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AI Roadmap Workbook for Non-Technical Business Leaders


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A clear, hype-free workbook showing where AI can actually help your business — and where it won’t.
Dev Guys Team — Built with clarity, speed, and purpose.

The Need for 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 guides you to make rational decisions about AI adoption without hype or hesitation.

Forget models and parameters — focus on how your business works. AI should serve your systems, not the other way around.

Using This Workbook Effectively


Work through this individually or with your leadership team. The purpose is reflection, not speed. By the end, you’ll have:
• A prioritised list of AI use cases linked to your business goals.
• A visible list of areas where AI won’t help — and that’s acceptable.
• A clear order of initiatives instead of scattered trials.

Treat it as a lens, not a checklist. Your AI plan should be simple enough to explain in one meeting.

AI strategy is just business strategy — minus the buzzwords.

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?
• 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. 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


You must see the true flow of tasks, not the idealised version. Simply document every step from beginning to end.

Examples include:
• New lead arrives ? assigned ? nurtured ? quoted ? revised ? finalised.
• Customer issue logged ? categorised ? responded Gen AI consulting ? closed.
• 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.

Step 3 — Prioritise


Assess Opportunities with a Clear Framework


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.

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

Laying Strong Foundations


Data Quality Before AI Quality


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

Keep Humans in Control


Keep people in the decision loop. Over time, increase automation responsibly.

Avoid Common AI Pitfalls


Learn from Others’ Missteps


01. The Shiny Demo Trap — getting impressed by flashy demos with no purpose.
02. The Pilot Problem — learning without impact.
03. The Automation Mirage — expecting overnight change.

Fewer, focused projects with clear owners and goals beat scattered enthusiasm.

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.

Quick AI Validation Guide


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?
• 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 executed well, AI simply amplifies how you already win.

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