What AI may decide.
What people must continue to decide.
What AI may decide.
What people must continue to decide.
We design the boundary.
AI is already beside management.
The question is not how to use it.
It is what not to hand over.
Yamazaki Office designs that boundary.
The management challenges we address
- AI adoption is proceeding as isolated optimization.
- Priorities for DX investment cannot be set.
- Ownership of the data organization remains unclear.
- Decision-making has stalled in the boardroom.
- Governance for generative AI is not yet in place.
None of these is a technology problem. They are decision-making problems.
What we do — create a state in which management can decide
Management faces decisions that are better entrusted to AI,
and decisions people must retain to the end.
We draw that line.
As a Fractional CxO, we support decision-making and governance design for AI, DX, and data strategy directly under the CxOs of multiple listed companies and holding companies. We do not act as a production agency on the ground.
There are three things to decide.
What to invest in and what not to do.
Which KPIs management will use to decide.
Which decisions people will continue to hold.
Set these three, and create a state in which management can decide. That is the work of this office.
But we do not hand over a strategy on paper and leave. We step into the critical points of a project: data definitions, architecture selection, and technical validation.
Not a strategist who only draws the picture, but one who can implement it. That is the premise.
Three entry points
- Engagement Model
- Neither a hired executive nor a fully outsourced vendor. A third way of engaging: sit beside management.
- Judgment Lineage
- From executor to designer. From decision-maker to designer of decision-making. A record of a career in which the scope and responsibility of the decisions carried kept expanding.
- Evidence
- How patterns of judgment have been used in practice. Examine them through anonymized examples.
