Identify an AI Use Case in 5 Steps

AI is a game-changer—but only if you apply it to the right problem. Too often, companies dive into AI just because it’s trendy, without a clear strategy. That’s why AI projects fail—not because the tech doesn’t work, but because it’s applied to the wrong problems in the wrong way.

This playbook is designed to help executives and business leaders cut through the noise, systematically identify high-value AI opportunities, and select the most impactful and feasible AI use cases.

Think of it as a practical, systematic approach to formulating real problems and identify AI-business use cases that are feasible and high-impact.

Let’s get started! 🚀

Step 1: Get Into the Right AI Mindset 🧠

AI isn’t magic—it’s a tool. And like any tool, success depends on how you use it.

To win with AI, you need to think big, start small, and scale fast. The best AI projects:
✔ Start with a small, focused experiment before expanding.
✔ Are measured by business impact, not just technical accuracy.
✔ Integrate into real workflows, not sit in a lab collecting dust.
✔ Are built with agility—AI isn’t a one-and-done solution; it needs continuous improvement.

The key takeaway? Don’t chase AI. Chase business value.

Now, let’s find the right problems AI can actually solve.

Step 2: Identify a Real Business Problem 🔍

If you’re asking, “Where can we use AI?”—stop.
The right question is, “What business problem needs solving?”

2.1. Find the Pain Points That AI Can Fix

Think about your organization. Where are things:
🚨 Too slow? (Long wait times, delays, manual processes)
💸 Too expensive? (High operational costs, wasted resources)
🤯 Too complicated? (Data-heavy decisions, unpredictable demand)
🔄 Inconsistent? (Quality varies, customer experiences fluctuate)

Examples of AI-Worthy Problems

✅ Loan approvals take too long → AI speeds up risk scoring.
✅ Customers abandon carts due to bad recommendations → AI personalizes suggestions.
✅ Manufacturing equipment fails unexpectedly → AI predicts breakdowns before they happen.

🎯 Your Action Step: Write down one frustrating process in your company that fits these patterns. That’s your AI starting point!

Step 3: Validate That AI is the Right Solution 🔬

Not every problem needs AI. Sometimes, better processes, automation, or analytics are enough. So, before jumping into AI, let’s check:

3.1. When Does AI Make Sense?

✅ AI is a good fit if:
✔ The problem involves lots of data (structured or unstructured).
✔ The task is repetitive, prediction-based, or requires pattern recognition.
✔ The outcome improves with automation, recommendation, or optimization.

🚫 AI is NOT a good fit if:
❌ The problem requires human intuition or creativity (e.g., brainstorming ad campaigns).
❌ There’s not enough historical data to train an AI model.
❌ The process is one-time or non-scalable.

🎯 Your Action Step: Check if your problem meets the AI Fit Criteria above.

🔹 Example Check:

If AI isn’t a good fit, don’t force it—find a better solution. If it is, move to feasibility testing.

Step 4: Prioritize the Best AI Use Cases 📊

Now that you’ve got a problem AI can solve, the next question is: Is it worth solving?

AI projects fail when they’re either too ambitious (huge cost, no clear ROI) or too small (not enough impact).

So, let’s evaluate AI use cases based on two key factors:
🟢 Business Impact (Will it drive revenue, reduce costs, or improve efficiency?)
⚫ Feasibility (Do we have the data, tech, and resources to build it?)

4.1. Score Your AI Ideas (AI Suitability Map Approach)

🎯 Your Action Step: Score your AI idea. If it’s high-impact and feasible, move forward. If it’s low-impact or too complex, rethink or refine it.

Step 5: Build a Strong AI Business Case 🚀

At this point, you’ve identified a real problem, confirmed AI is a good fit, and validated feasibility. Now it’s time to turn this into an actual business case.

5.1. AI Use Case Worksheet

AI Use Case: AI-Powered Real Estate Consulting Agent

Final AI Use Case Statement 📌

Problem: Homebuyers and investors struggle to find the right properties due to information overload and lack of market insights. The property search process is slow, requiring manual filtering and research by real estate agents.

AI Solution: An AI-powered real estate consulting agent that provides personalized property recommendations, market analysis, and automated consultation based on buyer preferences and historical market trends.

Expected Impact:
✔ 60% reduction in property search time → Faster transactions.
✔ 40% increase in lead conversion → More deals closed.
✔ 25% reduction in manual research costs → Higher agent efficiency.

Feasibility Check:
✅ Data Available: Property listings, buyer preferences, market trends, transaction history.
✅ Tech Feasibility: NLP for conversational AI, ML for pricing predictions, computer vision for property analysis.

Implementation Timeline: 3-6 months with phased rollout, starting with high-demand regions.

Final Takeaways: The AI Use Case Blueprint 🎯

✔ Step 1: Start with a real business problem—not AI for AI’s sake.
✔ Step 2: Validate whether AI is the best tool for the job.
✔ Step 3: Prioritize high-impact, feasible use cases to avoid wasted investment.
✔ Step 4: Build a clear AI business case with measurable outcomes.
✔ Step 5: Start small, test, iterate, and scale AI solutions that work.

🚀 AI is only valuable when applied to real, high-impact problems. Follow this playbook, and you’ll find AI opportunities that truly move the needle.

About the Author

Sam Obeidat: AI Strategy Expert, Technology Product Lead, Angel Investor, and a Futurist.

Sam Obeidat is an internationally recognized expert in AI strategy, a visionary futurist, and a technology product leader. He has spearheaded the development of cutting-edge AI technologies across various sectors, including education, fintech, investment management, government, defense, and healthcare.

With over 15,000 leaders coached and more than 31 AI strategies developed for governments and elite organizations in Europe, MENA, Canada, and the US, Sam has a profound impact on the global AI landscape. He is passionate about empowering leaders to responsibly implement ethical and safe AI, ensuring that humans remain at the center of these advancements.

Currently, Sam leads World AI X, where he and his team are dedicated to helping leaders across all sectors shape the future of their industries. They provide the tools and knowledge necessary for these leaders to prepare their organizations for the rapidly evolving AI-driven world and maintain a competitive edge.

Through World AI X, Sam runs a 6-week executive program designed to transform professionals into next-gen leaders within their domains. Additionally, he is at the forefront of the World AI Council, building a global community of leaders committed to shaping the future of AI.

Sam strongly believes that leaders and organizations from all sectors must be prepared to drive innovation and competitiveness in the AI future.

Connect with Sam Obeidat on LinkedIn

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