AI Policy

Washington has a clean political divide on AI: Trump says full speed ahead, Democrats are split, and neither side can agree on what to actually do. That paralysis matters more than it sounds. The labs that built the most powerful AI systems are now calling for pacing — not just Anthropic, but OpenAI, Google DeepMind, and Microsoft. They want embedded safety evaluators, coordination on capability limits, and government help running those conversations without triggering antitrust exposure. What they're getting instead is Trump dismissing safety advocates as "negative forces," House Speaker Johnson suggesting the labs don't need Congress to slow themselves down, Bernie Sanders and Steve Bannon joining forces at a Pro-Human AI Assembly, and Democrats with no unified doctrine beyond urgency. Microsoft published a 9,000-word Humanist AI code of conduct this week. Five words summed it up: "People matter more than AI." The company said AI should remain subordinate to humans, resist goal-setting on its own, and never fight human input. This is a meaningful position. It is not a policy. And without federal coordination, the labs most willing to pace are at a commercial disadvantage against those that aren't. The technology will keep moving. The governance gap is real. And Washington is, for now, watching from both directions without moving. https://www.axios.com/2026/09/14/trump-ai-safety-regulations-congress #AIGovernance #AIStrategy …more

Nearly half of managers are typing real employee names into public AI chatbots before difficult conversations. Barely any of their companies have a policy for it. This is the AI governance story that's not getting enough attention. Korn Ferry research published this week found that middle managers are already using AI to rehearse firing conversations, performance reviews, and pay discussions. The practice is spreading faster than the policy to govern it — and most of these conversations are happening in tools that aren't covered by any enterprise data agreement. The productivity case is clear. Rehearsing a hard conversation reduces anxiety and often produces a better outcome for everyone in the room. The governance gap is equally clear. Real employee names, salary figures, and performance details typed into public AI tools are data that don't belong there, full stop. Most enterprise AI policies don't address this use case because they were written before managers started doing it. For B2B marketing teams, the parallel is direct. If your content team is using public AI tools to draft campaigns with real customer data, competitive intelligence, or unreleased product details, you have the same exposure. The technology is ahead of the policy everywhere. Close the gap before someone closes it for you. https://aibusinessweekly.net/p/managers-ai-coaching-difficult-conversations #B2BMarketing #AIGovernance …more