AI, Power and Policy: Signals from Our Conversation with Axios’ Ashley Gold and Maria Curi

Curley Company and GlobalWIN hosted Axios reporters Ashley Gold and Maria Curi this week for an off-the-record conversation on the accelerated convergence of AI, technology and public policy. The pace of AI is accelerating on all fronts, the stakes are rising, and the lines between innovation and regulation are shifting fast.

Below are the signals that stood out, including breaking developments since our conversation on November 18.     

AI is moving faster than regulation

There’s a widening gap between the pace of AI adoption and the speed of regulatory response.  Companies highlight AI in earnings calls, investor materials and hiring strategies, but lawmakers and regulators are still defining what responsible oversight looks like. 

U.S. federal government, multiple state legislatures, and Europe are all attempting to define guardrails, but the frameworks do not align. There is no single model yet, and the race to regulate is also a race to define trust.

States are driving near-term action – AND Federal Overlays are Coming

With Congress unlikely to pass comprehensive AI legislation soon, states have become de facto laboratories for AI regulation.  New Mexico’s antitrust actions, along with regulatory activity in Florida, Illinois, and Vermont, show how state-level moves can alter national momentum. 

But hours after our panel, reporting from Axios by Ashley Gold and Maria Curi, revealed a draft executive order circulating inside the White House that would:

• Establish an “AI Litigation Task Force” to challenge state AI laws.
• Direct agencies like FCC, FTC, and Commerce to preempt or pressure states.
• Condition federal grants — including BEAD broadband funds — on state compliance.
• Advance a federal framework explicitly designed to override state standards.

The order is not final, and would face legal scrutiny, but it underscores how contested the state–federal balance has become and how central AI has become to national economic strategy. Next up, will energy scarcity to run it all take center stage?

Workforce and layoffs: uncertainty is the headline

No one actually has granular or transparent data on the workforce impact of AI.

Companies are trying to shift the narrative from “AI is taking jobs” to “AI will transform jobs,” but:

• Workforce fear is spreading faster than established scenarios
• Upskilling programs may lag behind AI-related product or workflow evolutions
• AI infrastructure spending is affecting profitability, talent, and partnerships

Uncertainty is becoming a defining hallmark of the strategic business, political, and reputational landscape.

The vocabulary of AI is becoming politicized – and that matters for advocacy

Across Washington, Silicon Valley, and state capitals, “safety” has become the defining and most contested word in AI debates.   It means different things to:

• Lawmakers
• Tech companies
• Industry leaders
• Regulators
• Consumers
• Voters

This vocabulary fight is shaping legislation, executive action, and public messaging in real time. And those differences aren’t just rhetorical, they lead to fundamentally different policy proposals, disclosure requirements, and expectations for accountability.

For advocacy and public affairs teams, this introduces a new layer of complexity:

• Messaging must work across audiences who define “harm” differently.
• The trust narrative is now a strategic variable, not a communications afterthought.
•  The same term (“AI safety”) can activate supporters or opponents depending on framing.

This is a textbook example of why the communication landscape around AI is becoming as important as the regulatory landscape itself.

Models that work: How states are experimenting

Across the country, governments are testing early AI pilots that reveal both the promise and the strain of adoption at scale. As Axios’ Ashley Gold and Maria Curi have reported, states are becoming laboratories for discovering what “responsible use” looks like in practice and where the friction points really are.

Pennsylvania became the first state to roll out ChatGPT Enterprise to its workforce, positioning AI as a productivity tool for public servants rather than a risk to be managed.

New Jersey’s NJ AI Assistant, used by more than 20 percent of the state workforce, is one of the clearest examples of bottom-up experimentation. Employees are using AI to summarize meetings, draft memos, and analyze data. 

Los Angeles is preparing for major global events like the World Cup, Super Bowl, and Olympics with a “smart city” strategy, training more than 27,000 workers on responsible use of AI.

Taken together, these pilots show:

• AI can drive meaningful efficiency and insight — even in resource-constrained environments.
• Leadership style matters; states with CIOs who frame AI as a tool rather than a mandate often see faster adoption.
• Training is a moving target; by the time employees upskill, the technology frequently shifts again.
• Data governance is the stress point; every pilot surfaces new questions about accuracy, privacy, and liability. “AI-approved scenarios” is a current norm.

These experiments are not just operational, they are shaping the early playbook for how agencies, vendors, advocates, and lawmakers will communicate, explain, and negotiate AI’s role in public life.

The Advocacy Communications landscape for AI is just beginning

While AI itself is not an election issue, it’s already shaping elections and communications through:

• Generative content
• Deepfakes and authentication
• AI-powered organizing and targeting tools
• New AI-focused super PACs and issue coalitions

For communicators, this means:

• The AI narrative intersects with economics, jobs, competitiveness, misinformation, national security, and beyond
• Proactive narrative shaping matters as much as policy positioning
• Earned media and journalist engagement remain critical because the information ecosystem is fragmenting even further

What Comes Next

Across industries and roles of the 60+ attendees who joined our panel discussion, one takeaway came through clearly:  AI is no longer a “tech” topic; it’s now shaping power, policy, profits and public perception in parallel, and leaders must navigate all of these at once.     

For organizations operating in this environment, the questions are becoming sharper:

• How do you prepare for policy that is still developing at the federal and state levels as well as outside the U.S.?
• How do you communicate clearly when public perception is moving faster than guidance?
• How do you bring stakeholders along as you balance business impact with so much investment and change?
•  How do you lead when innovation and accountability are now inseparable?

This is where Curley Company works — helping leaders navigate the intersection of AI, policy, reputation, and influence with clarity and strategy. If you’re charting what comes next, we’d be glad to help you see the path forward.

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