AI Roadmap Workbook for Non-Technical Business Leaders
A simple, practical workbook showing the real areas where AI adds value — and where it doesn’t.
The Dev Guys — Think deeply. Build simply. Ship fast.
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.
• Declining AI entirely because of confusion or doubt.
This workbook offers a balanced third option: a calm, realistic way to identify where AI truly fits in your business — and where it doesn’t.
You don’t have to be technical; you just need to know your operations well. AI is simply a tool built on top of those foundations.
Best Way to Apply This Workbook
You can complete this alone or with your management team. The aim isn’t to finish quickly but to think clearly. By the end, you’ll have:
• A short list of meaningful AI opportunities tied to profit or efficiency.
• Understanding of where AI should not be used.
• A structured sequence of projects instead of random pilots.
Think of it as a guide, not a form. A good roadmap fits on one slide and makes sense to your CFO.
AI strategy equals good business logic, simply expressed.
Step 1 — Business First
Begin with Results, Not Technology
Most AI discussions begin with tools and tech questions like “Can we use ChatGPT here?” — that’s backward. Instead, begin with clear results that matter to your company.
Ask:
• What 3–5 business results truly matter this year?
• Which parts of the business feel overwhelmed or inefficient?
• Which processes are slowed by scattered information?
AI is valuable only when it moves key metrics — revenue, margins, time, or risk. Ideas without measurable outcomes belong in the experiment bucket.
Start here, and you’ll invest in leverage — not novelty.
Understand How Work Actually Happens
Understand the Flow Before Applying AI
AI fits only once you understand the real workflow. Simply document every step from beginning to end.
Examples include:
• New lead arrives ? assigned ? nurtured ? quoted ? revised ? finalised.
• Customer issue logged ? categorised ? responded ? closed.
• Invoice issued ? tracked ? escalated ? payment confirmed.
Every process involves what comes in, what’s done, and what moves forward. AI belongs where the data is chaotic, the task is repetitive, and the result is measurable.
Step Three — Choose What Matters
Score AI Use Cases by Impact, Effort, and Risk
Choose high-value, low-effort cases first.
Map your ideas to see where to start.
• Quick Wins: easy and powerful.
• Strategic Bets — high impact, high effort.
• Optional improvements with minimal value.
• Avoid for Now — low impact, high effort.
Always judge the safety of automation before scaling.
Your roadmap starts with safe, effective wins.
Balancing Systems and People
Get the Basics Right First
Without clean systems, AI will mirror your chaos. Check data completeness, process clarity, and alignment.
Human Oversight Builds Trust
Let AI assist, not replace, your team. Over time, increase automation responsibly.
The 3 Classic Mistakes
Avoid the Three AI Traps for Non-Tech Leaders
01. The Shiny Demo Trap — getting impressed Enterprise Automation by flashy demos with no purpose.
02. The Pilot Problem — learning without impact.
03. The Automation Mirage — expecting overnight change.
Fewer, focused projects with clear owners and goals beat scattered enthusiasm.
Collaborating with Tech Teams
Non-tech leaders guide direction, not coding. Focus on measurable results, not buzzwords. 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.
Signals & Checklist
How to Know Your AI Strategy Works
You can summarise it in one slide linked to metrics.
Your team discusses workflows and outcomes, not hype.
Pilots have owners, success criteria, and CFO buy-in.
The Non-Tech Leader’s AI Roadmap Checklist
Before any project, confirm:
• What measurable result does it support?
• Is the process clearly documented in steps?
• Is the data complete enough for repetition?
• Where will humans remain in control?
• How will success be measured in 90 days?
• If it fails, what valuable lesson remains?
The Calm Side of AI
AI done right feels stable, not overwhelming. Focus on leverage, not hype. When executed well, AI simply amplifies how you already win.