Artificial Intelligence (AI) is rapidly reshaping global economies and industries. In Pakistan, the promise of AI is huge — yet adoption is still uneven, divided between enthusiasm and structural bottlenecks. In this article, we map where Pakistan truly stands: how much AI use is real today, where hype leads the narrative, and what must happen to bridge the gap.
Contents
The Promise & the Projections
- According to Invest2Innovate, Pakistan’s AI market is projected to reach USD 949.17 million in 2025, growing at about a 27.76% compound annual growth rate.
- Similarly, digital transformation enabled by AI is expected to generate roughly PKR 9.7 trillion (≈ USD 34.9 billion) in economic value by 2030.
- Pakistan’s National AI Policy 2025, recently approved by the federal cabinet, aims to transform the country into a knowledge economy, with goals like training 1 million AI professionals by 2030, establishing Centers of Excellence, and ensuring broad public awareness.
- The policy also envisions that by 2030, AI adoption could boost GDP growth by up to 12% and create 3.5 million new jobs.
These projections reflect high hopes — but the question is: how much of this is grounded in measurable current adoption?
What the Data Tells Us: Reality Check
Awareness & Usage
- In a survey by Public First / Seizing Pakistan’s AI Opportunity, 84% of online adults in Pakistan said they use an AI tool at least weekly at work.
- The same survey found that 54% of respondents expressed optimism about AI’s potential for the country, while 61% believed it would have a positive effect on their own lives.
- In the realm of generative AI, an Ipsos CATI survey (1,000 internet users) captured data on knowledge, perceptions, and usage of Gen-AI across the country.
Sectoral Adoption & Readiness
- In healthcare, researchers found a moderate positive attitude toward AI among Pakistani practitioners, though only 41.5% agreed with statements indicating readiness to integrate AI into daily practice.
- Another study on healthcare practitioners concludes there’s a “crucial knowledge gap and poor AI adoption” in the sector, aggravated by limited training and infrastructure constraints.
- Academic research (Farhat et al., 2025) conducted a structural model of AI adoption in Pakistan, surveying participants across demographic groups; it uncovered that user familiarity, perceived usefulness, and satisfaction are significant predictors of AI adoption.
- In the environmental domain, a recent AI project mapped ~11,000 brick kilns in the Indo-Gangetic region (Pakistan’s area included) by combining satellite imagery with AI techniques, showing that Pakistan is leveraging AI in environmental monitoring and policy support.
Structural Moves
- In May 2025, Pakistan’s Finance Ministry allocated 2,000 MW of electricity toward AI data centers and related initiatives, indicating strategic infrastructure support for growth.
- The federal AI policy framework includes six strategic pillars: AI innovation fund (NAIF), educational/training targets, regulatory sandboxes, sectoral adoption roadmaps, compute infrastructure, and global cooperation.
- The plan also sets ambitious public awareness targets: for example, reaching 90% public awareness of AI by 2026.
Where the Hype Outpaces Reality: Gaps & Risks
| Area | Hype / Promise | Current Reality / Constraints |
|---|---|---|
| Wide Adoption Across Industries | AI will transform manufacturing, retail, agriculture, governance fast | Outside sectors like IT and fintech, adoption is still low. Many firms lack capacity or awareness. |
| Job Displacement | AI will replace large swathes of jobs | Most surveys suggest < 2% of workers are at risk of full displacement. AI is seen more as augmentation than replacement. |
| Uniform Skills Readiness | Workforce will be AI-ready soon | Many industries, especially in healthcare, report limited readiness and a gap in training. |
| Ethics & Trust | AI systems will operate transparently and fairly | Regulatory frameworks are nascent; concerns over data privacy, misuse, algorithmic biases are real. |
| Local Innovation | Pakistan will build its own AI models and products | Currently much dependence exists on imported models, foreign cloud services, and basic AI tools. The ecosystem for deep AI R&D is still nascent. |
Bridging the Gap: What Must Happen Next
- Focus on Pilots & Use-Cases
Show AI’s value via targeted projects in health, agriculture, urban planning, local governance. This builds trust, data, and momentum. - Scale Human Capital & Training
Meeting the policy target of training 1 million AI professionals by 2030 is essential. But quality, accessibility, and specialization matter too. - Strengthen Infrastructure
Reliable compute, local data centers, high-speed connectivity, power supply — all must keep pace with AI growth. - Institutional & Regulatory Foundations
Ethical AI frameworks, data protection laws, transparent oversight, and regulatory sandboxes must be more than theoretical goals. - Promote Local Innovation & AI Sovereignty
Incentivize domestic development of AI models, open source contributions, and public procurement of local solutions. An industrial policy lens may help. - Raise Awareness & Build Public Trust
Public campaigns, transparency in AI deployments (especially in government), and address concerns (bias, misuse) are crucial for adoption.
