AI Roadmap Workbook for Non-Technical Business Leaders
A straightforward, no-jargon workbook showing how AI can truly benefit your business — and where it may not be useful.
The Dev Guys – Mumbai — Think deeply. Build simply. Ship fast.
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:
• 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 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 clear order of initiatives instead of scattered trials.
Treat it as a lens, not a checklist. Your AI plan should be simple enough to explain in one meeting.
AI strategy is just business strategy — minus the buzzwords.
Step One — Focus on Business Goals
Focus on Goals Before Tools
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?
• 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
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.
• cloud infrastructure 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.
Rank and Select AI Use Cases
Evaluate Each Use Case for Business Value
Not every use case deserves action; prioritise by impact and feasibility.
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
Steer Clear of Predictable Failures
01. The Demo Illusion — excitement without strategy.
02. The Pilot Graveyard — endless pilots that never scale.
03. The Full Automation Fantasy — imagining instant department replacement.
Choose disciplined execution over hype.
Partnering with Vendors and Developers
Your role is to define the problem clearly, not design the model. State outcomes clearly — e.g., “reduce response time 40%”. Share messy data and edge cases so tech partners understand reality. 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?
• How will success be measured in 90 days?
• What’s the fallback insight?
The Calm Side of AI
Good AI brings order, not confusion. It’s not a list of tools — it’s an execution strategy. True AI integration supports your business invisibly.