The ESG Case for 1 Million
First AI Agents
How NAAID and NDTI, operated by Hunar-Up, turn a national skills campaign into measurable social inclusion, responsible digital delivery, and auditable governance.
Explore the reportStudents building their first AI agent (flagship target, Year 2)
Students trained in 3 validation cohorts: 200 online, 200 University of Sargodha, 200 Superior University
Target universities overall, with 35+ partners targeted in Year 1
Potential annual FX impact, optimistic ceiling. Base case is $900M
Pakistan's skills crisis, in six numbers
This is the problem NAAID exists to solve. Every alarming stat lives here — so the rest of this report can focus on the response.
Graduate unemployment, ages 20–24
IT graduates with job-ready skills
Employers dissatisfied with graduate readiness
Workers registered for overseas jobs in 2025
Hold most meaningful AI training access. 100+ university towns have none
Growth in Pakistan’s labour force, 71.8M → 85.6M (2020-21 to 2024-25)
One programme. Three pillars of accountable impact.
Skills programmes are usually judged on headcount. ESG funders ask a harder question: who was reached, what footprint did it leave, and can the results be verified. NAAID is designed to answer all three.
E · Environmental
Digital-first, low-footprint delivery
S · Social
Inclusion, livelihoods, and access beyond the big cities
G · Governance
Verifiable outcomes, formal structure, shared data
A low-footprint model, and a promise to measure it
NAAID is a digital skills programme, so its environmental case is about avoided footprint and honest accounting, not carbon claims we cannot yet back with data.
Asset-light delivery
Sessions run in the university’s own venue with its Wi-Fi and projector. Tools are cloud-based and no-code, learning is project-first on screen, and certificates are digital and QR-verified. There is no new construction, no printed course packs and no travel by students.
Train-the-Trainer reduces travel
Faculty are trained to deliver NAAID themselves, so the programme scales through local trainers rather than a central team travelling between 50+ campuses every week.
Earn without relocating
Remote AI income reduces the need for graduates to move to a metro or emigrate for work. We treat the resulting reduction in relocation and commuting as a hypothesis, and will survey alumni rather than assume it.
Responsible AI footprint
AI has its own energy cost. NAAID commits to teach efficient agent design, favour lightweight models for classroom builds, and publish an estimate of programme-level compute and venue energy use in the Year-1 report.
What we are not claiming: NAAID has not yet measured its carbon footprint or any avoided emissions. The Year-1 report will include a first estimate with its method, so funders can see the numbers and how they were built.
Impact you can verify, not just read about
Pakistan's training market is moving toward accountability, and "certificate mill" scepticism is real. NAAID's governance is built so that every headline number can be checked.
Verifiable certificates
Every certificate carries a unique code and QR, checkable by anyone at hunarup.com/verify. Employers and funders do not have to take Hunar-Up’s word for completion.
Outcome-data clause in every MOU
Partner universities and Hunar-Up mutually collect anonymised outcome data, and Hunar-Up may publish aggregate results. Each MOU runs 12 months, and batches already in progress are completed even if notice of termination is given.
Formal non-profit structure
Hunar-Up is a joint venture of PREP-Karo (Pvt) Ltd and enARtifi (Pvt) Ltd, both SECP-registered. A Section 42 company will be registered to hold NAAID, enabling grant funding and formal governance.
Independent audit
Third-party verification of student numbers and outcomes, with session NPS published quarterly. Competitors publish placement figures, so NAAID will publish audited ones.
Secure platform and student data
The new LMS uses proper authentication, role-based access (Owner, Content Manager, Operations) and a database-backed certificate record. The data-protection basis for student records will be reviewed against current Pakistani law.
Honest claims
The 1M target lands in Year 2, not Year 1. NAAID does not claim to produce 1M AI engineers: it claims exposure for 1M, and tracks how many go on to earn. Economic projections are labelled as illustrative models.
