Step-by-Step AI Guide for Non-Tech Business Owners
A straightforward, no-jargon workbook showing where AI can actually help your business — and where it won’t.
The Dev Guys — Smart thinking. Simple execution. Fast delivery.
Purpose of This Workbook
If you run a business today, you’re expected to “have an AI strategy”. Everyone seems to be experimenting with, buying, or promoting something AI-related. But most non-tech business leaders face two poor choices:
• 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 need to understand AI models or algorithms — just your workflows, data, and decisions. AI should serve your systems, not the other way around.
How to Use 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.
• Recognition of where AI adds no value — and that’s okay.
• A structured sequence of projects instead of random pilots.
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.
Step 1 — Business First
Focus on Goals Before Tools
Most AI discussions begin with tools and tech questions like “Can we use ChatGPT here?” — that’s backward. Non-technical leaders should start from business outcomes instead.
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.
Skipping this step leads to wasted tools; doing it right builds power.
Step 2 — See the Work
Visualise the Process, Not the Platform
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 issued ? tracked ? escalated ? payment confirmed.
Every process involves what comes in, what’s done, and what moves forward. Ideal AI zones: messy inputs, repeatable steps, consistent outputs.
Step Three — Choose What Matters
Evaluate Each Use Case for Business Value
Not every use case deserves action; prioritise by impact and feasibility.
Think of a 2x2: impact on the vertical, effort on the horizontal.
• Focus first on small, high-impact changes.
• Strategic Bets — high impact, high effort.
• Nice-to-Haves — low impact, low effort.
• High cost, low reward — skip them.
Always judge the safety of automation before scaling.
Begin with low-risk, high-impact projects that build confidence.
Laying Strong Foundations
Fix the Foundations Before You Blame the Model
AI projects fail more from poor data than bad models. Ask yourself: Is the data 70–80% complete? Are processes well defined?.
Design Human-in-the-Loop by Default
Let AI assist, not replace, your team. Build confidence before full automation.
Avoid Common AI Pitfalls
Avoid the Three AI Traps for Non-Tech Leaders
01. The Demo Illusion — excitement without strategy.
02. The Pilot Problem — learning without impact.
03. The Full Automation Fantasy — imagining instant department replacement.
Choose disciplined execution over hype.
Collaborating with Tech Teams
Non-tech leaders guide direction, not coding. Focus on measurable results, not buzzwords. Share messy data and edge cases so tech partners understand reality. Agree on success definitions and rollout phases.
Transparency about failures reveals true expertise.
Evaluating AI Health
How to Know Your AI Strategy Works
Your AI plan fits on one business slide.
Your team discusses workflows and outcomes, not hype.
Ownership and clarity drive results.
Quick AI Validation Guide
Before any project, confirm:
• What measurable result does it support?
• Which workflow is involved, and can it be described simply?
• Is the data complete enough for repetition?
• Where will humans remain in control?
• What is the 3-month metric?
• What’s the fallback insight?
The Calm Side of AI
AI should make your business calmer, clearer, and more controlled — not noisier or chaotic. A Gen AI consulting real roadmap is a disciplined sequence of high-value projects that strengthen your best people. When executed well, AI simply amplifies how you already win.