Mission-driven and international organisations face the most acute version of the AI question: real pressure to work faster, and real consequences if a beneficiary's data ends up in the wrong place. Below is who we speak with, what each is trying to achieve, and the result each one ends with.
Across NGOs, foundations, UN agencies and public institutions, from small teams to 500 staff.
The job: Answer the board and the funders on AI with a written position.
The problem: A board member has raised the question. A donor questionnaire includes an AI section. Staff are believed to use AI, and the extent is unknown.
The result: A scored baseline and a policy in force before the next board meeting, and a written answer for the donor questionnaire.
Current response: The question is deferred to the next meeting.
The job: Prevent the incident, pass the audit, keep the tool list under control.
The problem: A prohibition memo was issued. Use continued out of view, and can no longer be monitored.
The result: A policy people follow because it permits. An approved tool list, a data classification table, an evidence file.
Current response: Prohibition and blocking, with limited visibility.
The job: Deliver training people complete and use, and spend the training line defensibly.
The problem: Completion rates below twenty percent. No evidence of changed practice. Staff still ask what is permitted.
The result: Ninety minutes per department that fits a real calendar. An attendance record and a before-and-after score.
Current response: The licence is renewed.
The job: Deliver proposals and donor reports on time without exhausting the team.
The problem: Uneven, private AI use. The risk that a junior colleague sends an unverified figure to a donor.
The result: Countable hours recovered on the next three proposals. A playbook the team uses. Permission to share what works.
Current response: Additional hours and personal accounts.
Training centres and academies work with us as delivery partners. Private-sector work is taken on referral. Individuals and organisation representatives are served through courses for fewer than ten participants, in person or online, priced per person.
Fixed price, fixed scope, agreed before work begins. Build your own scope in the estimator to see an indicative range.
| Package | Starting point | Result | How | Time | Price |
|---|---|---|---|---|---|
| Foundation | Up to 50 staff, no first step taken yet | A baseline score and one shared page everybody works from. You know what to fix next and can show a funder you have begun. | Short readiness assessment, one organisation-wide session, one shared playbook. | ~3 weeks | Estimate → |
| Adoption Recommended |
50–500 staff, AI in use across departments with no policy and no shared method | A policy in force, four departments working from their own pages, and a before-and-after score. The file a donor or auditor asks for exists. | Full ten-dimension assessment, board-ready AI use policy, organisation-wide session, four department labs with playbooks, re-score at 90 days. | ~8 weeks | Estimate → |
| Institution | Regulated, audited or multi-site, with compliance to demonstrate | A documented file mapped to ISO/IEC 42001, the NIST AI RMF and Article 4, and trainers in-house who can run the sessions without us. | Everything in Adoption, plus a governance gap plan against ISO/IEC 42001 and the NIST AI RMF, an EU AI Act Article 4 evidence file, train-the-trainer, and twelve months of support. | ~12 weeks + 12 months |
On a call → |
Thirty minutes on what is happening with AI in your organisation and which of the five services applies, if any.
The assessment, plus interviews where the package includes them. You receive a score and a ranked list before anyone is trained.
Policy drafted together with your people. Sessions built on your teams' real tasks and real documents.
A re-score, the evidence file, and the playbooks in your hands. Engagements close with a capability you own.
“The AI Literacy training wasn't just theoretical. It gave our management team the actual tools and confidence to lead our own digital transformation internally.”
BlackBird Training Center
“M.A.I. Consulting provided the intellectual bridge we needed to move our AI initiatives from theory to production. Their methodology is rigorous, transparent, and results-oriented.”
AI for Good Foundation
Disclosure: M.A.I. Consulting's principal also holds a role at the foundation.
Both are free. The check takes twelve minutes and you keep the report in either case.