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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 — Think deeply. Build simply. Ship fast.

Why This Workbook Exists

Modern business leaders face pressure to adopt AI strategies. AI discussions are happening everywhere—from vendors to competitors. But many non-technical leaders are caught between extremes:
• Accepting every proposal and hoping it works out.
• 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 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.

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. Only link AI to real, trackable business metrics.

Start here, and you’ll invest in leverage — not novelty.

Step 2 — See the Work

Map Workflows, Not Tools

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 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.

Rank and Select AI Use Cases

Evaluate Each Use Case for Business Value

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.
• MVP Building 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.

Fewer, focused projects with clear owners and goals beat scattered enthusiasm.

Working with Experts

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 focus remains on business, not tools.
Finance understands why these projects exist.

The Non-Tech Leader’s AI Roadmap Checklist

Before any project, confirm:
• Which business metric does this improve?
• Which workflow is involved, and can it be described simply?
• Do we have data and process clarity?
• Who owns the human oversight?
• What is the 3-month metric?
• If it fails, what valuable lesson remains?

Conclusion

AI should make your business calmer, clearer, and more controlled — not noisier or chaotic. It’s not a list of tools — it’s an execution strategy. True AI integration supports your business invisibly.

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