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AI could eliminate some tasks and reshape some jobs in Pakistan, while helping other workers become more productive—but available evidence does not establish how many Pakistani jobs it will displace or create. A panel at LUMS discussed both risks and opportunities. Its disagreement reflects a broader distinction: exposure to AI is not the same as employers adopting it, replacing workers, or generating new economic value.
What did the LUMS panel say about AI and jobs?
The session, “AI & the Human Condition,” took place at the 13th Asian Management Research Conference (AMRC 2026), organized by LUMS’s Suleman Dawood School of Business. TechJuice reports that Dr Muhammad Adeel Zaffar, dean of the school, chaired the session. Panelists named in the report were Aamer Ejaz of JazzWorld, Ali Farid of the Securities and Exchange Commission of Pakistan, Asif Akram of Systems Limited, and Dr Maurizio Sobrero of UAE University. TechJuice’s event report
The job-displacement concern
The report attributes a warning about replacement of particular roles to Ali Farid, identified as an SECP commissioner. It says he pointed to financial research and automated negotiations and urged academic institutions to teach emotional resilience. The article does not provide a transcript, identify the underlying studies, or quantify Pakistani job losses, so this is a reported panel position rather than a measurement of what is happening across the country. TechJuice’s event report
The job-reshaping argument
Asif Akram, identified as Systems Limited’s COO, emphasized company investment in reskilling and process redesign, according to the report. That view allows for AI to change how work is done without assuming that every exposed role disappears: employees may take on different tasks, work alongside AI tools, or move into roles created by organizational change. The report does not measure the results of such changes in Pakistan. TechJuice’s event report
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Why AI exposure does not equal job loss
“Exposure” describes whether tasks in an occupation overlap with what AI systems might be able to do. It does not establish that a business has adopted the technology, that it can perform those tasks reliably in a real workplace, or that an employer will eliminate a position. Adoption may instead change a worker’s task mix or raise output per worker. Whether that creates new work or reduces headcount depends on how employers reorganize work, the skills available, and whether demand grows enough to absorb productivity gains.
The International Labour Organization’s 2025 research brief, Generative AI and jobs: A 2025 update, estimates that one in four workers globally is in an occupation with some degree of generative-AI exposure. It says that, because human input remains necessary, transformation is the likelier outcome for most jobs than redundancy. This is a global estimate of occupational exposure—not an observed job-loss rate for Pakistan. ILO research brief
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What labor-market estimates can—and cannot—tell us
Available figures provide context, but they describe different populations and measures. None is a Pakistan-specific forecast of net employment.
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| Measure | Reported figure | What it means |
|---|---|---|
| AI-related job postings in South Asia | Lightcast’s share rose from 2.9% to 6.5% between January 2023 and March 2025; demand for AI skills grew 75% faster than demand in other postings over that period. | A change in a particular slice of hiring, not a count of jobs created or a Pakistan-only trend. The World Bank cautions that postings disproportionately reflect high-wage, urban, white-collar positions. World Bank, South Asia discussion |
| Jobs potentially at risk of generative-AI automation by income group | 4.5% in low- and middle-income countries, compared with 14.2% in high-income countries. | Broad income-group estimates, not rates for Pakistan and not predictions of net employment. World Bank, World Development Report launch announcement |
| Jobs in developing economies with potential productivity gains | 16.2% could see productivity meaningfully boosted by AI. | A potential productivity effect, not proof of realized gains, job creation, or a Pakistan-specific outcome. World Bank, World Development Report launch announcement |
The World Bank’s figures distinguish automation risk from possible productivity gains; the two can coexist. A role may include automatable tasks and still benefit from AI assistance, while higher productivity may or may not translate into more hiring. The ILO’s global exposure estimate makes a related point: task overlap is a reason to examine work, not evidence that a particular job has already vanished.
Could AI become an economic engine for Pakistan?
The opportunity depends on more than access to AI tools. Businesses need to integrate them into useful processes, workers need a chance to gain relevant skills, and the economy needs ways to turn productivity into broader value—such as new services, firms, or exports. The LUMS report describes panelists arguing for these conditions, but it does not quantify the gains Pakistan would receive from them.
Skills and workplace change
According to TechJuice, Akram called for businesses to invest in reskilling and process redesign. Aamer Ejaz emphasized mathematics, science, and coding as foundational skills, as well as teaching students to ask the “right questions.” These are recommendations reported from the discussion, not measured findings about which training programs work best or how many workers need them. TechJuice’s event report
Building locally developed solutions
The report attributes to Yasser Bashir an argument that Pakistan should move beyond acting primarily as a service provider and develop indigenous AI solutions through investment in research, startups, and university-industry collaboration. That is a proposed economic direction, not evidence that those investments will automatically produce jobs or exports. Results would depend on implementation, demand, infrastructure, and the ability of local firms and researchers to turn ideas into products and services. TechJuice’s event report
What determines whether workers benefit or lose out?
The competing “job killer” and “economic engine” descriptions each capture a possible outcome, but neither follows from exposure alone. The practical result will vary across workplaces and workers. Key factors include:
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- Tasks within a job: AI may handle a subset of tasks while leaving work that requires judgment, accountability, communication, or physical presence to people.
- Adoption and redesign: Employers decide whether to use AI and whether to redesign roles, retrain staff, expand output, or reduce staffing.
- Access to tools and training: Unequal access to connectivity, suitable systems, and time to learn can determine who captures productivity gains.
- Demand for what workers produce: Efficiency can support business growth when customers want more, but increased output per worker does not by itself guarantee more jobs.
- Institutions and governance: Rules, liability, and professional standards matter when errors can harm people or undermine trust.
What did the panel raise about AI governance?
TechJuice reports that panelists discussed ethical frameworks, liability systems, and professional certifications for high-stakes uses, including healthcare, law, and autonomous mobility. Those topics point to questions about who is responsible when an AI-assisted decision causes harm and what qualifications or safeguards should apply. The event report does not establish that a particular Pakistani governance framework or certification regime has been adopted. TechJuice’s event report
What can we conclude about AI jobs in Pakistan?
The LUMS discussion is evidence of a live debate, not a representative survey or national employment study. The available figures do not establish a Pakistan-specific measured rate of AI-driven displacement, a count of AI-exposed Pakistani roles, or a causal estimate of AI’s effect on national productivity or exports. The most defensible conclusion is conditional: AI can automate tasks and alter occupations, while complementing workers and increasing productivity elsewhere. How those effects balance depends on adoption, workplace design, skills, access, demand, and institutions.
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