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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 — Think deeply. Build simply. Ship fast.

Purpose of This Workbook


Modern business leaders face pressure to adopt AI strategies. Everyone seems to be experimenting with, buying, or promoting something AI-related. But many non-technical leaders are caught between extremes:
• Saying “yes” to every vendor or internal idea, hoping some of it will succeed.
• Saying “no” to everything because it feels risky or confusing.

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 One — Focus on Business Goals


Focus on Goals Before Tools


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?

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.

Skipping this step leads to wasted tools; doing it right builds power.

Step Two — Map the Workflows


Visualise the Process, Not the Platform


AI fits only once you understand the real workflow. Simply document every step from beginning to end.

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.

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.

Add risk as a filter: where can AI act safely, and where must humans approve?.

Small wins set the foundation for larger bets.

Foundations & Humans


Data Quality Before AI Quality


AI projects fail more from poor data than bad models. Clarity first, automation later.

Design Human-in-the-Loop by Default


AI should draft, suggest, or monitor — not act blindly. Build confidence before full automation.

The 3 Classic Mistakes


Avoid the Three AI Traps for Non-Tech Leaders


01. The Demo Illusion — MVP Rescue 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


Frame problems, don’t build algorithms. Focus on measurable results, not buzzwords. Share messy data and edge cases so tech partners understand reality. Agree on success definitions and rollout phases.

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

Signals & Checklist


Indicators of a Balanced AI Plan


Your AI plan fits on one business slide.
Your focus remains on business, not tools.
Pilots have owners, success criteria, and CFO buy-in.

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?
• Is the data complete enough for repetition?
• Who owns the human oversight?
• How will success be measured in 90 days?
• 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 executed well, AI simply amplifies how you already win.

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