Pakistan has approved its first national artificial-intelligence policy. The Federal Cabinet approved the National Artificial Intelligence Policy 2025, according to the Ministry of IT and Telecommunication; Associated Press of Pakistan (APP) reported the Cabinet endorsement in September 2025. The approval is a real policy commitment, but it is not proof that Pakistan has already built a globally competitive AI industry or funded every programme described in the document.
The policy is a roadmap for skills, research, startups, computing infrastructure, public-sector adoption and safeguards. Its success will depend on budgets, accountable institutions, provincial coordination and measurable results.
What Pakistan actually approved
The approved document is the National Artificial Intelligence Policy 2025, administered through the Ministry of IT and Telecommunication. The ministry’s policy listing is dated July 31, 2025, while APP says the Cabinet endorsed it in September 2025. The listing date should not automatically be treated as the Cabinet-approval date.
Official sources describe a national policy framework, not a standalone AI statute. A Cabinet-approved policy, a budget allocation, an operating fund, a regulation and a completed project are different things. The approval sets objectives and proposed mechanisms; it does not by itself show that every centre, scholarship, internship, fund or compute facility is operational.
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See the Ministry approval announcement, the National AI Policy PDF and the APP report.
Why the government sees AI as an economic strategy
The government’s theory of change is that investment in education, research, infrastructure and startup finance can help Pakistani firms move beyond low-cost outsourcing toward AI-enabled products, services and higher-value exports. It also presents AI as a way to improve productivity, modernise agriculture, education, health and government, and strengthen technological and economic sovereignty.
Those are intended outcomes, not verified results. Jobs, exports and investment will depend on whether trained people can access reliable computing, employers can find usable skills, startups can obtain capital and customers, and public agencies can deploy systems safely.
The policy’s six pillars
1. AI innovation ecosystem
The policy proposes a National AI Fund, venture and innovation funding, research support and AI Centres of Excellence in seven major cities. It also seeks commercialisation of locally developed products and services.
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The practical test is administrative: which body controls the money, whether support is a grant, loan or equity investment, who is eligible, how projects are selected and how spending is audited. Until capitalization and operating rules are published, the National AI Fund is best described as a proposed policy-backed mechanism.
2. Awareness and readiness
The ministry summary sets targets of 200,000 people trained annually, 3,000 scholarships and 20,000 paid internships, alongside broader AI literacy for marginalised groups. These are policy targets, not completed achievements.
Useful reporting should identify the delivery institutions, curriculum and assessment standards, geographic distribution, accessibility for women and people with disabilities, and whether certificates lead to internships or employment.
3. Secure AI ecosystem
The policy calls for regulatory sandboxes, cybersecurity protocols, transparency frameworks, ethical safeguards and data-protection measures. The document presents these as planned governance tools; it does not establish that a complete, enforceable AI-regulation regime is already operating.
Any future system that affects benefits, credit, health, education, employment or policing will need clear human accountability, security testing, disclosure and an appeals route for people harmed by an automated decision.
4. Transformation and evolution
Priority sectors include education, health, agriculture and governance, with workforce upskilling, sector-specific roadmaps and performance evaluation. Potential applications include crop forecasting, medical triage, tax administration, Urdu-language public services, tutoring and fraud detection.
Deployment also creates risks: inaccurate automated decisions, exclusion of people without reliable digital records, surveillance and weak grievance procedures. Sector pilots should therefore publish accuracy, error, inclusion and cost results rather than relying on adoption numbers alone.
5. AI infrastructure
The policy identifies a national compute grid, centralised datasets, AI hubs, cloud resources and expanded data-centre capacity. A “national compute grid” in the policy is not evidence that one has already been built.
Implementation must answer how many GPUs will be available, where they will be located, who pays for electricity, cooling, maintenance and upgrades, and whether researchers and startups receive subsidised access. Pakistan must also decide how much capacity to own, lease from foreign clouds or operate through a hybrid model. Data residency, connectivity, procurement and protection of health or government data are central issues.
6. International partnerships and collaborations
The policy seeks joint research, cross-border projects, global-standard alignment, expertise, investment and technology access. Partnerships can accelerate capability, but reliance on foreign cloud providers, model developers, semiconductor supply chains and proprietary platforms can also create strategic dependency.
