Artificial intelligence (AI) could increase productivity in 13-20% of jobs across the Middle East, North Africa, Afghanistan and Pakistan (MENAAP). However, fewer than 10% of jobs face near-term automation risks, according to the World Bank’s October 2026 Economic Update.
- Saudi Arabia and UAE lead regional AI readiness
- AI could change jobs before replacing workers
- Private-sector investment remains a major constraint
- AI skills demand extends beyond technical expertise
- Local data and Arabic-language AI need greater attention
- Clear regulation and trust will shape AI adoption
- What the World Bank’s findings mean for employers
The report, From Divide to Opportunity: AI, Jobs, and Growth, highlights the region’s potential to use AI to support economic growth and improve workplace productivity. However, it warns that these gains will depend on more than technology.
Skills development, private-sector investment, reliable digital infrastructure and effective regulation will shape how widely businesses and workers benefit. Without these foundations, AI could widen existing gaps between economies, companies and employees.
Saudi Arabia and UAE lead regional AI readiness
MENAAP economies are entering the AI transition from very different starting points. Saudi Arabia and the UAE have invested in computing capacity, data centres, digital infrastructure and AI ecosystems. Both rank among the world’s top 25 economies for AI model development and high-performance computing, according to the report.
Meanwhile, fragile and conflict-affected economies face more basic barriers. Unreliable electricity, limited broadband access and weaker institutional capacity can restrict digital adoption.
Middle-income economies, including Egypt, Jordan, Morocco, Pakistan and Tunisia, occupy a different position. They have growing pools of technical talent and national AI ambitions. However, gaps in implementation, regulation and business investment continue to constrain progress.
As a result, the region does not have a single path to AI adoption. Readiness also varies between industries, businesses and types of work within individual countries.
The World Bank identifies three structural gaps that could determine the scale of AI-driven productivity gains: localisation, usage and foundational capital. These cover the availability of relevant local data and applications, the extent to which businesses use AI productively, and the infrastructure and investment needed to support adoption.
AI could change jobs before replacing workers
The report presents a more nuanced employment outlook than the prospect of widespread job losses.
AI can help employees perform specialist tasks, improve productivity in existing roles and shift responsibilities between workers with different levels of expertise. It can also support new occupations, including large language model engineers, AI trainers and prompt specialists.
For employers, this means AI adoption could change how work is organised before it eliminates entire roles. Workers with less specialised knowledge may also be able to undertake tasks that previously required deeper technical expertise.
However, the potential benefits are not evenly distributed.
The estimated value of time saved through AI equals 1.1% of GDP in high-income Gulf economies. In upper-middle- and lower-middle-income economies, the figure stands at 0.4%.
Educated workers are also better positioned to benefit from AI-enabled productivity gains. Therefore, businesses and policymakers face a challenge: ensuring that the technology improves opportunities across the workforce rather than concentrating gains among employees who already have stronger skills and resources.
Private-sector investment remains a major constraint
National AI strategies alone will not guarantee productive adoption. Businesses must invest in technology, train employees and redesign workflows to realise its potential.
Yet the World Bank identifies weak business investment and innovation as barriers across MENAAP.
Only 16% of firms in the region introduced a new product or service during the previous three years. By comparison, the figure reached 29% in other emerging market and developing economies.
Investment in physical capital also remains lower. Only 24% of MENAAP firms invested in physical capital, against 37% among their peers outside the region. In addition, fewer than one in five firms provide formal training, compared with 30% elsewhere.
Research and process innovation show similar gaps. Only 9% of firms in MENAAP invest in research and development (R&D), compared with 11% in peer economies. Meanwhile, 9% reported introducing new or improved processes, against 19% outside the region.
These gaps matter because effective AI adoption involves more than purchasing software. Companies must integrate data, retrain employees and identify tasks where AI can deliver measurable business value.
