
Enterprises can quickly build AI agents with frameworks like NVIDIA NeMo, but demos mask a deeper problem. While models now meet capability thresholds, production failures stem from a lack of programmatic control and governance. The article argues that trust requires a separate policy layer to evaluate and audit decisions before execution. Without such control, AI projects stall despite impressive demos.

HyperFRAME’s 1H 2026 enterprise AI survey of 544 firms shows only 22.8 % of AI/ML projects launched in the past year are successfully deployed and meeting ROI, leaving a 77 % execution gap. The data, released openly without gating, highlights that most failures...

The Pentagon’s demand that Anthropic’s AI models be usable for all lawful purposes collided with the company’s refusal to support mass surveillance and fully autonomous weapons, sparking a supply‑chain‑risk designation and a legal showdown. The dispute highlights a clash between...