The headline numbers—and what they do not prove
| Announcement or target | What is established | Qualification |
|---|---|---|
| 200,000 people trained annually | Target in the ministry’s policy summary | Does not show completion, competency or employment |
| 3,000 scholarships | Target in the policy summary | Selection rules, timing and funding need publication |
| 20,000 paid internships | Target in the policy summary | Placement, employer participation and outcomes remain to be reported |
| Seven AI Centres of Excellence | Proposed under the innovation pillar | Do not assume locations or operating budgets without an implementation notice |
| One million people trained | Separate programme announced during Indus AI Week 2026 for non-IT professionals or young people | Do not add it to the 200,000 annual target without an official explanation of the relationship |
| $1 billion by 2030 | Investment commitment announced by Prime Minister Shehbaz Sharif in February 2026 | Its split between public money, private investment, loans or expected activity, plus the disbursement schedule, is not established here |
| 1,000 fully funded AI PhD scholarships by 2030 | Separate February 2026 announcement | Implementation agency and annual intake require confirmation |
The one-million training programme, the investment figure and the PhD announcement come from later statements, not automatically from the 2025 policy itself. Relevant announcements are available from Pakistan’s Ministry of Information and Broadcasting and APP.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What implementation must settle
Governance and accountability
- Which ministry or agency controls the policy budget and reports progress?
- How will federal and provincial governments coordinate on education, health and agriculture?
- Who can audit high-risk AI systems and impose sanctions?
- Will there be a public register of funded projects, milestones and results?
- What appeals process will protect people affected by automated decisions?
The Islamabad AI Declaration and the Pakistan Digital Authority’s coverage indicate a later move toward structured, sovereign and responsible AI governance. They should not be assumed to replace or amend the 2025 policy without a formal instrument.
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Funding
Readers should distinguish capitalised funds from announced funds awaiting rules, direct public expenditure, private investment expected to be attracted and in-kind support such as cloud credits or university facilities. The $1 billion figure is politically significant, but a credible investment plan requires fiscal-year allocations, sources, eligible projects, implementing agencies and disbursement data.
Skills and employment
AI literacy, professional engineering, data science, product management, domain expertise, research and entrepreneurship are different capabilities. Large enrolment numbers will not automatically produce high-value jobs. Results depend on instructor quality, mathematics and English preparation, computing access, employer demand, credible certification, internships and follow-on capital.
APP reported that about 300,000 young Pakistanis were already being trained in AI fundamentals through existing programmes as of February 2026. That is a government-reported training figure, not independent evidence of competency or employment.
Compute and data
Implementation should publish GPU capacity, access rules, uptime, energy and maintenance costs, dataset licensing, privacy controls and whether Pakistani institutions can train models or mainly consume foreign application-programming interfaces. These details will determine whether the strategy supports locally relevant systems, including Urdu and other Pakistani languages.
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Benefits and trade-offs
Potential gains
- More access to AI education, research funding and startup support.
- Productivity improvements in agriculture, health, education and government.
- More sophisticated IT exports and locally relevant language tools.
- Broader participation by women, marginalised communities and non-IT workers.
Risks to monitor
- Training certificates that do not translate into jobs.
- Centres of Excellence without sustained research budgets or compute.
- Fragmented government data and unsafe public-sector procurement.
- Imported models that perform poorly in local languages or contexts.
- Privacy violations, bias, cyberattacks and opaque automated decisions.
- Concentration of resources in major cities and dependence on foreign platforms.
- Routine clerical, customer-service, translation or coding work changing faster than reskilling programmes.
What readers should watch next
- A published implementation roadmap with responsible agencies and dates.
- Budget documents showing actual allocations and National AI Fund capitalization.
- Locations, governance and operating status of the seven Centres of Excellence.
- Transparent scholarship, internship and training application procedures.
- Rules for researcher and startup access to national or subsidised compute.
- Sector-specific roadmaps and evidence from public-service pilots.
- Independent audits, impact reports and provincial coordination arrangements.
Bottom line
Pakistan has made a genuine national policy commitment by approving the National AI Policy 2025. The promised innovation, jobs and technology growth remain objectives, not established outcomes. The decisive evidence will be visible in funded institutions, usable compute, high-quality training, transparent procurement, enforceable safeguards and independently measured results.
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