Federal AI Regulation Takes Center Stage
The U.S. government's push for a cohesive national AI regulatory framework reflects a transformative moment in the AI landscape, prioritizing safety, compliance, and bias mitigation. This shift signals a commitment to establishing standardized protocols, which could reshape how AI solutions are developed and deployed, benefiting responsible vendors while challenging those resistant to oversight. As federal procurement guidelines evolve, companies will need to adapt or risk losing access to lucrative government contracts and market credibility.
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White House adviser says US will push Congress for a single national AI regulatory framework
The White House said it plans to work with Congress to create a single, nationwide framework to regulate AI, arguing that a patchwork of state rules could slow down deployment and weaken US competitiveness. The comments came from White House adviser Sriram Krishnan in an interview, framing federal action as both pro-innovation and strategically necessary. The deeper subtext is that Washington is trying to stabilize the policy surface area for frontier-model builders and downstream adopters—reducing compliance fragmentation while keeping leverage for national-security guardrails. If this effort turns into legislation (not just executive actions), it could reshape how enterprise AI is rolled out across highly regulated sectors like finance, healthcare, and critical infrastructure.
US to require AI vendors to measure political bias to sell LLMs to federal agencies
The Trump administration is tightening procurement rules for generative AI: vendors will need to measure and report political “bias” in large language models to be eligible for U.S. federal sales (with national security systems carved out). The move operationalizes earlier direction to avoid buying AI systems the administration frames as ideologically “woke,” and it effectively turns bias measurement into a gatekeeping compliance requirement for major government contracts. Practically, this raises the bar for model evaluation tooling and documentation, and could nudge vendors toward more standardized test suites (or at least defensible methodologies) for neutrality, factuality, and “truth-seeking.” The bigger impact is market-shaping: the U.S. government is a huge customer, so procurement checklists often become de facto industry standards—especially for enterprise deployments that mirror federal requirements. Expect a second-order fight over definitions (what counts as bias, which benchmarks, and how to prevent the metric from becoming performative).
Seekr launches SeekrGuard to evaluate AI models for compliance with U.S. AI Action Plan
U.S.-based Seekr introduced SeekrGuard, an AI evaluation and certification platform designed to help government agencies and enterprises test AI models for bias, accuracy, reliability and security risks in line with the President’s AI Action Plan. The system combines custom evaluators, penetration testing and transparent scoring to create audit‑ready evidence for high‑stakes AI deployments, positioning Seekr as an emerging player in the AI safety and assurance ecosystem.
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📅 Event Timeline2 events
New procurement rules for AI vendors to measure political bias
This regulatory decision impacts how AI vendors operate and sell to federal agencies.
Seekr launches SeekrGuard for AI model compliance evaluation
The launch of SeekrGuard introduces a new tool for compliance testing in AI, relevant for government and enterprises.