Measured shift
Have a position statement on AI
Delhi
43%→76%
São Paulo
12%→38%
Ciudad de México
30%→67%
Stockholm
61%→76%
Kuala Lumpur
43%→64%
Product
AI Policy Maturity Matrix
Turn AI ambition into responsible execution, reducing bias, strengthening ethical decision-making, and building sustainable AI systems that can scale. Created by Jos Dirkx, in partnership with Beenova AI and Google.
Ministerial leaders leveraged the AI Policy Maturity Matrix
Brazil
Mexico
Spain
Malaysia
India
Sweden
Finland
“Very fruitful workshop. Well done.”
“We are blessed to have you and your team here. Thank you for the golden knowledge shared.”
“What a wonderful two days. Your facilitation and ability to truly engage people, and get them to do fun, hard things, is incredible.”
“An inspiring and productive day. We have set many key matters in motion.”
“Very inspiring. Thank you!”
“An inspiring and very useful workshop, great days.”
The challenge
Most organizations are using AI. Very few are governing it well.
Leaders know AI matters, but they’re stuck with:
- Fragmented pilots and unclear ownership
- A lack of clarity around ethics, safety and sustainability
- Vague policies that don’t translate into action
- Internal resistance driven by fear, confusion, or misalignment
- Bias and unequal outcomes that go undetected until they affect people, trust, and performance
The result? AI adoption that is slow, risky, or operational where it's not really needed. The Matrix exists to fix that.
What it is (and why it works)
A proven, high-impact framework
The AI Policy Maturity Matrix is a proven, high-impact framework used in real-world workshops across the globe to help organizations, small to very large, understand where they are, align leadership, and move forward with confidence.
This is not a theoretical model.
01
From Abstract to Clear
Abstract AI conversations → clear system-level insight
02
From Disagreement to Alignment
Disagreement → shared language
03
From Risk to Structure
Concern and risk → structured decision-making
04
From Ambition to Action
Ambition → prioritized action
The framework
The six domains that make or break AI at scale
These domains expose hidden blockers that most AI initiatives miss.
Five levels. No guesswork.
01
Governance & Strategy
01 Ad hoc
02 Emerging
03 Developing
04 Established
Monitoring & Evaluation
Regular review cycles with defined KPIs. Review dates and metrics are established clearly.
05 Transformational
02
Data Infrastructure & Privacy
01 Ad hoc
02 Emerging
Data Governance
Draft data model and stewardship emerging. The data model is written down but is not yet owned by one person or one team.
03 Developing
04 Established
05 Transformational
03
People & Capability
01 Ad hoc
02 Emerging
03 Developing
Integration into the Work
More than one function has changed how it works, with worked examples people can follow.
04 Established
05 Transformational
04
Evaluation & Ethics
01 Ad hoc
02 Emerging
03 Developing
04 Established
Ethical Frameworks & Principles
Operational ethics with checklists, DPIAs and guardrails for day-to-day use. Checks for bias and harm are applied before deployment rather than after.
05 Transformational
05
Partnerships & Innovation Ecosystems
01 Ad hoc
02 Emerging
03 Developing
Pilots & Experiments
Pilots start with a stated question and an agreed way of telling whether the answer was no, with ethics and risk checked first.
04 Established
05 Transformational
06
Mindset & Exponentials
01 Ad hoc
02 Emerging
03 Developing
04 Established
05 Transformational
Assumptions
The organization can name what it believed last year and was wrong about, and what it changed as a result.
What happens in a Matrix session
The Matrix is delivered through high-energy, facilitated workshops designed for leadership teams and cross-functional groups.
- Ethical and leadership decision moments
- Concrete roadmap articulation
- Individual and group scoring
- Guided discussion and comparison
- “Level-up” exercises
- Examine bias, representation, ethical trade-offs, and resource use across real AI decisions
“The moments that created the most energy were the matrix session, the level-up exercise, and the ethical and leadership discussions.”
“Articulating clearer visions, putting words to a plan forward, and agreeing on specific next steps for our municipality, company, or team.”
What organizations use it for
From intent to execution
What you walk away with
Organizations leave with
01
Benchmark AI maturity
across leadership, operations, data, people, and ethics.
01
Clear Maturity View
Before Every leader estimates maturity differently.
After One shared, defensible read of where you actually stand.
