented versus only 13% of men’s jobs. However, unless policies are designed to address gender gaps, women are expected to face fewer job opportunities by 2035.

In Vietnam, women face a higher level of AI exposure (24.1% versus 17.8% for men), reflecting the same pattern of unequal distribution.

2. The Geographic and Age Gap: Urban vs. Rural, Youth vs. Elderly

AI’s effects are concentrated in major urban centers and fast-growing service hubs, where digital infrastructure is more advanced and knowledge jobs are more prevalent. By contrast, older workers (over 55), rural communities, and conflict-affected regions fall behind due to reskilling and infrastructure challenges. Youth face growing pressure, with global youth unemployment at 12.4%, and AI may intensify competition for standardized high-skill roles.

Fourth: The Strategic Challenge — From “Premature De-Professionalization” to Hybridization

1. The Risk of “Premature De-Professionalization”

World Bank researchers introduced a new concept carrying a profound warning: “Premature De-Professionalization.” This concept refers to the risk that AI productivity in high-skill services sectors could shrink economies’—especially developing ones’—ability to generate well-paid jobs in these sectors. If productivity gains outpace demand expansion for these services, employment opportunities there may decline, depriving economies of a development path through high-skill services—a dangerous parallel to the “premature deindustrialization” phenomenon that many developing countries have suffered.

International trade plays a dual role: falling relative global prices for high-skill services, combined with delayed AI adoption, could cause countries to lose their competitive advantage and become trapped in low-skill, low-income specializations.

2. The “Hybridization” Model: Humans and Machines Together

The current debate goes beyond the “displacement versus creation” dichotomy to a third model: hybridization between human and machine capabilities. ILO data indicate that the vast majority of jobs will see task transformation rather than disappearance. For example, a study showed that 79% of programming interactions using AI tools involved direct automation of coding tasks, especially in front-end development, indicating a transformation in the nature of programming work rather than its disappearance.

Fifth: Conclusion and Future Outlook

AI is redistributing jobs in the digital economy according to a complex logic that goes beyond simple displacement. The key messages drawn from available evidence are:

1. The overall impact is positive in numbers: The World Economic Forum projects a net gain of 78 million jobs globally by 2030, and the ILO projects the creation of 118,000 additional jobs in the Arab region.

2. The risk is not job loss but job transformation: The biggest challenge is reskilling and upskilling the workforce to keep pace with the new nature of work.

3. Sectoral and gender gaps require targeted policies: Women, older workers, and rural workers are most at risk and least able to benefit from new opportunities unless comprehensive policies are designed to address these gaps.

4. The risk of “premature de-professionalization” is real: Developing economies must adopt proactive strategies to ensure that productivity gains in high-skill services translate into job creation rather than contraction.

The future is not about replacing humans with machines, but about redefining work itself. Companies that will succeed are those that recognize that real value lies in the integration of human and artificial intelligence, not in competition between them.

Sources and References

1. Uddin, M., Ali, A., & Siddik, A. B. (2025). Employment in the digital economy: Role of artificial intelligence and technological innovation. ScienceDirect.

2. International Telecommunication Union (ITU). (2025). The Annual AI Governance Report 2025: Steering the Future of AI.

3. International Labour Organization (ILO). (2025). Navigating the digital and artificial intelligence revolution in Arab labour markets: Trends, challenges and opportunities.

4. World Economic Forum. (2025). The Future of Jobs Report 2025.

5. Vietnam News. (2026). Digital technologies redraw jobs landscape.

6. World Economic Forum. (2026). Creating Opportunities For All In The Intelligent Age.

7. ILO. (2026). Navigating Generative AI’s transformations in ASEAN labour markets.

8. Liu, Y. (2026). Generative AI: Catalyst for Growth or Harbinger of Premature De-Professionalization? The World Economy.