Rob Llewellyn walks through five steps for finding AI projects that actually matter to your business. Start by understanding your real problems, then brainstorm solutions, evaluate what's feasible, and build the case for investment.
Are you struggling to figure out where AI fits in your organization? Well, you're not alone. I'm Rob Lewelyn, and today I'm going to show you how to develop AI use cases that actually make sense for your organization. Every day I see companies rushing to implement AI without a clear plan, wasting time and resources on projects that don't deliver value. But here's the good news. Developing strong AI use cases isn't as complicated as you might think. Let's break it down into five clear steps, and I'll share some insider tips that I've learned from working with hundreds of organizations. So step one is all about understanding your business problems. You need to talk to your team leaders, find out what's slowing them down, and spot those repetitive tasks that eat up valuable time. Look especially for those processes where people are spending hours crunching numbers or making repetitive decisions. Think about where better insights could help you make smarter decisions. Step number two is where we get creative with solutions. Look at what other companies in your industry are doing with AI, but don't copy them. Your organization is unique and your AI solutions should be, too. This is also where you need to think about what type of AI might work best. Whether it's machine learning for predictions, natural language processing for document handling, or perhaps computer vision for image analysis. And don't forget about your data. You'll need to consider what data you have, what you need, and whether it's actually good enough quality. Now, here's something that most people don't tell you. The best AI use cases often come from unexpected places. Step three is evaluation, and it's critical. Ask yourself, will this really.
