The usual course
Built once. Stale on release.
A catalogue course, written over months, delivered the same way to every team.
- Months to build
- Out of date at release
- Weeks away from the work
- Same content for every team
- Nobody owns it after delivery
Majlis Academy · AI training for regulated institutions
Learn fast. Stay current. Keep the core.
AI changes every quarter. Your training should too. Majlis Academy runs short, custom programmes for banks, telcos and governments across the GCC: rebuilt as the practice moves, on a core of regulation, architecture and method that does not. Days, not months. Applied in the next sprint. Owned by your teams when we leave.
Current practice, not last year's course
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
$ make gates ✓ G1 validate_bundle.py bundle is valid ✓ G2 alignment_check.py objectives aligned ✓ G3 ste_lint.py ASD-STE100 ✓ G4 grader_test.py graders tested ✓ G5 stale_report.py no stale concepts → D3 release: Learning Architect decides
$ stale_report.py ✓ bian-service-domain current to 2027-04-30 ✕ example-concept past its review date follows links to each package that uses it → D5 rebuild or retire: Knowledge Steward
Illustrative · field names simplified
We teach in
ADLC bootcamp: AI in the engineering delivery lifecycle.
Four days, classroom, at your site. Your engineers learn to use AI from intake to release at a known cost, with verification evidence and a human approval gate on each stage. Twelve outcomes. Sixteen assets your team keeps.
01 · Why the Academy exists
Why the Academy
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.
-
#1 Driver
AI practice moves every quarter.
New models, platforms and operating practices arrive faster than a traditional course cycle can absorb them.
DriverAI-driven pace of change
-
#2 Driver
Regulators update rules on AI, cloud and data.
GCC regulators issue new expectations. Staff must apply them correctly and show evidence that they can.
DriverRegulatory change
-
#3 Our answer
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.
OutcomeYour organisation owns its training capability
02 · How we stay current without losing the core
Fast on top. Solid underneath.
Every programme has two layers. The top layer is rebuilt as the practice moves: models, agent patterns, tools, the regulator's latest signal. The core underneath does not move with the news: regulation, sector models, architecture and the method. Your people learn the new on top of the solid.
Current practice
- Rebuilt every cohortFrontier and sovereign models · agent and MCP patterns · evaluation and red-teaming tools · vendor platforms · this quarter's regulatory signalsMoves monthly
The core
- RegulationISO/IEC 42001 · NIST AI RMF · EU AI Act · GCC rules
- Sector modelsBIAN · TM Forum ODA · GovStack
- ArchitectureTOGAF · ArchiMate · Wardley
- The methodOne owner · controls as tests · one release gate
the news changes the top layer. it never rewrites the core
How it stays current
- One knowledge base in GitEvery concept has a source, a steward and a stale-after date
- The factory rebuildsWhen a source changes, each package that depends on it is rebuilt or retired
- You take it overYour stewards own the base. The next cohort is yours to run
A Majlis programme
Short. Custom. Current. On a solid core.
Built for your decisions and your sector, delivered in days, and applied in the sprint that follows.
- 3–4 day formats, never longer; briefings in hours
- Rebuilt when the practice or the rule changes
- Applied in the next sprint
- Custom to your sector and your systems
- Core kept stable: regulation, architecture, method
- Your team owns the knowledge base
Inside the Academy
How we build programmes, how people learn with us, and what you can register for now.
- AI in the engineering delivery lifecycleA four-day classroom bootcamp for engineering teams: use AI from intake to release at a known cost, with verification evidence.
#1 · ADLC bootcamp
Open now · 4 days
- One core, three sector tracksGovKit Core, then a sector track for government, banking or telco. No course runs longer than four days.
#2 · Courses
Available soon
- How we workProgrammes, formats, the eight-stage method, the teams and the technology behind them.
#3 · How
- The way we teachOur pedagogy: how people learn at the Academy, and the rules we keep.
#4 · The Tao
03 · Partnerships in the GCC
Partners
Two partners, one programme for regulated institutions.
We work with Zero to 100 across the GCC. Each partner brings a different strength. Together, a client gets AI adoption at scale and regulated-sector depth in one programme.
Partner · AI adoption
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.
- AI diagnostics
- AI fluency
- Workflows and agents
Adoption at scale
zeroto100.aiMajlis Academy
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.
- Architecture
- Graded labs
- Factory transfer
Practitioners and leaders
Ask about a joint programmeHow the work divides in a joint programme
| Step | Zero to 100 | Majlis Academy |
|---|---|---|
| Diagnose | AI readiness and use-case priorities | Architecture and regulatory gaps |
| Lead | Board and executive alignment | Executive briefings with decision framing |
| Build skills | Workforce AI fluency on the platform | Bootcamps, labs, capstones, hackathons |
| Sustain | Workflows and agents in daily work | Factory transfer to the client team |
The Zero to 100 description summarises its public website, October 2026. Scope is agreed per engagement.
One practice, three ways in
We advise. We train. We build.
- #1 · Majlis AdvisoryWe adviseDecide fast, with one owner and a control your regulator can test.See the advisory
- #2 · You are hereWe trainShort, always-current programmes on a solid core. Your people run the method themselves.See the courses
- #3 · AI FactoriesWe buildAI factories, built with your engineers in your own tenant.See AI Factories
We advise, we train and we build with you.
Agree the objectives once. Then every cohort learns at full speed.
04 · 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. We propose a first package and the path to run it in-house.
- 1 · Agree the scopeWe meet your leaders and learning team. We agree the audience, format and domain.
- 2 · Design from the objectivesWe curate the knowledge, design back from objectives, and ask your sponsor to approve the plan.
- 3 · Hand overWe deliver the first cohort. Then we transfer the Brain, the skills and the gates to your team.