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AI Roadmap Workbook for Non-Technical Business Leaders


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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.

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.

Best Way to Apply This Workbook


You can complete this alone or with your management team. 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.

Think of it as a guide, not a form. Your AI plan should be simple enough to explain in one meeting.

AI strategy equals good business logic, simply expressed.

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:
• What 3–5 business results truly matter this year?
• Where are mistakes common or workloads heavy?
• 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.
• 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


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.
• 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


Messy data ruins good AI; fix the base first. 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


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.

Define ownership, success, and rollout paths early.

Working with Experts


Your role is to define the problem clearly, not design the model. State outcomes clearly — e.g., “reduce response time 40%”. 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 Enterprise Automation 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?

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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