LAHORE: The rapid rise of artificial intelligence has exposed a widening skill gap in the developed world. The US, Europe and even parts of East Asia face acute shortages of AI engineers, data scientists and machine learning researchers.
This shortage is already reshaping global labour markets — and for countries like Pakistan, it presents a familiar but more complex dilemma: will AI trigger another wave of brain drain, or can it become a pathway for domestic economic transformation? The core constraint is not intelligence or aptitude. It is the absence of an ecosystem that can absorb, challenge and reward high-level AI work within Pakistan.
For Pakistan to move ahead in AI, the first shift must be conceptual. AI cannot be treated merely as an extension of IT exports or software services. True AI capability rests on data ownership, model development and deep integration with local economic sectors such as agriculture, health, logistics, energy and finance. Without this, Pakistani professionals will remain subcontractors rather than creators of high-value intellectual property.
Unlike earlier episodes of migration involving doctors or engineers, AI-driven brain drain does not always involve physical relocation. Today, much of the drain is digital. Pakistani AI professionals increasingly work remotely for foreign firms, contribute to products owned abroad, and pay taxes elsewhere. The country retains the cost of education, while the economic value is captured overseas. If left unaddressed, AI could repeat Pakistan’s long-standing pattern of exporting talent without retaining wealth.
Yet the narrative that Pakistan lacks AI capability is inaccurate. The country does possess strong human capital — though not at the scale or depth required to lead. A small but credible group of elite researchers, trained at top global universities, work in frontier labs in North America, Europe and East Asia. Many Pakistani-origin researchers contribute to advances in computer vision, natural language processing and applied machine learning. Their success, however, largely benefits foreign ecosystems.
At home, a growing pool of applied AI engineers has emerged from institutions such as LUMS, NUST, FAST, GIKI and PIEAS. These graduates are competitive in machine learning engineering, data pipelines and model fine-tuning. They are active in freelancing platforms, remote employment and regional tech markets. Alongside them is a much larger ‘certificate economy’ workforce — individuals trained through short courses and bootcamps, familiar with tools but lacking strong theoretical grounding. This segment is ironically most vulnerable to being displaced by AI itself.
The state has a crucial role to play. Globally, no country has scaled AI without the public sector acting as an anchor client. Pakistan’s government sits on vast datasets and complex problems ideally suited for AI deployment: tax evasion detection, customs risk profiling, power theft analytics, land record digitisation, judicial backlog management and rural health diagnostics. Strategic use of AI in these areas would generate local demand, provide real-world datasets and create meaningful career paths that retain talent.
Engaging the diaspora is another underutilised lever. Pakistan should abandon the unrealistic expectation that top AI researchers will permanently return home. Instead, it should institutionalise remote engagement through adjunct professorships, joint labs, shared intellectual property frameworks and venture co-investment
AI value lies in fine-tuning, application-layer innovation and domain-specific intelligence — areas that are human-skill intensive rather than infrastructure-heavy. However, this balance shifts over time. At scale, Pakistan’s weaknesses in affordable compute, national datasets, data governance and secure cloud access become binding constraints. Without infrastructure, the country cannot own models, protect data sovereignty or capture long-term economic rents. Skill ignites progress, but infrastructure sustains it.
The deeper risk is that Pakistan may miss yet another technological window. It failed to industrialise at scale, integrate into electronics value chains, or lead in the platform economy. AI is different. Entry barriers are lower, geography matters less and global labour arbitrage favours countries with large, young, technical populations. But the window is narrow.
