01Delivery mode
Self-paced learning
Defined format · enrolment not open
A defined self-directed twelve-stage method with the book and toolkit as its spine. The format is not yet open for enrolment.
Scalebotics training
Build the conditions that make AI valuable in real organizations.
AI Value Management training teaches you how to connect AI capability to business value: define the value case, place AI in real workflows, establish decision rights, judge readiness and evaluate outcomes. The method is grounded in The AI Value Gap and the AI Value Management Operating Toolkit.
01Three ways to learn
Choose the format that fits the decision.
The same twelve-stage arc runs through every format. What changes is the setting, the facilitation, and whose AI uses the work is oriented around.
02Delivery mode
Live public-seat cohorts
Enquiries only · no dates or seats announced
Facilitated cohorts with peer operators working through the twelve stages. Dates, seat capacity and registration remain subject to activation.
03Delivery mode
Private enterprise cohorts
Scoping enquiry · schedule subject to confirmation
The defined twelve-stage format for one organization or team, oriented around its AI uses. Scope, schedule and delivery commitments are agreed separately.
02The learning arc
Twelve stages. One connected discipline.
The arc follows the same order the operating discipline follows — from diagnosis to portfolio. Each stage has a declared output and an evidence boundary.
Diagnose the value gap
Separate visible AI activity from decision-useful evidence of value.
Bound one intervention
Define a single AI use with clear boundaries before increasing commitment.
Apply the Five Conditions
Test the use against the five conditions that value depends on.
Build the value case
State the value claim in terms a decision-maker can authorize.
Place AI in real work
Put the use inside an actual workflow with named ownership.
Allocate decision rights
Decide who decides, who reviews, and who is accountable.
Design review and escalation
Build the review paths and escalation rules before they are needed.
Judge readiness
Determine whether the current evidence supports the decision approaching.
Design a managed pilot
Scope a pilot that produces evidence, not just activity.
Operate runtime assurance
Keep value, cost, permission, and evidence current as conditions change.
Make evidence-authorized decisions
Commit only as far as the evidence supports.
Place the intervention in the portfolio
Allocate the intervention alongside every other claim on resources.
03Who it is for
Built for the people who carry the decision.
Training is for the organization that wants the capability inside its own walls — not rented for the length of an engagement.
01Audience
Leaders
Who authorize AI investment and need the judgment to do it on evidence rather than momentum.
02Audience
Operators
Who place AI inside real workflows and live with the consequences of the operating design.
03Audience
Practitioners
Building AI value capability as a professional discipline — the people who will run the method after the engagement ends.
Grounded in the doctrine, not in the product.
Participants use The AI Value Gap and the AI Value Management Operating Toolkit to apply the twelve-stage method to the AI uses, workflows and decisions they manage.
Leadership orientation or transferable training?
The Executive AI Fluency Briefing frames leadership choices. AI Value Management training develops transferable method competence. Enquire directly about either route; neither requires buying the other first.
04Stay in the loop
Cohort announcements go to subscribers first.
Public-seat cohort dates and new releases from the training programme — via the State of AI Value newsletter.
05Next decision
Bring AI Value Management into your organization.
Whether you're learning individually or building capability across a team, explore the training format that fits your needs. Tell us what you're looking to achieve, and we'll help identify the right next step.