Step 5 — Finding the Right First AI Use Case: The Key to Early Wins (1.5-Minute Read)
Part of the “Becoming AI-Ready” Series
Most AI programs fail not because of the technology —
but because the organization chooses the wrong first use case.
The right first use case is simple, measurable, high-impact, and easy to deploy.
The wrong one is broad, vague, and tied to “transformation.”
Here’s the practical framework I use with customers.
1. Focus on Friction, Not Fantasy
Don’t start with:
- “Reinvent our customer experience”
- “Automate everything”
- “Transform the business”
Start with:
- Slow processes
- Repetitive tasks
- High-volume work
- Areas with constant rework
- Work that drains teams
AI succeeds when it removes friction, not when it chases ambition.
2. Pick a Business Problem With a Clear Owner
Not IT. Not “the business.”
A specific department leader who wants the win.
Examples:
- Sales director wants faster proposal drafts
- Support manager wants case summarization
- HR lead wants consistent onboarding docs
- Finance wants automated reconciliations
If no one owns the outcome, the use case will die.
3. Choose Work That’s Already Digital
AI breaks when the workflow lives in:
- Verbal exchanges
- Paper
- Legacy apps with no integrations
- Tribal knowledge
Start where content already lives in Microsoft 365:
Teams, SharePoint, Outlook, OneDrive, Loop, Planner, etc.
4. Aim for “Small Win, Big Signal”
The best first use cases:
- Save time immediately
- Are visible across the org
- Build confidence
- Don’t require months of prep
- Create measurable improvement
Examples with quick ROI:
- Email drafting + summarization (Copilot for M365)
- Meeting recap automation
- Document standardization
- Ticket triage in support
- Policy or SOP generation
5. Validate Feasibility Fast
Before committing, check 3 things:
✔️ Is the data accessible and labeled?
Use sensitivity labels / DLP if needed:
https://learn.microsoft.com/en-us/purview/sensitivity-labels
✔️ Is the identity + access model clean?
Conditional Access overview:
https://learn.microsoft.com/en-us/entra/identity/conditional-access/overview
✔️ Is the workflow stable and well-defined?
AI works poorly on chaotic processes.
If these three aren’t true → pick another use case.
6. Define 2–3 Metrics to Prove Value
Examples:
- “Reduce time to draft proposals by 40%”
- “Cut meeting recap effort from 20 minutes to 2 minutes”
- “Reduce manual ticket triage by 30%”
Metrics turn AI from hype into evidence.
The Simple Truth
The right first AI use case is:
Small → Fast → Visible → Owned → Measurable.
Nail the first one, and adoption becomes a pull, not a push.
Next up:
Step 6 — Piloting AI: How to Measure, Iterate, and Scale the Right Way.
— Jean-Paul Abi Atme