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AI Roadmap Workbook for Non-Technical Business Leaders

A clear, hype-free 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. 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.

It guides you to make rational decisions about AI adoption without hype or hesitation.

You don’t need to understand AI models or algorithms — just your workflows, data, and decisions. AI should serve your systems, not the other way around.

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.
• A visible list of areas where AI won’t help — and that’s acceptable.
• A realistic, step-by-step project plan.

Use it for insight, not just as a template. If your CFO can understand it in a minute, you’re doing it right.

AI planning is business thinking without the jargon.

Starting Point: Business Objectives

Focus on Goals Before Tools

The usual focus on bots and models misses the real point. 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?

It should improve something tangible — speed, accuracy, or cost. If an idea doesn’t tie to these, it’s not a roadmap — it’s just an experiment.

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

Step Two — Map the Workflows

Understand the Flow Before Applying AI

Before deciding where AI fits, observe how work really flows — not how it’s described in meetings. Pose one question: “What happens between X starting and Y completing?”.

Examples include:
• New lead arrives ? assigned ? nurtured ? quoted ? revised ? finalised.
• 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.

Step 3 — Prioritise

Assess Opportunities with a Clear Framework

Choose high-value, low-effort cases first.

Think of a 2x2: impact on the vertical, effort on the horizontal.
• Quick Wins — high impact, low effort.
• Reserve resources for strategic investments.
• Minor experiments — do only if supporting larger goals.
• Avoid for Now — low impact, high effort.

Always judge the safety of automation before scaling.

Your roadmap starts with safe, effective wins.

Balancing Systems and People

Fix the Foundations Before You Blame the Model

Without clean systems, AI will mirror your chaos. Ask yourself: Is the data 70–80% complete? Are processes well defined?.

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

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.

Ask vendors for proof from similar businesses — and what failed first.

Evaluating AI Health

Indicators of a Balanced AI Plan

Your AI plan fits on one business slide.
Your focus remains on business, not tools.
Finance understands why these projects exist.

Quick AI Validation Guide

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?
• GCP 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.