After the illusion: what enterprise AI must become
# What Enterprise AI Got Wrong (And How to Fix It) Companies have spent billions on AI tools that don't actually improve their bottom line because they've been treating AI like a helpful assistant you can plug into existing work, when what they really need is to redesign how work flows around AI from the ground up. The fundamental problem is that AI starts fresh with each question (it has no memory), while businesses depend on understanding past decisions and relationships over time. To make AI investments actually pay off, companies need to stop trying to make AI fit into old processes and instead rebuild their processes around what AI can actually do.
In a previous piece, I argued that large language models are not enterprise architecture. The response was clear: that argument is hard to dismiss. The harder question is what comes next: “if not this, then what?” It’s the right question. Because the problem was never that AI doesn’t work. It cl
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