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Getting new artificial intelligence (AI) tools up and running feels like a massive win for any company. It promises faster workflows, smarter insights, and a clear competitive edge. But the unsettling truth is that many AI initiatives stall, fail, or create more problems than they solve. When you look at the real data, the primary blockers aren’t the algorithms themselves. The breakdown almost always happens because of poor integration, a lack of structured training, and non-