Practical AI Roadmap Workbook for Business Executives
A straightforward, no-jargon workbook showing how AI can truly benefit your business — and where it may not be useful.
The Dev Guys – Mumbai — 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. 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.
Forget models and parameters — focus on how your business works. 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 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.
Treat it as a lens, not a checklist. If your CFO can understand it in a minute, you’re doing it right.
AI strategy is just business strategy — minus the buzzwords.
Step One — Focus on Business Goals
Start With Outcomes, Not Algorithms
Too often, leaders ask about tools instead of outcomes — that’s the wrong start. Start with measurable goals that truly impact your business.
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
AI fits only once you understand the real workflow. Ask: “What happens from start to finish in this process?”.
Examples include:
• Lead comes in ? assigned ? follow-up ? quote ? revision ? close/lost.
• Customer issue logged ? categorised ? responded ? closed.
• 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 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?.
Small wins set the foundation for larger bets.
Foundations & Humans
Get the Basics Right First
AI projects fail more from poor data than bad models. 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.
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 RAG 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.