AI practice moves every quarter
New models, platforms and operating practices arrive faster than a traditional course cycle can absorb them.
Driver · AI-driven pace of change
Majlis Academy · academy.majlisofai.com
Training that keeps pace with AI in regulated institutions
We build AI, cloud and data capability inside banks, telcos and government entities across the GCC. Executive briefings, bootcamps, labs, capstones, hackathons and accelerator tracks — designed by learning science, produced by an AI Training Factory, and owned by your teams when we leave.
current practice, not last year's course
01 · Why the Academy exists
Courses take months to build and go stale after release
AI and cloud practice change faster than training. In regulated sectors, the rules change too. We designed the Academy to close that gap and to leave the capability with you.
Regulators update rules on AI, cloud and data
GCC regulators issue new expectations. Staff must apply them correctly and show evidence that they can.
Driver · Regulatory change
Shorter time from change to trained staff
One knowledge base in Git feeds every programme. When a source changes, the factory finds each package that depends on it and rebuilds it.
Outcome · Your organisation owns its training capability
02 · Pedagogy
We start from what people must do, then design back to the lesson
Six principles from learning science govern every programme. Each one has a check in the factory, so the principle survives production at speed.
Objectives first, evidence second, activities last
After Wiggins and McTighe. Each objective has a measurable verb at a stated Bloom level. A script checks that every objective has evidence and activities.
Designs every syllabus
Short units, deliberate pacing, no extraneous load
Cognitive Load Theory and Mayer's multimedia principles. Content comes in 6–12 minute micro-lessons with retrieval breaks.
Audits slides, labs and media
Practice on cases from your own sector
Branching cases from banking, telco and government. Role-plays, jigsaws, debates, and ArchiMate and Wardley-mapping exercises.
Classroom, online and hybrid
Learners know the purpose, task and criteria
TILT assessments, calibrated rubrics and peer review. Labs use deterministic graders, so the same answer always gets the same result.
Fair, repeatable evidence
Cohorts learn from each other
We build teaching, social and cognitive presence. Clear norms, onboarding, weekly prompts and wrap-up digests keep a cohort active.
Online and hybrid delivery
Technical text in Simplified Technical English
Learner-facing material follows ASD-STE100: one instruction per sentence, verb first, one word for one meaning. Framework terms stay exact.
Clear for every first language
Decide what they must do. Then teach to it.
03 · Methodology
One value stream, eight stages, five human decisions
Every programme moves through the same stages, from a change in the world to a renewed package. Agents do the production work. People make the decisions. Select a stage to see what happens.
Build the package
Run, measure and renew
stage 8 feeds stage 1 — the loop never closes
1Factory value stream
Business process view · eight stages · source: AI Training Factory blueprint
Quality gates before release
Scripts run each gate. A package with a failed gate does not reach a learner.
| Gate | Checks | Run by |
|---|---|---|
| G1 | The knowledge bundle is valid against OKF v0.2 and the training profile | validate_bundle.py |
| G2 | Each objective has its evidence and its activities | alignment_check.py |
| G3 | Learner text follows ASD-STE100 and uses exact framework terms | ste_lint.py + review |
| G4 | Each lab grader passes right answers and fails wrong ones | grader_test.py |
| G5 | No concept in the package is past its review date | stale_report.py |
Decisions that stay with people
The factory prepares the inputs and stops. It does not decide for you.
| ID | Decision | Decided by |
|---|---|---|
| D1 | Accept a concept as stable | Knowledge Steward |
| D2 | Approve the learning plan | Learning Architect with client sponsor |
| D3 | Release the package | Learning Architect |
| D4 | Choose the lab data source | Client data owner · default synthetic |
| D5 | Renew or retire a package | Knowledge Steward and Learning Architect |
04 · Audience and programmes
From the boardroom to the build team
Three audiences, one knowledge base. Leaders get decision framing. Practitioners get hands-on work. Your learning team gets the factory.
CXO, ExCo and board members
Decide on AI with a shared vocabulary. Briefings use only human-reviewed knowledge, frame the decision, and show the regulatory context.
Executive briefings · steering-committee teach-ins
Architects, engineers and delivery teams
Build and run AI, cloud and data platforms under regulation. Learners prove skills in graded labs, capstones and hackathons on synthetic sandbox data.
Bootcamps · labs · capstones · hackathons · accelerators
L&D, CoE leads and knowledge stewards
Run the factory yourselves. We transfer the Brain, the skills and the gates, and we train your people in the roles that operate them.
Knowledge Steward · Learning Architect · Facilitator
Formats
| Format | For | Shape | Evidence of learning |
|---|---|---|---|
| Executive briefing | CXO, ExCo, board | 45–90 minutes · Wardley map and ArchiMate overview · regulatory context | One decision exercise |
| Technical bootcamp | Architects, engineers | Micro-lessons of 6–12 minutes, cases and labs, classroom or hybrid | Graded labs and TILT assessments |
| Hands-on lab | Engineers | Lab environment as infrastructure as code · synthetic data | Deterministic attester grades the result |
| Capstone | Bootcamp graduates | Challenge brief tied to objectives · milestone gates · mentors | Rubric review and demo day |
| Hackathon | Cross-functional teams | One to three days · sandbox data · judging rubric | Working solution and demo |
| Accelerator track | A cohort with a real use case | Cohort over several weeks · mentor plan · milestone gates | Gate reviews toward a pilot |
| Online micro-learning | Any audience | 6–12 minute units on your LMS or LXP | Retrieval quizzes and item analysis |
Content
We teach with each industry's own frameworks
BIAN service domains
Map AI and data use cases to the BIAN service landscape and to the controls a banking regulator expects.
