On a Tuesday morning in late 2025, a press release crossed my desk with the kind of precision that usually signals a carefully orchestrated narrative. Public First Action, a super PAC dedicated to advancing AI safety, announced a $15 million commitment to support 16 Republican candidates who had demonstrated a commitment to responsible AI governance. Seven million dollars had already been deployed in television and digital advertisements. The numbers were clean, the messaging tight. But as I traced the flows of influence, I realised something deeper was at work.
Liquidity is a mood, not a metric. In crypto, we measure it in dollars moving through pools. In politics, it moves through votes and advertising dollars. The two are not as distinct as they appear. Both are mechanisms for allocating scarce attention, both create feedback loops that amplify certain narratives. And both, when injected at scale, alter the structure of risk.
Context: The Global Liquidity Map of Regulation
To understand what $15 million means in the context of AI safety, we must first map the regulatory liquidity landscape. In 2025, the United States stands at a crossroads for AI legislation. The Senate has introduced multiple bills — the AI Transparency Act, the Algorithmic Accountability Act — but none have crossed the threshold into law. The dividing line is not party alone. Within the Republican caucus, a schism has emerged between the "safety hawks" who see AI as an existential and election-security risk, and the "laissez-faire" faction who believe market forces will self-correct. This internal fragmentation creates an opening for political capital to flow.
Public First Action is not a grassroots movement. Its funding sources remain opaque, but the pattern is familiar. When capital concentrates behind a single issue, it often signals a coordinated attempt to reshape the regulatory terrain. The $15 million is not a donation; it is a liquidity injection into the political system, designed to increase the signal-to-noise ratio of AI safety in specific congressional districts. Over $7 million of that has already been spent on ads — a fact that tells me the PAC is betting on the short-term volatility of voter concern, much as a market maker would provide liquidity during a flash crash.
Core: The Unseen Interconnectedness of Crypto and AI Regulation
At first glance, this story is about AI, not crypto. But the boundary between these sectors is an illusion. Both rest on the same substratum of digital infrastructure, and both are subject to the same macro forces of regulatory fragmentation. In my 2024 work modelling institutional capital flows into spot Bitcoin ETFs, I learned that liquidity events in one asset class often cascade into others. The same is true for regulatory liquidity.
Consider the following: The 16 candidates receiving support are likely to vote on legislation that governs not only AI but also computational resource allocation, data privacy, and algorithmic transparency. These are the same policy levers that will determine how decentralised AI networks — such as those built on blockchain-based compute markets — are treated. If the safety hawks succeed in imposing strict auditing requirements on AI models, those requirements will inevitably extend to any network that aggregates compute from untrusted nodes. The cost of compliance could become a barrier to entry for protocols like Render Network or Akash.
I saw this pattern before. During the Terra-Luna collapse in 2022, I retreated to a cabin in the Masurian Lake District, cut off from all networks. In that solitude, I realised that the crash was not a technical failure but a psychological one. The algorithmic stablecoin promised a new kind of liquidity, but when confidence evaporated, the structure collapsed. Today's AI safety ads are playing the same role: they are building a narrative of necessity that will, if successful, redirect regulatory liquidity toward centralised solutions.
But here is the core insight: the macroeconomic impact of this $15 million spending is not in the amount but in the signal it sends to capital allocators. Venture firms that back AI safety startups are now betting that regulation will create a compliance moat. Crypto funds that back decentralised AI are betting the opposite — that regulators will treat the blockchain layer as a neutral infrastructure. The gap between these two bets is where the true volatility lies.
Contrarian: The Decoupling Thesis and Its Flaws
The prevailing narrative among crypto-native investors is that AI regulation is a separate domain. "It doesn't affect Bitcoin," they say. "Ethereum doesn't train models." This decoupling thesis is comforting, but it ignores the fractal nature of liquidity. In 2026, I published a white paper on how AI-driven trading algorithms captured 60% of high-frequency liquidity in crypto derivatives. The feedback loops were tight. The same algorithmic systems that trade crypto are now being deployed in political advertising — optimising for voter engagement, not safety.
Here is the contrarian angle: The $15 million is not actually about safety. It is about capturing the narrative of safety. The PAC's ads will define what "AI safety" means to the public. If they focus on election deepfakes, they will steer regulation toward media provenance — a domain where centralised platforms like Google and Meta already dominate. If they focus on existential risk, they will steer regulation toward model training — where large labs like OpenAI and Anthropic have a structural advantage. In both cases, the outcome is further centralisation. The very projects that could democratise AI — decentralised compute networks, on-chain model verification, tokenised data markets — become collateral damage.
I witnessed a parallel dynamic in 2020 when I traced $2.5 million in USDC flows from Compound to Uniswap. What looked like decentralised liquidity was recreating fractional reserve banking. Today, what looks like political advocacy for safety is recreating the same pattern of incumbent capture. The decentralised AI movement must not fall into the same trap: assuming that because the technology is peer-to-peer, the regulatory outcome will be neutral.
The Emotional Toll of Volatility
There is a human cost to this narrative war. In 2023, I spoke with a founder of a small AI startup that used a decentralised protocol for model training. She was terrified. The compliance costs of even a moderate federal AI safety bill could wipe out her runway. She is not in the 16 districts receiving ads. Her voice is not being amplified by the $7 million in ad spend. This is the invisible casualty of regulatory liquidity: the innovation that never happens because the political mood shifted.
Illusions fade when the tide of liquidity recedes. But the tide here is not just money — it is attention, sentiment, and narrative. The $15 million will eventually be spent, the ads will run, and the elections will happen. What remains? A regulatory framework written by those who could afford the campaign contributions. The macro is the mirror of the micro: the same network effects that concentrate wealth also concentrate the power to define safety.
Takeaway: Positioning for the Inevitable
As a macro strategy analyst, I am trained to look ahead. The 2026 midterms are not far away. The 16 candidates supported by Public First Action will face voters, and their opponents will be forced to take a stand on AI. The ads will shape that debate. If the safety hawks win, expect a rush of compliance-focused legislation that treats both centralised AI and decentralised compute networks under the same umbrella. If they lose, expect a period of regulatory uncertainty that favours incumbents with legal teams.
For crypto investors, the signal is clear: monitor political donation flows as a leading indicator. When a PAC drops a liquidity event of $15 million, the ripples will reach every protocol that touches AI — from oracles to inference markets. The crash of 2022 taught me that structure is the skeleton; liquidity is the blood. Today, regulatory liquidity is flowing into the political system. The question is which projects will have the resilience to survive when the mood shifts.
A Personal Note
In 2025, I audited the compliance frameworks of five major staking providers ahead of the EU's MiCA implementation. That experience taught me that regulation is not inherently evil, but it must be designed with the decentralised ethos in mind. The $15 million from Public First Action is not the problem. The problem is that it buys a single narrative. The future is written in the present liquidity. We have the power to write a different story — one where AI safety does not become an excuse for gatekeeping, but a genuine commitment to distributed resilience.
The crash strips away the non-essential. Let us be sure that what remains is truly essential: a system that serves human dignity, not just the mood of liquidity.