PAKISTAN AI & FUTURES READINESS INDEX (PAFRI) 2027
Study Protocol v0.1 — 26 September 2026

STATUS
Instrument development. No national benchmark results have been collected or published yet.
National fieldwork will begin only after expert review, cognitive testing, pilot validation and ethics approval.

PURPOSE
PAFRI is designed to measure readiness for an AI-shaped future without reducing readiness to AI tool use.

PRIMARY POPULATION
Pakistani higher education.

TWO PRIMARY INDICES
1. People Readiness Index (PRI)
   - AI Literacy & Critical Evaluation
   - Responsible AI Judgement & Human Agency
   - Learning Agility & Human Capabilities
   - Futures Literacy & Foresight

2. Institutional Readiness Index (IRI)
   - Governance & Accountability
   - Curriculum & Capability Development
   - Inclusion, Access & Infrastructure
   - Anticipatory Strategy & Experimentation

APPLIED JUDGEMENT
Four short scenarios are scored separately during the pilot. They will not be merged into PRI until validation supports doing so.

VALIDATION PLAN
- Expert review: 10–15 experts
- Cognitive interviews: 15–20 participants
- Pilot: 250–400 respondents across 6–8 HEIs
- National target: at least 2,000 respondents across 40+ HEC-recognized institutions/campuses, subject to access and final sampling calculations
- Ethics approval and preregistration before national fieldwork

SCORING
Each four-item domain uses a five-point agreement scale. Valid domain means are transformed to 0–100:
Domain score = ((mean - 1) / 4) * 100

PRI = equal-weighted mean of four People domains.
IRI = equal-weighted mean of four Institutional domains.
A single combined national PAFRI score will not be used in Version 1 unless validation supports it.

REPORTING PRINCIPLES
- No public university league table in Version 1
- Institution-specific results confidential unless the institution opts in
- Report sample composition and uncertainty next to comparisons
- Do not call self-reported tool use "competence"
- Report Don't-know rates separately for institutional items
- Publish item wording, scoring rules, limitations and revision history

CONCEPTUAL REFERENCES
UNESCO AI Competency Framework for Students:
https://www.unesco.org/en/articles/ai-competency-framework-students

UNESCO AI Competency Framework for Teachers:
https://unesdoc.unesco.org/ark:/48223/pf0000391104

OECD / European Commission (2026), Empowering Learners for the Age of AI:
https://doi.org/10.1787/65cd27d4-en

NIST AI RMF 1.0:
https://doi.org/10.6028/NIST.AI.100-1

NIST Generative AI Profile:
https://doi.org/10.6028/NIST.AI.600-1

UNESCO Futures Literacy resources:
https://www.unesco.org/en/futures-literacy/resources

World Economic Forum, Future of Jobs Report 2025:
https://www.weforum.org/publications/the-future-of-jobs-report-2025/

LEAD
Dr. Salman Ahmed Khatani
Fiker Futures Academy
https://fikerfuturesacademy.lovable.app/dr-salman-khatani

CANONICAL PROTOCOL PAGE
https://fikerfuturesacademy.lovable.app/pakistan-ai-futures-readiness-index-2027