AI guardrails are necessary, but they are not an AI response plan. As organizations deploy AI agents that can interpret instructions, use tools, access systems, and act at machine speed, static controls alone cannot account for every prompt, workflow, integration, or harmful outcome. A rule may block one risky action while missing a similar one … Continued
The bipartisan FRONTIER Act, introduced by Representatives Jay Obernolte and Lori Trahan, signals a practical shift in U.S. AI governance. Lawmakers are moving from broad principles for responsible AI to more concrete expectations for transparency, independent evaluation, risk management, and serious-incident reporting. For organizations adopting AI, the signal is clear: AI governance cannot be measured … Continued
The rapid adoption of artificial intelligence is creating a visibility gap inside the enterprise. Organizations may believe they know which AI systems process their data, only to discover that employees are using unapproved tools or that approved vendors have quietly introduced additional AI providers into their processing chains. As the IAPP reports, recent research found … Continued
OpenAI’s Health in ChatGPT experience gives eligible U.S. users the option to connect medical records and Apple Health data, including medications, lab results, clinical visits, sleep, and activity, to support more personalized health conversations. OpenAI says connected health information and conversations that use it are not used to train its foundation models or target ads, … Continued
AI vendor evaluations often start with the product demo. The features look useful. The workflow feels familiar. The platform integrates with systems teams already use. On the surface, the decision can seem straightforward. But a strong demo does not answer the most important governance question: can this AI system be used in a way that … Continued
AI Privacy Risks Need More Than Policies. They Need Privacy Incident Management. Artificial intelligence is now part of everyday business operations. Employees use AI to summarize documents, analyze data, draft communications, and automate routine work. Vendors are also embedding AI into enterprise applications, often changing how personal information is processed, retained, or shared. That shift … Continued
The conversation around AI regulation has reached another inflection point. Recent congressional testimony from the U.S. Chamber of Commerce raised a familiar concern: a growing patchwork of state AI and privacy laws could make it harder for businesses to adopt artificial intelligence, especially as compliance costs and legal uncertainty increase. That concern is real. Organizations … Continued
Enterprise AI governance is entering a new phase. For the past year, many organizations focused on AI experimentation: where to deploy it, which use cases could create value, and how quickly teams could put new tools to work. Now that AI usage is spreading across daily operations, leaders are adding financial discipline. A recent Wall … Continued
Historically, conversations around AI governance have centered on risk assessments, inventories, principles, and policies. Those foundations matter. But AI governance becomes real when something goes wrong. When an AI system fails, changes unexpectedly, becomes unavailable, or creates new risk, organizations need more than a written framework. They need a consistent way to assess impact, involve … Continued
Artificial intelligence has become the business world’s favorite answer to nearly every operational question. Can it automate this task? Can it reduce manual work? Can it move faster than a human team? Often, the answer is yes. But that does not make AI the right answer every time. A recent Wall Street Journal article made … Continued
