Organization Readiness Assessment and Vision Canvas
Use it when...
Use when an organization is deciding whether and how fast to move on AI-supported coaching, or when a person or leader wants to commit to specific next steps.
What this is
The closing planning tools of the book: a five-line Organization Readiness Assessment scored 1-5 per line for a total out of 25, a Coached Machine Vision Canvas, a Future Scenario Planning Template (best, worst and most likely case), and Personal Action Commitments at 30 days, 90 days and one year. The chapter frames the choice as intentional design: "Both futures are possible. The choices you make now determine which one you get."
The book's final chapter also includes a section called "The Five-Year Horizon" with three forward-looking waves (2025-2026, 2027-2028, 2029-2030). These are the author's dated forecasts, not findings, and they are not reproduced here as facts.
Use when / Do not use when
Use when an organization is deciding whether and how fast to move on AI-supported coaching, or when a person or leader wants to commit to specific next steps.
Do not use the readiness total as a go/no-go rule. The bands are the book's guidance, given without validation. Do not quote the book's forecasts as expected outcomes.
The Instrument
Organization Readiness Assessment (book wording)
"Rate your organization 1-5 on each dimension:"
| Dimension | Guiding question (book) | Score (1-5) |
|---|---|---|
| Leadership alignment | Do leaders understand and support this? | ___ |
| Technical infrastructure | Do we have the systems to support AI coaching? | ___ |
| Manager capability | Are managers ready to orchestrate AI + human coaching? | ___ |
| Cultural readiness | Is the culture open to this change? | ___ |
| Measurement maturity | Can we track what matters? | ___ |
Total: ___/25
Scoring bands (exactly as the book gives them):
| Total | Band |
|---|---|
| Below 10 | Not ready. Build foundation first. |
| 10-15 | Possible but challenging. Pilot carefully. |
| 16-20 | Ready to scale. Move deliberately. |
| 21-25 | Strong position. Execute confidently. |
The book gives no anchor descriptions for individual scores of 1 to 5.
The Coached Machine Vision Canvas (book wording)
"Our 2030 vision:"
- Access: Who has coaching? Everyone? Still selective?
- Technology: What AI capabilities do we use? How integrated?
- Human role: What do managers do? What do coaches do?
- Boundaries: Where's the line between AI and human? How do we protect it?
- Culture: How do people talk about development? How does it feel?
- Impact: What's different? What problems did we solve? What value did we create?
Future Scenario Planning Template (book wording)
Best case (5 years): What does coaching look like? How has access changed? What can AI do that it can't today? What do humans focus on? What's the business impact?
Worst case (5 years): What went wrong? What got automated that shouldn't have been? What atrophied? How do people feel about it? What's the cost?
Most likely (5 years): What's realistic given current trajectory? Where will we succeed? Where will we struggle? What decisions matter most?
Personal Action Commitments (book wording)
- In the next 30 days I will: 1. [Specific action] 2. [Specific action] 3. [Specific action]
- In the next 90 days I will: 1. [Specific action] 2. [Specific action] 3. [Specific action]
- In the next year I will: 1. [Specific action] 2. [Specific action] 3. [Specific action]
Context from the chapter: two futures and four leader decisions (book wording)
The chapter sets two possible futures. Future A (Optimistic): everyone has access to coaching, managers have leverage rather than burnout, development is continuous, "The coaching gap closed." Future B (Pessimistic): organizations "automated the wrong things", people feel surveilled, human elements of development "atrophied", and "Performance metrics look better on dashboards. People feel worse." These are scenarios, not predictions of probability.
What leaders must get right:
- Where to draw the line. Be explicit about what AI handles versus what stays human; communicate the boundary; protect the human domain.
- How to build trust. Transparency about how AI coaching works; control (employees choose to use it); data privacy that people actually believe.
- How to develop human coaching capability. Don't assume AI reduces the need for manager skill; invest more in Transform coaching skills; train managers in presence, witnessing and meaning-making.
- How to measure what matters. Not just adoption metrics, not just efficiency metrics; human metrics: trust, meaning, belonging, growth.
The ethical stakes (the book's four tensions): Surveillance versus support; Autonomy versus optimization; Access versus quality; Efficiency versus humanity.
The individual imperative (the book's four headings): Don't wait; Invest in uniquely human skills; Maintain human relationships; Stay current.
How to run it (Performance Lab suggested practice)
- Have three to five people from different levels score the Readiness Assessment separately, then compare line by line. A single combined total hides disagreement.
- Write one sentence of evidence beside each score.
- Read the band, then read the lowest-scoring dimension. Decide the next step from that dimension, not from the band alone.
- Complete the Vision Canvas in a working session with leaders. Because the canvas uses 2030, record the date you completed it and revisit it on a schedule you choose.
- Run the scenario template with the best, worst and most likely cases written by different people.
- Each leader or manager completes Personal Action Commitments and brings them to the next review.
Record sheet (Performance Lab suggested practice)
| Field | Entry |
|---|---|
| Organization / unit / date | |
| Scorers (roles) | |
| Scores by dimension (5) | |
| Evidence per dimension | |
| Total /25 and book band | |
| Lowest dimension and next step | |
| Vision Canvas completed (date) | |
| Scenario cases written by | |
| Commitments recorded (30 / 90 days / year) |
From Performance Amplified by Chad T. Dyar, Ch.12.