Practical AI Roadmap Workbook for Business Executives
A clear, hype-free 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 provides a third, smarter path — a clear, grounded way to find genuine AI opportunities.
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. It’s not about completion — it’s about clarity. 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 top objectives are driving your business now?
• Which parts of the business feel overwhelmed or inefficient?
• Where do poor data or slow insights hold back progress?
It should improve something tangible — speed, accuracy, or cost. If an idea doesn’t tie to these, it’s not a roadmap — it’s just an experiment.
Skipping this step leads to wasted tools; doing it right builds power.
Step Two — Map the Workflows
Visualise the Process, Not the Platform
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 generated ? sent ? reminded ? paid.
Each step has three parts: inputs, actions, outputs. AI adds value where inputs are messy, actions are repetitive, and outputs are predictable.
Step 3 — Prioritise
Assess Opportunities with a Clear Framework
Evaluate AI ideas using a simple impact vs effort grid.
Think of a 2x2: impact on the vertical, effort on the horizontal.
• Quick Wins — high impact, low effort.
• Reserve resources for strategic investments.
• Minor experiments — do only if supporting larger goals.
• Delay ideas that drain resources without impact.
Consider risk: some actions are reversible, others are not.
Begin with low-risk, high-impact projects that build confidence.
Laying Strong Foundations
Fix the Foundations Before You Blame the Model
Messy data ruins good AI; fix the base first. Ask yourself: Is the data 70–80% complete? Are processes well defined?.
Keep Humans in Control
Keep people in the decision loop. As trust grows, expand autonomy gradually.
Avoid Common AI Pitfalls
Learn from Others’ Missteps
01. The Shiny Demo Trap — getting impressed by flashy demos with no purpose.
02. The Pilot Graveyard — endless pilots that never scale.
03. The Automation Mirage — expecting overnight change.
Define ownership, success, and rollout paths early.
Working with Experts
Your role is to define the problem clearly, not design the model. State outcomes clearly — e.g., “reduce response time 40%”. Expose real examples, not just ideal scenarios. Clarify success early and plan stepwise rollouts.
Transparency about failures reveals true expertise.
Signs of a Strong AI Roadmap
Signs Your AI Roadmap Is Actually Healthy
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 MVP Building 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?
• Who owns the human oversight?
• 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.