Strategic Roadmap · 2025 – 2028
AI for PIM Project Preparation
A phased strategy for embedding AI across all 8 elements of the public investment project cycle — augmenting human judgement, strengthening appraisal quality, and building institutional capacity in government budget agencies.
“Every public infrastructure investment decision backed by the best available evidence, analysis and guidance — delivered at the speed government needs.”
The Strategic Opportunity
Implementation Roadmap
Three-Phase Approach
From pilot validation through scale-up to full institutional embedding.
Phase I
Foundation & Pilot
2025 Q2 – 2026 Q1
- Validate AI coach core capabilities with 3–5 government pilot agencies
- Focus on Project Appraisal & Guidance elements
- Feasibility study quality checker & CBA/CEA methodology guide
- Ethics & AI policy framework published
- Field guide for budget officials (v1)
Phase II
Scale & Integrate
2026 Q2 – 2027 Q2
- Extend to Selection, Review, and Implementation elements
- API integrations with national PIMS platforms
- Agentic appraisal workflow automation
- Climate-informed investment screening
- Certified PIM.ai Practitioner programme
Phase III
Institutionalise & Expand
2027 Q3 – 2028 Q4
- Full 8-element PIM cycle coverage
- Regional/multilateral institution partnerships
- Ex-post evaluation & lessons capture
- Open-source knowledge commons
- South-South learning network with 1,000+ practitioners
AI Applications
Across the 8 PIM Project Cycle Elements
Each element of the public investment management cycle is enhanced with targeted AI capabilities, phased across the strategic roadmap.
Guidance
AI knowledge base synthesising IMF PIMA, Green Book, World Bank PCR and national policies into context-aware guidance for project teams.
Phase IProject Appraisal
Automated CBA/CEA scaffolding, shadow price lookups, feasibility study completeness checks, and climate-adjusted economic analysis.
Phase IIndependent Review
AI-assisted quality assurance checklists, optimism bias detection, methodology compliance scoring against international standards.
Phase IISelection
Portfolio ranking using weighted MCA + CBA, fiscal space modelling, strategic alignment scoring, and pipeline prioritisation dashboards.
Phase IIImplementation
Progress monitoring against baselines, early warning alerts for cost overruns and schedule slippage, disbursement pattern analysis.
Phase IIAdjustment
Scenario modelling for project redesign options, re-appraisal automation when scope changes exceed thresholds, risk-adjusted cost projections.
Phase IIIOperation
Asset lifecycle cost optimisation, preventive maintenance scheduling, performance benchmarking against design-stage projections.
Phase IIIEvaluation
Counterfactual impact evaluation, predicted vs. actual benefit tracking, institutional lessons extraction and feedback into future project guidance.
Phase IIISuccess Metrics by 2028
Guiding Principles
Design Philosophy
Human Authority, AI Augmentation
Every AI output is an input to human decision-making, never a replacement. Budget officials retain full authority.
Multi-Tier Knowledge Architecture
Integrates international good practice (IMF, World Bank, OECD), national policy frameworks, and project-specific data.
Progressive Complexity Scaling
Simple tools for simple projects; sophisticated analytics for complex mega-projects. Adapts depth to project risk and scale.
Climate-Integrated by Default
Climate risk and transition considerations embedded throughout. Every appraisal includes climate scenario analysis.
Sovereign Capacity, Not Dependence
Build lasting government capability — training officials, transferring knowledge, and strengthening institutions.
Transparent & Auditable by Design
Every recommendation includes its reasoning chain. Every data source is cited. Every assumption is visible and challengeable.
Governance
Governance & Risk Management
AI Risk Classification
Inspired by EU AI Act risk tiers
- →Low risk: Guidance queries, information retrieval, standards lookup — AI responds autonomously
- →Medium risk: Appraisal scaffolding, template population, indicator calculation — AI drafts, official reviews
- →High risk: Project ranking, portfolio selection recommendations — AI provides analysis, committee decides
- →Critical: Final investment approval, budget appropriation — humans only, AI provides supporting evidence
Institutional Safeguards
- →Independent AI Ethics & Quality Board with external members
- →Annual transparency report covering AI decision volumes, override rates, and quality outcomes
- →Mandatory human-in-the-loop checkpoints aligned to PIMA gate review stages
- →Full audit trail for every AI-assisted analysis stored for 10 years
- →Bias monitoring across sectors, project sizes, and country income groups
- →Right-to-explanation: any official can request plain-language rationale