How Much is it Worth For AI

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AI Roadmap Workbook for Non-Technical Business Leaders

A clear, hype-free workbook showing where AI can actually help your business — and where it won’t.
Dev Guys Team — 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 have to be technical; you just need to know your operations well. 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. 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 structured sequence of projects instead of random pilots.

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 1 — Business First

Begin with Results, Not Technology

Most AI discussions begin with tools and tech questions like “Can we use ChatGPT here?” — that’s backward. Start with measurable goals that truly impact your business.

Ask:
• What 3–5 business results truly matter this year?
• Which parts of the business feel overwhelmed or inefficient?
• 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

AI fits only once you understand the real workflow. Ask: “What happens from start to finish in this process?”.

Examples include:
• Lead comes in ? assigned ? follow-up ? quote ? revision ? close/lost.
• Customer issue logged ? categorised ? responded ? closed.
• 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

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

Use a mental 2x2 chart — cloud infrastructure 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.

Begin with low-risk, high-impact projects that build confidence.

Laying Strong Foundations

Data Quality Before AI Quality

Messy data ruins good AI; fix the base first. Clarity first, automation later.

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 Demo Illusion — excitement without strategy.
02. The Pilot Graveyard — endless pilots that never scale.
03. The Automation Mirage — expecting overnight change.

Define ownership, success, and rollout paths early.

Working with Experts

Your role is to define the problem clearly, not design the model. Focus on measurable results, not buzzwords. Expose real examples, not just ideal scenarios. Clarify success early and plan stepwise rollouts.

Transparency about failures reveals true expertise.

Signs of a Strong AI Roadmap

How to Know Your AI Strategy Works

It’s simple, measurable, and owned.
Buzzword-free alignment is visible.
Ownership and clarity drive results.

Essential Pre-Launch AI Questions

Before any project, confirm:
• What measurable result does it support?
• Is the process clearly documented in steps?
• Is the data complete enough for repetition?
• Where will humans remain in control?
• How will success be measured in 90 days?
• What’s the fallback insight?

The Calm Side of AI

AI done right feels stable, not overwhelming. It’s not a list of tools — it’s an execution strategy. When executed well, AI simply amplifies how you already win.

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