OpenAI on Identifying AI Use Cases

⏱️ Your Morning Brief (TL;DR)

Welcome back,

While 92% of companies plan to increase AI investments, only 1% believe they've reached full maturity (BCG).

You’ve probably thought of a couple key use cases for your company, but what comes next?

And, how do you identify the right use cases and properly prioritize them?

To help, OpenAI recently published a report on Identifying and Scaling AI Use Cases after analyzing over 600 use cases from its customers.

This week, to save you time, we summarize everything in 5-minutes.

In this email, you’ll find:

• 3 key areas to identify AI opportunities

• 6 common building blocks of AI use cases

• 1 framework for prioritizing use cases

• 8 curated reads on AI

Let’s dive in 🔎

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 💡 This Week’s Deep Dive

3 Common Areas to Start with AI

OpenAI recommends to start looking at parts of your business that can be improved with AI, they offer three key areas:

1.  🔄 Repetitive Tasks Tedious: Manual work like summarizing meetings, analyzing spreadsheets, or creating routine documents.

2. 🧠 Skill Gaps: Where employees need specialized expertise, causing delays. For example, AI can help with data analysis, visualization, or coding.

3. 🧭 Ambiguity :When unclear challenges create roadblocks. AI can generate ideas, analyzes data, and suggests next steps.

The 6 Building Blocks of AI Use Cases

The report outlines the 6 fundamental use case types across all departments and disciplines.

Key Takeaways

• Identify opportunities by focusing on three critical areas: repetitive tasks that drain productivity, skill gaps that create bottlenecks, and ambiguous situations where employees struggle to move forward.

• Leverage the six building blocks of AI use cases that work across all departments.

📚 Interesting Reads

• Google: 601 real-world gen AI uses cases from the world’s leading organizations

• The State of Gen AI use in Canada 2025

• OpenAI report on AI in the Enterprise

• Middle Managers in the Age of AI

• The Atlantic - The Great AI Lock-in Has Begun

• Deloitte Principal Says Consultants 'Have to Be Technologists' First

• Ark Invest - AI Agents Could Transform Enterprise Spending

 🤔 AI Thoughts

OpenAI’s Impact/Effort framework for prioritizing AI use cases.

GPTLDR’s take - This 2x2 Impact/Effort matrix helps teams prioritize AI initiatives by categorizing use cases into four quadrants:

• Quick Wins: High impact, low effort. Best starting point to build momentum with strong ROI.

• Transformational: High impact, high effort. Worth pursuing after quick wins establish credibility.

• Self-service: Low impact, low effort. Individual solutions that may eventually scale across teams.

• Low-priority: Low impact, high effort. Safe to defer until AI capabilities advance.

The framework enables systematic evaluation to maximize value from limited resources, focusing first on high-ROI opportunities that create further interest and investment.

🗳️ This Week’s Poll

 ➜ Until Next Week

To break things down from this weeks newsletter, to maximize your AI investment, first identify opportunities by targeting three key areas. This includes repetitive tasks, bottlenecks, and situations that need additional guidance.

From there, ideate on solutions using the six simple building blocks of AI use cases.

Finally, use the Impact/Effort framework to prioritize quick wins that deliver immediate value while building momentum and credibility for more ambitious, transformational AI projects.

Stay curious,

The GPTLDR Team

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