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 — Smart thinking. Simple execution. Fast delivery.
Why This Workbook Exists
In today’s business world, leaders are often told they must 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.
• Declining AI entirely because of confusion or doubt.
It provides a third, smarter path — a clear, grounded way to find genuine AI opportunities.
Forget models and parameters — focus on how your business works. 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
Too often, leaders ask about tools instead of outcomes — that’s the wrong start. 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 decisions are delayed because information is hard to find?
AI matters when it affects measurable outcomes like profit or efficiency. 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
Before deciding where AI fits, observe how work really flows — not how it’s described in meetings. Ask: “What happens from start to finish in this process?”.
Examples include:
• Lead comes in ? assigned ? follow-up ? quote ? revision ? close/lost.
• Support ticket ? triaged ? answered ? escalated ? resolved.
• Invoice issued ? tracked ? escalated ? payment confirmed.
Inputs, actions, outputs — that’s the simple structure. Ideal AI zones: messy inputs, repeatable steps, consistent outputs.
Step Three — Choose What Matters
Evaluate Each Use Case for Business Value
Not every use case deserves action; prioritise by impact and feasibility.
Map your ideas to see where to start.
• Quick Wins: easy and powerful.
• Strategic Bets — high MVP Building impact, high effort.
• Optional improvements with minimal value.
• High cost, low reward — skip them.
Add risk as a filter: where can AI act safely, and where must humans approve?.
Your roadmap starts with safe, effective wins.
Foundations & Humans
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 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.
Transparency about failures reveals true expertise.
Signs of a Strong AI Roadmap
How to Know Your AI Strategy Works
It’s simple, measurable, and owned.
Buzzword-free alignment is visible.
Ownership and clarity drive results.
Essential Pre-Launch AI Questions
Before any project, confirm:
• What measurable result does it support?
• Is the process clearly documented in steps?
• Do we have data and process clarity?
• Where will humans remain in control?
• What is the 3-month metric?
• What’s the fallback insight?
Conclusion
Good AI brings order, not confusion. A real roadmap is a disciplined sequence of high-value projects that strengthen your best people. When AI becomes part of your workflow quietly, it stops being hype — it becomes infrastructure.