The biggest mistake enterprise companies make when trying to implement AI? Ru ing too fast without a strategy. David Rabin from Lenovo's Solutions & Services Group dropped this truth bomb during our conversation. He's been helping companies build right-sized AI solutions, and he's seen the pattern over and over. Here's what stuck with me. As a solopreneur, you can experiment wildly with AI tools. Break things. Learn fast. But in an enterprise with thousands of employees? That cowboy approach creates chaos. Lenovo built an AI committee that does two things:n• **Manages governance** - Someone needs to own the rulesn• **Evaluates tools constantly** - With 1,000+ marketers, they can't have everyone using different AI platforms But here's the paradox David shared: "You gotta start. You ca ot wait." Wait, what? So you need process AND speed? That feels impossible. Until he explained their approach: **Garbage in, garbage out.** If your data is a mess, AI amplifies that mess. Lenovo organized their product databases, visual identity guidelines, and image libraries BEFORE implementing their Studio AI tool. **Define "good enough."** David's not expecting AI to match a $25,000 agency campaign that took two weeks. He wants faster and cheaper first. Better comes with iteration. **Think beyond today.** We're in the generative AI era, but agentic AI is coming. David envisions telling their AI: "We're launching a product in 30 days." A week later, the complete marketing toolkit appears in their inbox. No prompting needed. The real mistake? Not starting. Because while you're perfecting your AI strategy, your competitors are already learning from their mistakes. What's your take - is it better to move fast and break things, or build the perfect foundation first? If you'd like to hear my conversation with David Rabin on the MarTech Podcast, let me know in the comments and I'll share a link.