In this episode of National Energy Talk, data² CEO Jon Brewton explains why trust is the biggest barrier to enterprise AI adoption and how data² solved it with the world's first patented, hallucination-resistant, explainable AI platform.

Jon breaks down why traditional AI systems fail in regulated, high-stakes industries like energy, finance, and government. Black-box models, disconnected data, and unverifiable outputs create real financial, operational, and compliance risk. data² takes a fundamentally different approach, grounding AI decisions in graph-based reasoning with full traceability back to source data.

The conversation explores how explainable AI (eXAI) enables faster audits, multi-million-dollar cost recovery, and decision-grade intelligence leaders can defend in boardrooms and regulatory reviews.

Inside the episode:

• Why black-box AI breaks down under regulatory scrutiny

• How patented explainability and graph reasoning deliver auditable results

• Real outcomes across energy, finance, and government

• Why transparency is now non-negotiable for enterprise AI

If your organization depends on clarity, traceability, and confidence, this episode defines what trustworthy AI should be.

Listen to Podcast: data² CEO Jon Brewton Announces AI Patent, Discusses Cutting-Edge Data Infrastructure on National Energy Talk