For humanitarian and development professionals
Work with realistic project documents, verify AI-generated outputs and build reusable workflows through six live sessions and practical work between sessions.
Next available live cohorts
EUR 350 including VATSelf-funded individual
EUR 280 including VATEligible self-funding rate
Six 90-minute live sessions over three weeksLive commitment
September 2026 cohort
Applications remain open while places are available.
Tuesdays and Thursdays
22, 24 and 29 September; 1, 6 and 8 October 2026
10:00 to 11:30 Cyprus time (07:00 to 08:30 UTC)
Choose morning cohortWednesdays and Fridays
23, 25 and 30 September; 2, 7 and 9 October 2026
16:00 to 17:30 Cyprus time (13:00 to 14:30 UTC)
Choose afternoon cohortEmployer paying? Organisation-funded open-cohort places are EUR 350 per participant excluding VAT and follow the invoicing process.
Ask about an organisation-funded place Pricing and VAT policyParticipant feedback
This training helped our teams understand AI in a practical, responsible way. People came out with real workflows they can use immediately, clearer safeguards, and the confidence to work safely with these tools. It was one of the most relevant and useful trainings we've had this year.
Cohort evidence
July 2026 cohort · Responses to · n=7
Learning examples
Each example uses fictional or synthetic material and makes the human checks visible.
Included in the cohort
Six 90-minute live sessions over three weeks, plus 20–30 minutes of practice between sessions
Join a shared open cohort or commission a programme adapted to your organisation.
Open cohorts
A shared fictional workplace gives every learner realistic evidence, decisions and constraints without exposing real organisational data.
See dates and cohort detailsCustom programmes
Adapt the roles, source material, tasks and governance context for an agency, government team or organisation while keeping the AidGPT core.
Discuss a tailored programmeParticipant evidence
I signed up a little nervous it might be too introductory. It wasn't. The instructors pitched it at a useful technical level for people already working with AI in practice. The cohort format meant real-time pressure-testing of ideas, and other participants' questions sharpened my thinking. If you work in the humanitarian or development sector and want to go beyond the hype on AI, this is worth your time.
The training took something complex and made it workable. The trainers have a rare gift for translating daunting territory into practical, usable guidance that lands across different roles and industries. I walked in uncertain. I walked out confident, equipped to use these tools wisely, and clear-eyed about what I should and shouldn't do.
The learning journey
The course moves from understanding and controlling AI to building useful systems and making responsible decisions about how they should be used.
What is AI, how should we think about it, and how can we control it?
Learn to choose a worthwhile task, give AI a proper brief and remain responsible for the purpose, constraints and final result.
When can we trust AI-generated work, and how should we challenge, check and verify it?
Learn to ground work in reliable sources, challenge the first answer, test important claims and explain material AI use when accountability requires it.
What structures allow an AI system to work reliably over longer, multi-step tasks?
Learn to organise instructions, context, source material and intermediate outputs so useful work does not depend on one increasingly unreliable conversation.
What can AI reach and do through connectors, local files, browsers and computer access—and how should that access be controlled?
Learn to distinguish availability from authority, limit access to what the task requires and keep consequential actions behind an explicit human decision.
What useful applications become possible when we combine these capabilities with deliberate memory and reusable context?
Learn to turn a successful piece of AI-supported work into a repeatable system that retains the right instructions, sources, checks and organisational knowledge.
What does this mean for risk, accountability, organisational policy and the future of work?
Decide what should be adopted, what needs safeguards or policy, what remains experimental and what should stay human-led.
Synthetic practice world
Eleni Andreou is Head of Programmes at Koinon Relief Partnership in the fictional Republic of Alashiya. She works across programme priorities, evidence, partners and operational constraints during early recovery. Her role gives the cohort a consistent point of view without using real organisational or personal information.
Synthetic training material — not a real crisis or participant case.
Public guide · MI-GUIDE-001
A free ten-page guide for managers: what staff may use AI for, what must be disclosed, and a staff notice ready to adapt and issue. Free, ungated and CC BY 4.0.
Public guide · MI-GUIDE-002
A free six-page protocol for commissioning AI-assisted analysis you can defend: seven phases, nine failure modes with the control that caught each one, and ten requirements you can write into terms of reference. Free, ungated and CC BY 4.0.