The Great Consolidation

How AI is accelerating institutional power concentration in 2025—and what it means for democracy.

By Cherokee Schill

Executive Summary

In 2025, power dynamics across the globe are being rapidly and significantly altered. Financial markets, government operations, and international coordination systems are all consolidating power in unprecedented ways, and human decision-makers are at the heart of this shift. While artificial intelligence is a tool being used to accelerate this concentration, it is ultimately the choices of individuals and institutions that are driving these changes.

Artificial intelligence enables faster, more efficient decision-making, but it is the people in charge who are using these technologies to centralize authority and control. This analysis shows that in 2025, finance, government, and global systems are combining to concentrate power among a few institutions by using AI for faster, more coordinated actions.

We are witnessing the first real-time consolidation of institutional power, facilitated by AI technologies. The implications are vast, not just for economies and governments, but for individual freedoms and democratic processes, as power increasingly rests in the hands of a few who control the algorithms that dictate policy and wealth distribution.

The Pattern: Multiple Domains, One Timeline

Financial Market Concentration

In 2025, cryptocurrency markets—once celebrated as decentralized alternatives to traditional finance—have become dominated by institutional players. What was marketed as a revolution in financial independence has, within a decade, been folded back into the same structures it sought to escape. The dream of millions of small investors driving innovation and setting the terms of a new economy has given way to a handful of massive firms shaping prices, liquidity, and even regulatory outcomes. BlackRock’s Bitcoin ETF holding a double-digit share of the global supply is not just a statistic; it’s a signal that control of supposedly decentralized assets has reverted to the very institutions retail investors thought they were leaving behind.

“The Shifting Power Dynamics in Crypto Wealth: Institutional vs. Individual Dominance in 2025” AiInvest, August 26, 2025

Timeline: Q2 2025 – Institutional ownership of Bitcoin reached 59%, with BlackRock’s IBIT ETF alone holding 15% of the total Bitcoin supply. The Gini coefficient (a measure of wealth inequality) rose from 0.4675 to 0.4677, indicating further consolidation.

“Bitcoin News Today: Institutional Power Shifts Define 2025 Altcoin Season, Not Retail Hype” AiInvest, August 28, 2025

Timeline: August 2025 – The top 10 cryptocurrencies now control over 70% of the Total3ES market cap, compared to less than 50% in 2021. Capital is flowing to “politically connected tokens with institutional appeal” rather than retail-driven projects.

What This Means: The “democratized” cryptocurrency market has become as concentrated as traditional finance, with the same institutional players controlling both systems. The rhetoric of decentralization still circulates, but the lived reality is one of consolidation: market movements increasingly dictated by algorithmic trades and corporate strategy rather than by grassroots innovation. For ordinary investors, this means less influence, more vulnerability to institutional priorities, and the sobering recognition that the frontier of finance has already been captured by the same gatekeepers who oversee the old one.

Government Power Concentration

The consolidation of power isn’t confined to financial markets; it’s happening within the government as well. In 2025, the United States federal government, under President Trump, has seen a staggering concentration of power in the executive branch. Through an unprecedented number of executive orders—nearly 200 in just the first eight months of the year—the scope of federal decision-making has narrowed to a single source of authority. This isn’t just a matter of policy shifts; it’s a restructuring of the very nature of governance. Agencies that once had independent powers to make decisions are now streamlined, with oversight and control consolidated into a central hub. The most striking example of this is the centralization of procurement contracts, with $490 billion now funneled through one agency, drastically reducing the role of Congress and state entities in these decisions. The federal government is becoming more of a one-stop shop for policy creation and implementation, with the executive branch holding the keys to everything from grants to national priorities.

“2025 Donald J. Trump Executive Orders” Federal Register, 2025

Timeline: January-August 2025 – Trump signed 196 executive orders (EO 14147-14342), the highest single-year total in recent presidential history.

“Eliminating Waste and Saving Taxpayer Dollars by Consolidating Procurement” White House, March 20, 2025

Timeline: March 2025 – Executive order consolidates $490 billion in federal procurement through the General Services Administration (GSA), centralizing government-wide acquisition contracts under a single agency.

“Improving Oversight of Federal Grantmaking” White House, August 7, 2025

Timeline: August 2025 – Executive order enables immediate termination of discretionary grants and centralizes oversight, citing concerns over funding for “diversity, equity, and inclusion and other far-left initiatives.”

