Practical AI Roadmap Workbook for Business Executives
A simple, practical workbook showing the real areas where AI adds value — and where it doesn’t.
The Dev Guys — Built with clarity, speed, and purpose.
Purpose of This Workbook
Modern business leaders face pressure to adopt AI strategies. Everyone seems to be experimenting with, buying, or promoting something AI-related. But many non-technical leaders are caught between extremes:
• Saying “yes” to every vendor or internal idea, hoping some of it will succeed.
• Saying “no” to everything because it feels risky or confusing.
It guides you to make rational decisions about AI adoption without hype or hesitation.
You don’t have to be technical; you just need to know your operations well. AI is only effective when built on your existing processes.
How to Use This Workbook
Either fill it solo or discuss it collaboratively. The purpose is reflection, not speed. By the end, you’ll have:
• A short list of meaningful AI opportunities tied to profit or efficiency.
• A visible list of areas where AI won’t help — and that’s acceptable.
• A structured sequence of projects instead of random pilots.
Think of it as a guide, not a form. If your CFO can understand it in a minute, you’re doing it right.
AI planning is business thinking without the jargon.
Step 1 — Business First
Focus on Goals Before Tools
Too often, leaders ask about tools instead of outcomes — that’s the wrong start. Instead, begin with clear results that matter to your company.
Ask:
• What top objectives are driving your business now?
• Which parts of the business feel overwhelmed or inefficient?
• Which processes are slowed by scattered information?
It should improve something tangible — speed, accuracy, or cost. Only link AI to real, trackable business metrics.
Leaders who skip this step collect shiny tools; those who follow it build lasting leverage.
Step Two — Map the Workflows
Map Workflows, Not Tools
You must see the true flow of tasks, not the idealised version. Simply document every step from beginning to end.
Examples include:
• Lead comes in ? assigned ? follow-up ? quote ? revision ? close/lost.
• Support ticket ? triaged ? answered ? escalated ? resolved.
• Invoice generated ? sent ? reminded ? paid.
Every process involves what comes in, what’s done, and what moves forward. AI adds value where inputs are messy, actions are repetitive, and outputs are predictable.
Rank and Select AI Use Cases
Assess Opportunities with a Clear Framework
Choose high-value, low-effort cases first.
Use a mental 2x2 chart — impact vs effort.
• Quick Wins — high impact, low effort.
• Reserve resources for strategic investments.
• Minor experiments — do only if supporting larger goals.
• High cost, low reward — skip them.
Consider risk: some actions are reversible, others are not.
Begin with low-risk, high-impact projects that build confidence.
Balancing Systems and People
Fix the Foundations Before You Blame the Model
Without clean systems, AI will mirror your chaos. Ask yourself: Is the data 70–80% complete? Are processes well defined?.
Human Oversight Builds Trust
Keep people in the decision loop. Build confidence before full automation.
The 3 Classic Mistakes
Learn from Others’ Missteps
01. The Demo Illusion — excitement without strategy.
02. The Pilot Problem — learning without impact.
03. The Automation Mirage — expecting overnight change.
Choose disciplined execution over hype.
Working with Experts
Your role is to define the problem clearly, not design the model. State full stack product engineering outcomes clearly — e.g., “reduce response time 40%”. Expose real examples, not just ideal scenarios. Clarify success early and plan stepwise rollouts.
Ask vendors for proof from similar businesses — and what failed first.
Signs of a Strong AI Roadmap
Indicators of a Balanced AI Plan
You can summarise it in one slide linked to metrics.
Buzzword-free alignment is visible.
Finance understands why these projects exist.
The Non-Tech Leader’s AI Roadmap Checklist
Before any project, confirm:
• Which business metric does this improve?
• Which workflow is involved, and can it be described simply?
• Is the data complete enough for repetition?
• Where will humans remain in control?
• How will success be measured in 90 days?
• What’s the fallback insight?
The Calm Side of AI
AI should make your business calmer, clearer, and more controlled — not noisier or chaotic. It’s not a list of tools — it’s an execution strategy. When executed well, AI simply amplifies how you already win.