David's Digest
AI in Enterprise: What Actually Works vs What Fails
A practical breakdown of what drives success in enterprise AI and why most initiatives stall before delivering value.
--- --- There is a growing gap between how AI is marketed and how it actually performs inside enterprise environments. On the surface, everything looks promising. In reality, most initiatives stall because they lack clear objectives, clean data, and a path to integration. What works is not complicated, but it does require discipline. Teams that succeed focus on outcomes, start small, and build solutions that fit into real workflows from day one. **What actually works** - Define the outcome before selecting tools - Start small and prove value early - Build into real workflows, not side projects - Ensure data quality before scaling - Assign clear ownership
**What consistently fails** - Chasing AI trends without a use case - Overengineering too early - Ignoring data readiness - Lack of accountability - No integration plan
Closing Thought
AI is not a shortcut. It amplifies whatever system you already have. If execution is weak, AI will expose it. If execution is strong, AI will accelerate it.
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I share practical insights on AI, cloud, and execution through David’s Digest, focused on what actually works in real-world environments. If you are building in this space, this is exactly the kind of work I focus on. Have fun, but be the best. David Campodonico MBA/PMP