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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 — 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.
• 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. The aim isn’t to finish quickly but to think clearly. 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. 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.

Leaders who skip this step collect shiny tools; those who follow it build lasting leverage.

Step 2 — See the Work

Map Workflows, Not Tools

You must see the true flow of tasks, not the idealised version. Pose one question: “What happens between X starting and Y completing?”.

Examples include:
• New lead arrives ? assigned ? nurtured ? quoted ? revised ? finalised.
• AWS 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 belongs where the data is chaotic, the task is repetitive, and the result is measurable.

Step 3 — Prioritise

Score AI Use Cases by Impact, Effort, and Risk

Choose high-value, low-effort cases first.

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

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. As trust grows, expand autonomy gradually.

Common Traps

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 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?
• Which workflow is involved, and can it be described simply?
• Is the data complete enough for repetition?
• Who owns the human oversight?
• What is the 3-month metric?
• If it fails, what valuable lesson remains?

Final Thought

AI should make your business calmer, clearer, and more controlled — not noisier or chaotic. 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.

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