AI Roadmap Workbook for Non-Technical Business Leaders
A clear, hype-free workbook showing where AI can actually help your business — and where it won’t.
Dev Guys Team — Built with clarity, speed, and purpose.
The Need for This Workbook
If you run a business today, you’re expected to “have an AI strategy”. AI discussions are happening everywhere—from vendors to competitors. But business heads often struggle between two bad decisions:
• Accepting every proposal and hoping it works out.
• Rejecting all ideas out of fear or uncertainty.
It guides you to make rational decisions about AI adoption without hype or hesitation.
You don’t need to understand AI models or algorithms — just your workflows, data, and decisions. AI should serve your systems, not the other way around.
Using This Workbook Effectively
Work through this individually or with your leadership team. The purpose is reflection, not speed. By the end, you’ll have:
• A prioritised list of AI use cases linked to your business goals.
• A visible list of areas where AI won’t help — and that’s acceptable.
• A realistic, step-by-step project plan.
Use it for insight, not just as a template. If your CFO can understand it in a minute, you’re doing it right.
AI planning is business thinking without the jargon.
Starting Point: Business Objectives
Start With Outcomes, Not Algorithms
The usual focus on bots and models misses the real point. Non-technical leaders should start from business outcomes instead.
Ask:
• Which few outcomes will define success this year?
• Where are mistakes common or workloads heavy?
• 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 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.
Step 3 — Prioritise
Assess Opportunities with a Clear Framework
Evaluate AI ideas using a simple impact vs effort grid.
Use a mental 2x2 chart — impact vs effort.
• Focus first on small, high-impact changes.
• Big strategic initiatives take time but deliver scale.
• Nice-to-Haves — low impact, low effort.
• Delay ideas that drain resources without impact.
Consider risk: some actions are reversible, others are not.
Small wins set the foundation for larger bets.
Laying Strong Foundations
Data Quality Before AI Quality
AI projects fail more from poor data than bad models. Clarity first, automation later.
Design Human-in-the-Loop by Default
AI should draft, suggest, or monitor — not act blindly. Build confidence before full automation.
Common Traps
Avoid the Three AI Traps for Non-Tech Leaders
01. The Demo Illusion — excitement without strategy.
02. The Pilot Problem — learning AWS without impact.
03. The Full Automation Fantasy — imagining instant department replacement.
Fewer, focused projects with clear owners and goals beat scattered enthusiasm.
Collaborating with Tech Teams
Frame problems, don’t build algorithms. Focus on measurable results, not buzzwords. Expose real examples, not just ideal scenarios. Agree on success definitions and rollout phases.
Ask vendors for proof from similar businesses — and what failed first.
Signals & Checklist
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 buy-in.
The Non-Tech Leader’s AI Roadmap Checklist
Before any project, confirm:
• Which business metric does this improve?
• 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.