Why most of AI models may fail? 🤔

We've witnessed a remarkable surge in AI-driven initiatives across both public and private sectors, spearheaded by governments, big-tech, and start-ups. However, 85% of these AI initiatives don't reach their objectives. Why is that? Here are three key pitfalls:

1️⃣ Data Quality Mismatch: Even the most brilliant AI ideas need access to quality data to succeed. Without it, failure is inevitable.

2️⃣ RoI Timeline Mismatch: Even great AI solutions must often deliver returns in the short-term to survive. Integration into market or firm processes often takes longer and is more complex and costly than anticipated.

3️⃣ Product and Strategy Mismatch: AI should serve existing demand and/or enhance existing processes to provide clear, measurable value. Success hinges on a deep understanding of the product space and sector.

Think of AI solutions like capital investments. Evaluate them based on the value they bring to current processes, operations, cost structures, and demand. Especially when it comes to AI, it's not just about the technology—it's about how you use it! 💡

Why 85% Of Your AI Models May Fail