What we will report, and where we stand
| Pillar | Indicator | Today | Year-1 target (to Sep 2027) |
|---|---|---|---|
| Social | Students trained | 600+ measured (3 validation cohorts) | 500,000+ |
| Social | University partners | 2 campus cohorts (University of Sargodha, Superior University) | 35+ (228 overall target) |
| Social | Allied-department share of students | Not yet reported | >35% |
| Social | Female participation | Tracking begins Q1 | Reported; target set after baseline |
| Social | Share of students in Tier 2–3 cities | Validation cohorts in Sargodha and online | Reported; 5 cities by Q2 2027 |
| Environmental | Programme footprint estimate (venue energy, AI compute) | Not yet measured | First estimate and method published |
| Governance | Certificates verifiable by QR | Live | 100% |
| Governance | Faculty trained to deliver (TTT) | Not yet reported | 300+ |
| Governance | Session NPS | Not yet reported | ≥ +50, published quarterly |
| Governance | Section 42 entity registered | Planned | Registered |
| Governance | Independently audited outcomes | Planned | Published by Q3 2027 |
Mapped to the UN Sustainable Development Goals
Each goal below is one NAAID contributes to by design. Indicators are the ones in the scorecard above.
SDG 4 · Quality education
Free, hands-on AI skills inside university programmes, with certified faculty.
SDG 5 · Gender equality
Institutional delivery that reaches women opt-in programmes miss. Participation reported by gender.
SDG 8 · Decent work and growth
A path from first agent to freelance income to micro-agency, with dollar-earning remote work.
SDG 9 · Industry, innovation, infrastructure
NDTI is reusable digital infrastructure for delivering any new technology to campuses.
SDG 10 · Reduced inequalities
Targets the 100+ university towns outside the major cities, at no cost to students.
SDG 17 · Partnerships for the goals
Universities, PSEB, Ignite, the Ministry of IT and global tech communities working on one rollout.
Why ESG-minded capital fits NAAID
NAAID is a free programme funded by paid offerings, grants and sponsorship. The ESG structure above is what lets those funders report their own impact credibly.
Grants
Ignite (National Technology Fund) and the National AI Fund, ring-fenced under the National AI Policy 2025 for capacity building.
Development partners
UNDP, British Council and GIZ are in the targeted pipeline for skills, inclusion and gender outcomes.
Corporate CSR
Brand placement on certificates, banners and campus showcases, backed by audited reach and outcome numbers.
Funding sources above are a targeted pipeline, not confirmed commitments.
Delivering National AI Policy Targets (2026–2027)
National AI Policy 2025[10]
- Train 1 million AI professionals by 2030
- Develop 10,000 AI trainers by 2027
- Create 20,000 annual AI internships
- Establish National AI Fund (ring-fenced)
- $1 billion AI infrastructure investment
NAAID / NDTI delivers this
- 1M students = the policy's headline target
- 300+ TTT faculty by Year 1 → 10K path
- Curriculum-embedded, free to all students
- Reusable infrastructure (NDTI) for any tech
- University network as permanent national asset
Sources & Data
Every figure in this report is sourced.
- 01
Graduate unemployment at 32.8% (ages 20–24)
- 02
Only ~10% of IT graduates are employable (SBP)
- 05
~3.1 million enter labour force annually
- 06
72% of employers dissatisfied with graduate readiness
- 09
Pakistan freelance exports hit record $1.76B in FY2026
- 10
National AI Policy 2025 — 1M professionals, NAIF, $1B infrastructure
Access, inclusion, and the livelihoods path
NAAID's social response: reach students where they are, open paths to income, and keep talent earning at home.
Closing the access gap
Computer access, urban vs rural households
Digital-literacy confidence, urban vs rural students
Opt-in bootcamps tend to attract students who are already connected, already in a metro, and already confident. A curriculum-embedded model reverses that: the session comes to the campus where the student already is, in a Tier 2 or Tier 3 city, at no cost.
Women and economic participation
Of GDP forgone due to low female participation (IMF, 2016)
Average rate of Pakistani women freelancers vs $20/hr for men
Remote AI work is one of the few income paths where Pakistani women already out-earn men per hour. Saudi Arabia's SAMAI reached 52% female participation, though it was a mass AI-literacy programme (70% of participants were employees, 30% students), so it is a reference point rather than a like-for-like model. NAAID will report participation by gender from Q1 rather than assume it.
Livelihoods: from first agent to first income
The 100,000 and 1,000 figures are planning targets (10% and 1% conversion), not measured outcomes. They are the numbers the independent outcome audit is designed to test.
Keeping skilled talent at home
Of 2024 overseas workers were unskilled / skilled
Pakistan freelance exports in FY2026, a record
Most overseas employment is labour migration to the Gulf, not a graduate exodus, so NAAID does not claim to stop it. The narrower claim is that remote AI work gives a graduate a dollar-earning option at home, if payment rails, connectivity and skills are in place.