02
Align teams
Executives, legal, IT, and frontline teams in one room.
02
Leadership Alignment
Before Functions plan in parallel and call it alignment.
After Leadership and functions agree on the same priorities.
03
De-risk adoption
without killing innovation.
03
Risk Understanding
Before Risk surfaces late, usually from legal.
After Risks and opportunities understood early enough to act on.
04
Create buy-in
by making risks visible and manageable.
04
Actionable Steps
Before Risk talk stalls the room.
After Prioritized next steps people are willing to own.
05
Prioritize moves
instead of debating endlessly.
05
Scaling Foundation
Before Decisions relitigated every quarter.
After A foundation for scaling AI deliberately, not reactively.
06
Responsible AI Priorities
06
Responsible AI Priorities
Before Responsible AI lived in a policy document.
After Clear priorities for reducing bias, strengthening accountability, and making AI development more sustainable, with diversity and ethics treated as a standing priority.
Proven impact, globally
What Audiences Say
Across countries, sectors, and organization sizes:
More than two-thirds
Most Valuable
More than two-thirds of participants find the Matrix the most valuable aspect of a two-day workshop. That's why we've built a process around it.
Highlights
Delhi, India
100% of all ratings in the top three categories
São Paulo, Brazil
A 3x jump in policy maturity, in two days
Ciudad de México
Highest in the series
Stockholm
Best sessions at Google for a long time.
Madrid, Spain
Regulatory complexity turned into decisions schools can act on
Kuala Lumpur, Malaysia
Highest post workshop rating
Measured shift
AI awareness (of 5)
São Paulo
2.82→3.31
Ciudad de México
3.70→4.11
Stockholm
3.65→4.03
Madrid
3.27→3.70
Kuala Lumpur
3.93→4.50
Effectiveness
Day-1 and overall effectiveness
Delhi, India
8.67/10
8.33/10
Day-1Overall
São Paulo, Brazil
9.27/10
9.31/10
Day-1Overall
Ciudad de México
9.56/10
9.67/10
Day-1Overall
Stockholm
8.08/10
Day-1
Madrid, Spain
8.06/10
8.10/10
Day-1Overall
Kuala Lumpur, Malaysia
8.81/10
9.04/10
Day-1Overall
“Truly appreciate your support for Team Malaysia. We look forward to having you back.”
“All of it was great, but especially the matrix session.”
“We managed to identify clear next steps and turn discussion into a real plan.”
“I’m proud that we were able to articulate a clear vision for the direction our AI policy should take.”
Who it’s for
While widely used in education systems, the AI Policy Maturity Matrix is sector-agnostic and easily adapted.
Enterprise
Corporates and enterprises
Growth Companies
SMEs and fast-growing startups
Public Sector
Government agencies and municipalities
Regulated Industries
Healthcare, finance, infrastructure, and regulated industries
Organizations
NGOs and large networks
If your organization is asking, “How do we scale AI responsibly without slowing ourselves down?”, this is designed for you.
About the creators
Built from the real world, not theory
The AI Policy Maturity Matrix was created by Jos Dirkx, in partnership with Beenova AI and Google, combining deep AI expertise, facilitation excellence, and years of implementation experience. The focus is practical: helping organizations move faster, with fewer mistakes and an emphasis on ethics and sustainability, helping teams discern when, where, why and how to use AI.
It is built on six to seven years of hands-on AI work, including:
- · AI policy and strategy labs across multiple countries
- · Leadership workshops with public and private organizations
- · Advisory work helping teams scale AI responsibly
- · IP gathered from implementing AI inside complex systems, not just talking about it
It reflects what actually breaks, actually works, and actually scales.
The structure matters
Where the alignment comes from
Participants consistently rate the content and format from “very valuable” to “outstanding”. They value:
Focused Leadership Time
Focused time with their own leadership teams.
Cross-Organizational Dialogue
Cross-organizational dialogue that challenges assumptions.
Energizing Conversations
Conversations described as humbling, fun, and energizing.
This combination creates trust, momentum, and buy-in, even in risk-averse environments.
“A critical understanding of risks that will help secure stronger buy-in.”
Send a message
Let’s Connect
For direct inquiries, please email us.
Tell us where your organization stands with AI and we’ll make sure your message lands in the right hands.