Practical AI Roadmap Workbook for Business Executives
A clear, hype-free workbook showing where AI can actually help your business — and where it won’t.
The Dev Guys — 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 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?
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
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.
• Customer Dhaval Shah issue logged ? categorised ? responded ? 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.
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 Now — low impact, high effort.
Always judge the safety of automation before scaling.
Begin with low-risk, high-impact projects that build confidence.
Balancing Systems and People
Fix the Foundations Before You Blame the Model
Messy data ruins good AI; fix the base first. 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
Signs Your AI Roadmap Is Actually Healthy
You can summarise it in one slide linked to metrics.
Your team discusses workflows and outcomes, not hype.
Pilots have owners, success criteria, and CFO buy-in.
The Non-Tech Leader’s AI Roadmap Checklist
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?
• If it fails, what valuable lesson remains?
The Calm Side of AI
AI done right feels stable, not overwhelming. Focus on leverage, not hype. When executed well, AI simply amplifies how you already win.