The Blog on RAG

Step-by-Step AI Guide for Non-Tech Business Owners


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A simple, practical workbook showing the real areas where AI adds value — and where it doesn’t.
The Dev Guys — Built with clarity, speed, and purpose.

Purpose of This Workbook


If you run a business today, you’re expected to “have an AI strategy”. All around, people are piloting, selling, or hyping AI solutions. But most non-tech business leaders face two poor choices:
• Agreeing to all AI suggestions blindly, expecting results.
• Rejecting all ideas out of fear or uncertainty.

It provides a third, smarter path — a clear, grounded way to find genuine AI opportunities.

Forget models and parameters — focus on how your business works. AI is only effective when built on your existing processes.

How to Use This Workbook


Either fill it solo or discuss it collaboratively. 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 1 — Business First


Begin with Results, Not Technology


The usual focus on bots and models misses the real point. 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 matters when it affects measurable outcomes like profit or efficiency. Only link AI to real, trackable business metrics.

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.
• Customer issue logged ? categorised ? responded ? closed.
• Invoice issued ? tracked ? escalated ? payment confirmed.

Every process involves what comes in, what’s done, and what moves forward. AI belongs where the data is chaotic, the task is repetitive, and the result is measurable.

Step Three — Choose What Matters


Score AI Use Cases by Impact, Effort, and Risk


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 RAG 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?.

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 Shiny Demo Trap — getting impressed by flashy demos with no purpose.
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


Non-tech leaders guide direction, not coding. 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?
• Which workflow is involved, and can it be described simply?
• Do we have data and process clarity?
• Where will humans remain in control?
• What is the 3-month metric?
• What’s the fallback insight?

Conclusion


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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