Enterprise AI adoption is moving toward agentic workflows, autonomous operations, and physical AI, yet many organizations still struggle to connect emerging tools with the data required to make them useful. In the final installment of this three-part series, Kyle DuPont, Founder and CEO of DataXray (Ohalo), speaks with Maribeth Achterberg, CDO Magazine Editorial Board Member, about the organizational work required to move from experimentation to action.

DuPont describes why enterprise technology diffusion can take months and why special operations teams can create room for faster testing outside normal processes. The conversation then turns to unstructured data as a foundation for AI, with a practical starting point for organizations that need safeguards around sensitive or operational information.

The discussion explores:

• Enterprise AI execution: Faster experimentation depends on creating room to test emerging capabilities without waiting through every standard process.
• Data understanding: AI initiatives require a clear view of where data resides and what the data means before organizations can act on it.
• Organizational safeguards: Data priorities can include security, operations, intellectual property, factory information, and HR records, depending on the organization.
• Leadership engagement: DuPont describes how CDO and CISO conversations are shaping work around unstructured data and AI.

As the concluding installment, the conversation brings the series back to a practical question: how can organizations structure unstructured data so AI initiatives have the context needed to move forward? The final discussion also connects AI experimentation with physical AI and the growing need to give enterprise systems usable context.

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