Days 7 and 8 explored the human side of AI — why the strongest performers resist hardest and how the centaur model reframes the partnership. Today we zoom out from the individual to the organization. Most AI initiatives fail not because of the technology but because three fundamental strategy questions were never answered. This toolkit helps you answer them for your context.
The organizations succeeding with AI aren't necessarily the ones with the best models or the biggest budgets. They're the ones that answered three questions before they bought anything — what problem are we solving, who owns the outcome, and what does success look like in 90 days. These aren't technology questions. They're leadership questions. And answering them requires making commitments that can be evaluated.
The bottleneck was never the model. It was the plan.
Most AI initiatives start with a solution — "we should use AI" — rather than a problem. This exercise reverses that.
Question 01
What is the specific friction, cost, delay, or risk you are trying to address?
Not "improve efficiency" or "leverage AI capabilities." Something specific.
Not: "We want to improve customer service"
Yes: "Our support team takes an average of 4 hours to respond to tier-1 queries and 60% of those queries are repetitive"
Question 02
What does that problem cost today?
In time, money, quality, risk, or customer experience. If you can't quantify it even roughly — the problem may not be specific enough yet.
Question 03
How will AI address this specifically?
Not "AI will make us more efficient." What specific AI capability addresses the specific problem you described?
Question 04
Why hasn't this been solved already?
If the problem is real and the solution is available — why hasn't it been addressed? Understanding the real barrier tells you whether AI is actually the right solution or whether the barrier is something else entirely.
Your Output — combine your answers into one statement
"We are using to solve which currently costs us . We haven't solved it before because ."
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Watch For This
If you can't answer Question 1 specifically — stop here. The initiative isn't ready to deploy. Going back to define the problem properly is not a delay. It's the work.
The most dangerous AI initiative is one with no definition of success. It can never be declared a failure — so it continues consuming budget and attention indefinitely.
Question 01
What will be measurably different in 90 days if this works?
One specific, observable, measurable thing. Not a list of improvements. One thing.
Question 02
How will you measure it?
What data will you look at? How often? Who is responsible for tracking it?
Question 03
What is the minimum viable signal of progress at 30 days?
90 days is too long to wait for the first signal. What will you check at 30 days to know whether you're on track or need to course correct?
Your Output — one success statement
"This initiative will be working if by . We will know at 30 days if . We will measure it by ."
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Watch For This
If you can't answer Question 1 with a single measurable outcome — the initiative scope is too broad. Narrow it until you can define one thing that will be different. Small and measurable beats large and vague every time.
Score your organization 1 to 5 on each dimension. 1 = Not in place · 3 = Partially in place · 5 = Fully in place. Your lowest scores are your highest priorities.
Problem Clarity
No specific problem defined — general ambition to adopt AI
Specific, well-defined problem with quantified impact
Ownership
No named owner — shared responsibility across teams
Named individual accountable for a specific business outcome
Success Definition
No definition of success — progress is undefined
Specific measurable success criterion with a 90-day timeline
Governance
No AI usage policies or data governance framework
Clear policies for AI usage, data handling, and risk management
Capability
No internal capability to build or maintain AI systems
Strong internal capability across build, deploy, and maintain
Data Readiness
Data is siloed, dirty, or ungoverned
Data is clean, accessible, and appropriately governed
Change Management
No plan for helping people adopt AI — technology deployed, change ignored
Structured change management plan alongside technology deployment
Measurement
No system for tracking AI performance or business impact
Robust measurement system tracking both technical and business outcomes
What Your Score Means
✓
32 to 40 — Strong Foundation
Focus on the lowest scoring dimensions. You have the foundation — now optimize the weak points.
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20 to 31 — Partial Foundation
Address dimensions scoring 2 or below before expanding your AI footprint. Growth on a weak foundation creates debt.
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Below 20 — Strategy Work First
More technology investment before strategy work is risk, not progress. Do the strategy work first.
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Your Challenge For Today
Complete Exercises 1 through 3 for one AI initiative — current or planned. If you can't answer the questions clearly, that's the signal. The initiative isn't ready to deploy. The strategy work comes first.
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A Note on Privacy and Security
- Use general descriptions rather than specific confidential business data when completing these exercises. The frameworks work with high-level answers.
- The ownership and accountability questions may surface sensitive organizational dynamics. Use this toolkit as a personal reflection tool first before sharing outputs more broadly.
Resources Worth Exploring
- Search "Jobs to be Done framework" — a powerful complement to Exercise 1 for defining the real problem
- Search "OKR framework" — Objectives and Key Results, directly applicable to Exercises 2 and 3
- Day 6 toolkit — the eight components of a production-ready AI system — a useful companion to the health check