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A PROPOSED PATHWAY FOR PRACTITIONERS
AI Transformation
Practitioner Fellowship.
The proposed AIDIVE Practitioner Fellowship brings learning, application and contribution together. Develop a question, case or practical insight that advances understanding of holistic enterprise AI transformation.
Proposed fellowship structure
TAKE THE NEXT STEP
LEARNING THROUGH CONTRIBUTION
A focused question.
A useful shared output.
WHO THIS COULD SERVE
Practitioners with a relevant transformation question, a permitted application context or a well-framed research or learning contribution. Final eligibility criteria remain open for design.
THE PROPOSED COMMITMENT
Develop a meaningful contribution, examine the evidence and improve the work through reflection and peer feedback.
A PROPOSED PATHWAY
From a question
to a contribution.
STAGE 01
Express an interest
describe your context, learning goal and a contribution you would like to explore.
STAGE 02
Shape a contribution
agree a focused question, scope, confidentiality needs and a useful output with the proposed fellowship team.
STAGE 03
Apply and exchange
develop the contribution through practice, structured reflection and peer discussion.
STAGE 04
Review and improve
examine evidence, test assumptions and revise the work with feedback.
STAGE 05
Share and continue
publish only approved material with clear attribution, then identify a next question for continued contribution.
This is a proposed fellowship design. Eligibility, selection, duration, intake, participation terms and any recognition remain to be defined.
What a contribution could look like
An anonymized practice case or a clearly labeled simulation with an explicit evidence trail.
A reusable tool, teaching example, practice improvement or research note connected to an AIDIVE topic.
A reflection on assumptions, limitations, observed learning and what should be tested next.
A concise, permission-cleared community contribution that distinguishes demonstrated results from hypotheses.
Draft selection principles
The proposed selection approach would value relevance, thoughtful practice and useful contribution.
Relevance to a substantive AI transformation question and the AIDIVE framework.
Willingness to make a useful contribution and respond constructively to feedback.
A credible evidence or research approach, including a simulation where real organizational access is unavailable.
Respect for confidentiality, consent, attribution and responsible use.
A mix of professional contexts, regions and perspectives that enriches shared learning.
Practice with an evidence trail
A contribution should make its question, context, reasoning and limitations clear. A carefully designed simulation can be useful when real organisational access is unavailable. Case material would be shared only with the necessary permissions.
Stay connected to the framework.
Ground the work in a relevant dimension, operating layer or practice. Explain which part of the framework helped, what remained uncertain and what another practitioner could use or investigate next.
Go a little deeper.
LEARN. CONTRIBUTE. APPLY.
Have a question worth exploring?
Bring it into the practice.
Build capability through training, contribute your expertise or explore a connected workspace for applying the holistic AIDIVE framework.
PRACTITIONER FELLOWSHIP
Contribute to the practice.
Share the question, case or contribution you would like to develop with other practitioners.
TRAINING & CERTIFICATION
Build the capability.
Develop the skills to connect AI transformation strategy, business outcomes, people and governance to your own decisions and responsibilities.
AIDIVE PLATFORM
Bring AIDIVE into your work.
See how the proposed workspace could connect AI transformation learning, maturity evidence and practical artifacts.
CONNECT THE DOTS