Saudi Arabia offers an example of stronger adoption. Nearly 28% of Saudi establishments had adopted AI in 2024, compared with an OECD average of 20% in 2025.
However, adoption rates alone do not show whether businesses have reorganised tasks or achieved lasting productivity gains. Jordan illustrates this distinction. Around 24% of surveyed firms had adopted at least one AI technology, but fewer than 5% used AI for advanced applications such as decision support or automated workflows.
For business leaders, the priority is therefore to move beyond experimentation and embed AI into everyday operations.
AI skills demand extends beyond technical expertise
The region’s workforce also faces a skills challenge. AI engineers account for less than 1% of LinkedIn members across MENAAP, according to the World Bank.
However, the report suggests that employers need more than technical specialists. Communication, critical thinking and adaptability are among the skills employers identify as significant gaps.
Employees will increasingly need to assess AI-generated information, question unreliable outputs and apply technology to business problems. They will also need to adapt as AI changes existing processes and responsibilities.
Interest in AI learning is growing. Generative AI course enrolment rose sharply across several regional markets in 2025. Enrolments increased by 344% in the UAE, 194% in Qatar, 165% in Saudi Arabia and 57% in Egypt.
However, women remain underrepresented among learners. They accounted for only around one-fifth to one-quarter of generative AI course enrolments in Egypt, Qatar, Saudi Arabia and the UAE.
The findings point to two priorities for employers: expanding access to AI training and strengthening the human skills that support effective technology use. Creative thinking, problem-solving and sound judgement will remain important as employees work alongside AI systems.
Local data and Arabic-language AI need greater attention
AI systems must also reflect the languages, data and working conditions of the markets where businesses deploy them.
Arabic is spoken by more than 500 million people, yet it accounts for just 0.7% of global URLs. Persian represents 0.7%, while Urdu accounts for 0.03%, according to the report.
Although AI models are improving in Modern Standard Arabic, their performance can decline when they encounter the region’s diverse Arabic dialects.
The challenge extends beyond language. Applications in healthcare, law, labour markets and public services need relevant, reliable local data to produce useful results.
Without this context, businesses and public institutions may struggle to apply AI effectively to regional needs. Local datasets, language capabilities and sector-specific applications will therefore influence how much value organisations gain from the technology.
Clear regulation and trust will shape AI adoption
Regulation is another important factor in regional AI readiness. The World Bank identifies gaps in adaptable legal frameworks, enforcement and accountability.
Businesses also face concerns about privacy, security and bias. These issues can slow adoption when organisations lack clear rules for using AI responsibly.
The report calls for better regulatory frameworks covering data governance, data sharing, procurement, liability, cybersecurity and ethical AI use.
For employers, predictable rules can help clarify how to introduce AI, protect sensitive information and establish accountability for automated decisions. At the same time, regulation needs to support responsible innovation rather than create unnecessary barriers to adoption.
Regional cooperation could also help distribute AI capabilities more widely. Saudi Arabia and the UAE have developed stronger computing infrastructure and AI ecosystems. Other MENAAP economies can contribute technical talent, local data, sector expertise and practical applications.
Shared computing capacity, regional datasets and research partnerships could help businesses and governments access capabilities that might otherwise remain concentrated in a few markets.
What the World Bank’s findings mean for employers
The World Bank’s assessment places AI adoption within a broader development challenge. The region needs stronger education systems, better digital infrastructure and greater private-sector investment to turn technological potential into economic gains.
For employers, this means linking AI investment to workforce development and operational change. Training should help employees use AI effectively, assess its outputs and adapt to changing responsibilities.
Businesses must also address differences in access to skills and technology. Otherwise, the employees and firms best equipped to adopt AI could capture a disproportionate share of the gains.
Ultimately, MENAAP’s AI opportunity will depend on how effectively its economies translate technology into higher productivity, better jobs and wider economic participation. Developing advanced models matters, but so does building the conditions that allow businesses, workers and public institutions to use them productively.
