AI governance enables scale without slowing innovation, expert tells Congress

Governance as infrastructure, not obstacle

Artificial intelligence governance should be understood as the infrastructure that allows innovation to scale, not a brake on development, according to testimony delivered to a House panel this week.

Miriam Vogel, CEO of EqualAI, told the House Select Committee on the Strategic Competition Between the U.S. and the Chinese Communist Party that "effective governance does not slow down innovation. It's the infrastructure that allows innovation to scale." The virtual hearing, led by Ranking Member Ro Khanna (D-Calif.), focused on responsible AI development ahead of meetings between President Donald Trump and Chinese President Xi Jinping.

Vogel drew parallels to established regulatory frameworks that enable daily reliance on complex systems. "We fly 45,000 flights across the U.S. airspace daily because passengers trust international safeguards for certification, inspection, maintenance and investigation," she said. "We put our families in our vehicles daily because we know they've met global and national safety standards. AI needs that same institutional discipline."

Why it matters

The testimony reframes a central tension in AI policy debates. While President Trump has argued against regulations that could constrain AI development, and some industry leaders have called for slowing frontier model development to ensure safety, Vogel's position suggests governance and innovation are complementary rather than competing priorities. With less than 1% of companies having strong AI governance according to World Economic Forum findings, the gap between deployment speed and oversight infrastructure represents both a competitive and security risk.

Deployment risks and agentic AI concerns

Vogel emphasized that governance must extend beyond model development into deployment phases. "Too often, proposed safeguards end with the model development," she told the panel. "Some of the highest-stakes AI interactions occur during deployment in financial institutions, hospitals, workplaces, and public institutions where governance can be weakest."

She highlighted particular concerns around agentic AI systems that can take actions and interact with other systems autonomously. A simulation at EqualAI's agentic AI governance summit demonstrated how "ordinary deployments quickly escalated into incidents and then crises" without adequate governance frameworks.

McKinsey data cited in the testimony showed that fewer than one-third of companies have AI governance in place, underscoring the scale of the implementation gap.

International coordination and U.S.-China dialogue

Vogel called for international engagement on AI governance, including between the U.S. and China, despite institutional and value differences. "If the U.S. wants to shape global AI norms, we first have to define and operationalize our own," she said. "American leadership on AI requires leadership on AI governance."

The Trump administration is reportedly considering establishing a "hotline" with China similar to military communication channels, allowing direct contact if AI-related problems arise, including hacking, national security concerns, or rogue AI systems.

Vogel concluded that "discussions about a pause in AI development must include China," while emphasizing that "we have navigated technological transformation before, not by stopping innovation, but by building the institutions capable of governing it."

The details were first reported by Fox Business.