Why Enterprise AI Projects Fail and What Alteryx Is Doing Differently

Everyone says AI is the priority. Yet many projects are quietly failing. At Gartner D&A, I asked Christopher Moore, Global Sr. Director, AI & Platform at Alteryx, to be direct about why.

His answer was not about models. It was about execution. Too many AI initiatives are disconnected from real business workflows. They look good in a lab. They struggle in operations. We then got into a bigger tension inside enterprises. Business teams understand the problem best. But they rarely build the AI solutions themselves.

Why? Because the tooling has been too technical. Too fragmented. Too dependent on centralized teams. Christopher explained how Alteryx is trying to close that gap. Not by lowering standards, but by enabling governed, production-grade AI where business users already work. We also talked about what MCP server and Agentspace unlock for long time Alteryx users. In simple terms, it is about moving from isolated workflows to orchestrated AI systems. From analytics automation to agent-enabled automation.

And then we addressed the elephant in the room. Alteryx was once labeled shadow IT. That perception has shifted. In a world where AI governance is critical, the focus is now on controlled enablement. Visibility. Auditability. Guardrails built in.

The message was clear. Empowering business users does not mean losing governance. It means designing platforms that balance speed with control. If you are navigating the tension between innovation and oversight, this is a conversation you will want to watch.

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