TM Forum ODA and Frameworx
Work with ODA components and their widely used predecessors: eTOM processes, the SID information model and the TAM application map.
TOGAF, Well-Architected and ArchiMate 3.2
Describe target states formally. Every architecture exercise uses ArchiMate notation and Well-Architected review questions.
Wardley mapping and systems thinking
See the landscape before choosing a move. Map value chains, evolution and feedback loops in complex systems.
Cloud, data and AI operations
DevOps, DataOps, MLOps, LLMOps, AIOps and ScienceOps as standards. Labs in Python, TypeScript, Go and Rust. Documentation as code.
AI regulation and standards
Apply GCC regulator guidance with the EU AI Act, NIST AI RMF and ISO/IEC 42001 as reference frames for controls.
05 · The technology
An AI Training Factory built on knowledge as code
The Brain is one Open Knowledge Format (OKF) v0.2 bundle in Git. Seventeen agent skills turn its concepts into learning packages. CI runs the gates on every pull request.
Business
roles
roles
Knowledge StewardVerifies concepts
Learning ArchitectOwns design and release
Production EngineerRuns skills, edits assets
FacilitatorClass, online, hackathon
Business
processes
processes
Curate knowledge
Design learning
Produce assets
Assure release
Deliver · measure · renew
Application
components
components
BrainOKF v0.2 bundle in Git
Skill runtimeFactory agents
Freshness SentinelFinds stale concepts
Lab GraderDeterministic, no LLM
LMS / LXPClient channel
Learning analytics
one source of truth for every package
Data
OKF conceptMarkdown + YAML front matter
Learning packageOne audience, one format
Attestation receiptRuntime evidence only
Technology
Git platform and CIGates on pull requests
LLM platform
Lab sandboxSynthetic data
SkillsSKILL.md files
AttestersGrader code
Lab IaCEnvironments as code
In scope
Client context
Focal component
Notation: ArchiMate 3.2, monochrome
2Layered view
ArchiMate 3.2 · simplified for the web · source: ai-training-factory.archimate.xml
Every fact has a source and a review date
Concepts are Markdown files with front matter. Each one records its sources, trust tier and the date after which it is stale.
Change finds its own impact
The Sentinel compares review dates with today and follows links to every package that uses a stale concept.
Graders that do not guess
Lab graders are deterministic code, not an LLM. They are tested against right and wrong answers before release.
Seventeen skills, one per job
Skills harvest knowledge, design syllabi, write scripts, build labs and check language. A router skill stops at each human decision.
An OKF concept · Illustrative
--- id: bian-service-domain type: domain-concept status: stable sources: - BIAN Service Landscape trust_tier: primary stale_after: 2027-04-30 verified_by: human:steward-01 --- # BIAN service domain A service domain is one discrete business capability. It has one control record and one owner.
Field names are simplified for this page. The OKF v0.2 training profile defines the exact schema.
06 · Partnerships in the GCC
Three partners, one programme for regulated institutions
We work with Zero to 100 and Emeritus across the GCC. Each partner brings a different strength. Together, a client gets scale, academic standing and regulated-sector depth in one programme.
Zero to 100
An AI adoption platform and consultancy. Z100 assesses AI readiness, sets use-case priorities and runs role-based AI fluency for the whole workforce.
zeroto100.ai · adoption at scale
Regulated-sector depth
We add what regulated institutions need on top: BIAN and TM Forum architecture, controls and regulatory context, graded engineering labs, capstones and hackathons, and a factory your team can own.
academy.majlisofai.com · practitioners and leaders
Emeritus
Executive and professional programmes delivered with more than 80 universities, for individuals and for private enterprise cohorts.
emeritus.com · academic standing
How the work divides in a joint programme
| Step | Zero to 100 | Majlis Academy | Emeritus |
|---|---|---|---|
| Diagnose | AI readiness and use-case priorities | Architecture and regulatory gaps | — |
| Lead | Board and executive alignment | Executive briefings with decision framing | University-backed executive programmes |
| Build skills | Workforce AI fluency on the platform | Bootcamps, labs, capstones, hackathons | Professional certificates |
| Sustain | Workflows and agents in daily work | Factory transfer to the client team | Alumni and continuing education |
Partner descriptions summarise each partner's public website, October 2026. Scope is agreed per engagement.
07 · Work with us
Build the capability once, then keep it current yourselves
Majlis Academy is the training practice of The Majlis of AI. Tell us the capability your teams need, and we will propose a first package and the path to run it in-house.
Sit together
We meet your leaders and learning team. We agree the audience, format and domain.
Listen first
We curate the knowledge, design back from objectives, and ask your sponsor to approve the plan.
Hand over
We deliver the first cohort, then transfer the Brain, the skills and the gates to your team.