you.com - AI Use Case Discovery Whitepaper

Why Use Case Discovery Matters

AI transformation is not just about technology—it starts with identifying the most valuable use cases.

Many organizations fail because they:

• Focus on vague ambitions or “shiny” AI capabilities

• Don’t tie AI to real business problems

Successful AI adoption begins with:

• Identifying what’s not working

• Understanding why it’s happening

• Aligning teams around clear opportunities (Scribd)

Types of Challenges

Internal

• Back-office automation

• Employee workflows

• Knowledge management

• Operational efficiency

External

• Customer support

• Personalization

• Digital product experiences

• Engagement across channels (Scribd)

---

The Unified Use Case Discovery Framework

A 5-step framework for identifying AI opportunities:

1. Establish processes

2. Brainstorm use cases

3. Map journeys & workflows

4. Capture structured use cases

5. Prioritize holistically (Scribd)

---

1. Establish Processes

Collecting use cases is only half the work—how you gather them matters.

Best Practices

• Invite diverse stakeholders

  • Product, business, tech, support, marketing, customers

• Use a template

  • Standardize how use cases are captured

• Push for specificity

  • Avoid vague ideas—focus on real workflows

• Encourage storytelling

  • “Day in the life” scenarios

• Document nuance

  • Workarounds, edge cases, tribal knowledge (Scribd)

---

2. Brain Dump Ideas (Internal Vs External)

Generate ideas freely, then organize them into two buckets:

Internal Processes

Look for:

• Repetitive, rules-based tasks

• Bottlenecks and inefficiencies

Examples:

• Contract review

• HR onboarding

• Invoice processing

• Compliance checks

External Processes

Focus on customer interactions:

Examples:

• Customer support automation

• Intelligent search

• Digital onboarding

• Product recommendations

• Personalization

• In-app assistants (Scribd)

---

3. Map Customer Journeys & Business Processes

Map use cases to real workflows.

External (Customer Journey)

• Awareness → onboarding → engagement → support → retention

• Identify:

  • Friction points

  • Opportunities for delight

  • Causes of churn

Internal

• Talk to teams directly

• Identify:

  • Inefficiencies

  • Automation opportunities

  • High-volume or “long-tail” tasks

👉 Key principle:

Tie every use case to a specific workflow and pain point (Scribd)

---

4. Capture Structured Use Cases

Use a standardized worksheet to define each use case:

Use Case Template

• Problem Statement What’s the pain or opportunity?

• Who is Impacted? Roles, departments, or customer segments

• Persona / Segment Target user type

• Sample Tasks / Queries Example actions (e.g., “Reset password”)

• Touchpoints / Channels App, chatbot, email, portal, etc.

• Business / Experience Benefit Time saved, revenue, satisfaction, NPS

• Volume / Frequency Usage scale

• Current Process / Pain Existing workflow issues

• Potential Risks Compliance, accuracy, brand risk

• Strategic Priority Alignment with company goals

• Feasibility Data + system readiness (Scribd)

---

Example Use Case

Field	Internal Example	Customer Example
Problem	Expense processing is slow	Customers can’t get product advice
Impacted	Finance team	End customers
Persona	Accounts payable clerk	Shoppers
Tasks	”Is this expense valid?"	"Best product for me?”
Channels	Portal, email	App, chatbot
Benefit	Faster processing, cost savings	Higher conversion, NPS
Volume	200/week	10,000/month
Pain	Manual, error-prone	Poor search experience
Risks	Fraud, compliance	Wrong recommendations
Priority	Medium	High
Feasibility	Data available	Needs content access

---

5. Prioritize Holistically

Evaluate each use case across four dimensions:

1. Impact

• Business value

• Cost savings

• Customer experience

2. Feasibility

• Data availability

• Technical complexity

3. Risk

• Compliance

• Brand impact

• Operational risk

4. Strategic Alignment

• Fit with company goals (Scribd)

Tip

Start with:

• Quick wins

• Internal automation Then expand to:

• More complex, customer-facing solutions

---

Key Takeaways

• AI success depends on clear, valuable use cases

• Use a structured, repeatable discovery process

• Involve cross-functional stakeholders

• Balance:

  • Impact

  • Feasibility

  • Risk

• Start small, then scale

---

Final Thought

A disciplined discovery process is the foundation of AI success.

The journey to AI maturity begins with asking the right questions and capturing the right details. (Scribd)

---

If you want, I can:

• Turn this into a Notion template

• Convert it into a workshop playbook

• Or extract ready-to-use prompts for AI use case discovery sessions