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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:
• 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 need to understand AI models or algorithms — just your workflows, data, and decisions. AI is simply a tool built on top of those foundations.

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.
• Understanding of where AI should not be used.
• A clear order of initiatives instead of scattered trials.

Think of it as a guide, not a form. A good roadmap fits on one slide and makes sense to your CFO.

AI planning is business thinking without the jargon.

Starting Point: Business Objectives

Focus on Goals Before Tools

Most AI discussions begin with tools and tech questions like “Can we use ChatGPT here?” — that’s backward. Instead, begin with clear results that matter to your company.

Ask:
• What top objectives are driving your business now?
• Where are teams overworked or error-prone?
• Which decisions are delayed because information is hard to find?

AI is valuable only when it moves key metrics — revenue, margins, time, or risk. Ideas without measurable outcomes belong in the experiment bucket.

Skipping this step leads to wasted tools; doing it right builds power.

Step 2 — See the Work

Understand the Flow Before Applying AI

AI fits only once you understand the real workflow. Pose one question: “What happens between X starting and Y completing?”.

Examples include:
• Lead comes in ? assigned ? follow-up ? quote ? revision ? close/lost.
• Support ticket ? triaged ? answered ? escalated ? resolved.
• Invoice issued ? tracked ? escalated ? payment confirmed.

Each step has three parts: inputs, actions, outputs. Ideal AI zones: messy inputs, repeatable steps, consistent outputs.

Step Three — Choose What Matters

Assess Opportunities with a Clear Framework

Not every use case deserves action; prioritise by impact and feasibility.

Map your ideas to see where to start.
• Focus first on small, high-impact changes.
• Strategic Bets — high impact, high effort.
• Minor experiments — do only if supporting larger goals.
• Avoid for Now — low impact, high effort.

Consider risk: some actions are reversible, others RAG are not.

Your roadmap starts with safe, effective wins.

Balancing Systems and People

Data Quality Before AI Quality

Without clean systems, AI will mirror your chaos. Clarity first, automation later.

Human Oversight Builds Trust

Keep people in the decision loop. Over time, increase automation responsibly.

Avoid Common AI Pitfalls

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.

Choose disciplined execution over hype.

Working with Experts

Frame problems, don’t build algorithms. Focus on measurable results, not buzzwords. Expose real examples, not just ideal scenarios. Agree on success definitions and rollout phases.

Transparency about failures reveals true expertise.

Signals & Checklist

How to Know Your AI Strategy Works

You can summarise it in one slide linked to metrics.
Buzzword-free alignment is visible.
Pilots have owners, success criteria, and CFO buy-in.

Quick AI Validation Guide

Before any project, confirm:
• What measurable result does it support?
• 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?

Final Thought

Good AI brings order, not confusion. A real roadmap is a disciplined sequence of high-value projects that strengthen your best people. True AI integration supports your business invisibly.