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Training Location & Duration

Kathmandu, Nepal: April 15 to 17, 2026
Bangkok, Thailand: April 27 to 29, 2026
Siem Reap, Cambodia: May 18 to 20, 2026

Registration Deadline

Nepal: March 20, 2026
Thailand: April 10, 2026
Cambodia: April 30, 2026

Training Language

Nepal: English
Thailand: Thai
Cambodia: English

Introduction

This training manual provides detailed guidance on integrating Artificial Intelligence (AI) into project management and Result-Based Management processes. It will equip development professionals with practical knowledge to use AI tools for project identification, planning, implementation, monitoring, evaluation, and closure.

Target Participants

– Project Managers, M&E Specialists, and Program Coordinators
– Development professionals integrating AI tools in project workflows
– PMD Pro certified professionals (Level 1 & 2) advancing to digital project management

Duration

3 Days

Training Objectives

– Understand AI fundamentals relevant to project management.
– Integrate AI tools into the PCM and RBM (Identification → Closure).
– Use AI for predictive planning, stakeholder engagement, and monitoring.
– Apply AI for risk forecasting, resource optimization, and performance analysis.
– Ethical Use of AI.

Methodology

The training uses a mix of lectures, demonstrations, and hands-on exercises.
Participants will engage with AI-driven tools to design, plan, and monitor projects effectively.
Methods include:
– Interactive lectures
– AI tool demonstrations
– Group case studies and simulations
– Hands-on exercises with real datasets
– AI-augmented project planning sessions

Training Modules

Day 1 — AI Foundations + Responsible Use + Prompting for PCM/RBM
Module 1: AI basics for program teams
– What AI/LLMs do (and don’t do): strengths, weaknesses, common failure modes
– Hallucinations, bias, confidence traps, and validation methods
– Choosing the right tool for the job (LLM vs spreadsheet vs BI)
Module 2: Responsible AI in NGO programming
– Privacy-by-design: what should never be entered into AI tools
– Handling child-related and sensitive information: anonymisation, summarisation, redaction
– Ethical use: bias checks, inclusive language, cultural sensitivity
– Documenting AI use (transparency notes, versioning, audit trail)
Module 3: Prompting skills lab
– Prompt frameworks: Role–Task–Context–Constraints–Output format
– Prompt libraries for PCM/RBM (planning, indicators, reporting)
– Practice: convert a weak prompt into a strong prompt; evaluate output quality
Day 1 Outputs
– Personal “Prompt Playbook” (participant-specific)
– Responsible AI checklist for partner organisations
Day 2 — Applying AI across the Project Cycle with PCM/RBM Tools
Module 4: AI for design and planning
– Situation analysis: turning qualitative notes into structured problem statements
– Drafting Theory of Change (ToC) assumptions and risks; stress-testing logic
– Logframe support: outputs/outcomes alignment, indicator quality checks (SMART/CREAM)
– Workplan and implementation planning: activity sequencing, milestones, RACI draft
Module 5: AI for MEAL system design
– M&E plan structure: indicators, means of verification, frequency, responsibilities
– Data collection tools: survey/FGD guides (with bias checks)
– Data quality: validation rules, skip logic, cleaning checklists
Module 6: AI for reporting and donor communications
– Drafting narrative reports: results, challenges, adaptations, lessons learned
– Producing clear summaries for multiple audiences (HQ, partners, communities)
– Tone, clarity, safeguarding language, and “do-no-harm” wording
Day 2 Outputs
– A revised ToC/logframe excerpt (from a case or anonymised real example)
– A draft M&E plan component (indicator + data collection plan)
– A reporting outline and paragraph set (results + evidence + narrative)
Day 3 — Monitoring Data, Dashboards/Graphs, Interpretation, and Adaptation
Module 7: Simple dashboards/graphs for monitoring
– Turning raw monitoring tables into useful visuals (Excel/Sheets-based)
– AI-assisted formulas, pivot guidance, chart suggestions, and error checking
– Building a “minimum viable dashboard” (3–5 KPIs + disaggregation)
Module 8: Interpretation for program decisions
– Reading trends vs noise; common interpretation mistakes
– Using AI to generate hypotheses (not conclusions) and testing them
– Decision memos: what data suggests, what it doesn’t, what to do next
Module 9: Adapting content for different ages, levels, and learning contexts
– Simplifying technical content without losing accuracy
– Creating training handouts, facilitator notes, and youth-friendly materials
– Translating/adapting messages for culturally appropriate communication
Module 10: Capstone clinic + follow-up assignment briefing
– Participants work on a real deliverable (logframe section, dashboard, reporting piece)
– Peer review using a quality checklist
– Trainer feedback + next steps
Day 3 Outputs
– Basic dashboard/graph set + interpretation notes
– A one-page learning brief or donor-ready summary
– Capstone deliverable improved through peer review

Training Fee:

– USD 150 for local organizations (Home Country-based)
– USD 250 for International organizations (Home Country-based)
– USD 450 for all organizations (Other Countries)

Discount:

– Register three participants from the same organization, and the fourth participant attends free of charge.

Residential Package

Residential packages available on-site for additional charges.

In-House Training

CRSM also offers in-house training for organizations. This cost-effective solution allows you to customize the training to meet your organization’s specific needs, ensuring maximum relevance and applicability to your projects and initiatives. To discuss this, please get in touch with a CRSM representative at +92 321 55 65 072 or +92 316 58 87 783 or email registration@crsmconsulting.net

For Further Information:

For Further Information, Please Contact:

Email: registration@crsmconsulting.net

Phone number: +92 (321) 55 65 072 | +92 (316) 58 87 783