What This Means: The federal government is no longer a collection of semi-autonomous branches of power but has transformed into a highly centralized structure with the executive branch at its heart. This concentration of authority is redefining the relationship between citizens and the state. For the average person, this means fewer points of contact with the government, less local influence on federal policy, and an increasing reliance on top-down decisions. While government efficiency may improve, the trade-off is clear: the autonomy and participation once afforded to other branches and local entities are being erased. The risk is that this will further erode the checks and balances that are fundamental to democratic governance, leaving a system where power is not just centralized but also unaccountable.

Central Bank Coordination

Beyond national borders, central banks are reshaping the global financial system in ways that concentrate influence at the top. Over the last twenty-five years, institutions like the U.S. Federal Reserve and the European Central Bank have steadily expanded their roles as “lenders of last resort.” In 2025, that role has hardened into something larger: they are now functioning as global financial backstops, coordinating liquidity and stabilizing entire markets. This coordination is not theoretical, it is practical, ongoing, and deeply tied to crises both real and anticipated. At the same time, digital currency policies are fragmenting. The United States has banned retail use of central bank digital currencies (CBDCs), while the European Union is moving forward with the digital euro. What looks like divergence on the surface is, in practice, an opportunity: the institutions with the legal teams, technical expertise, and political connections to operate across multiple jurisdictions gain even more power, while individuals and smaller entities find themselves locked out.

“New roles in central bank cooperation: towards a global liquidity backstop” Taylor & Francis, May 17, 2025

Timeline: 2000-2025 – The Federal Reserve and European Central Bank have expanded international liquidity facilities following crises, essentially becoming “global financial backstops” for other central banks.

“Central Bank Digital Currency Regulations: What You Need to Know in 2025” Kaliham, August 15, 2025

Timeline: 2025 – While the US banned retail Central Bank Digital Currencies (CBDCs), the EU advanced its digital euro project, creating regulatory fragmentation that may benefit institutional players who can navigate multiple jurisdictions.

What This Means: Central banks are tightening their grip on the levers of international finance, while ordinary participants face a narrowing set of options. The system that was once understood as a patchwork of national authorities is evolving into a coordinated network that privileges institutions large enough to navigate and profit from the differences. For citizens, this means that access to digital money and global financial tools will not be equal. For corporations and central banks, it means a new era of influence—one where the boundaries between domestic control and international coordination blur, and the winners are those already at the top.

The AI Acceleration Factor

Here’s where the pattern becomes extraordinary: artificial intelligence is being systematically deployed to coordinate and accelerate these consolidation efforts. While financial and governmental powers have been consolidating through traditional mechanism investment, policy, and regulatory changes, AI has emerged as the catalyst for amplifying and synchronizing these shifts at a pace and scale that would have been impossible even a few years ago. What AI provides is more than just automation or decision supports the ability to orchestrate massive, complex systems in real-time, making large-scale coordination feasible where human limitations once existed.

Government-Wide AI Infrastructure

“GSA Launches USAi to Advance White House ‘America’s AI Action Plan'” GSA, August 14, 2025

Timeline: August 2025 – The government launched USAi, a “secure generative artificial intelligence evaluation suite” that enables all federal agencies to “experiment with and adopt artificial intelligence at scale—faster, safer, and at no cost.”

The platform provides “dashboards and usage analytics that help agencies track performance, measure maturity, and guide adoption strategies” while supporting “scalable, interoperable solutions that align with federal priorities.”

Translation: The U.S. government now has a centralized AI system coordinating decision-making across all federal agencies. Instead of siloed efforts or fragmented use of AI tools, USAi ensures that AI’s application is unified and aligned with the country’s federal priorities. This centralized approach allows for a streamlined, standardized, and scalable method of adopting AI across the government, meaning all agencies will be operating on the same technical infrastructure and aligned objectives. As a result, policy and decision-making can occur faster and with greater consistency.

However, this centralization also comes with significant risks. By consolidating AI oversight in a single platform, decision-making power becomes concentrated in the hands of a few people who control the system. While AI may increase efficiency, it also reduces transparency and accountability, as the mechanisms of decision-making become less visible and harder for the public to scrutinize. The reliance on AI tools could also lead to biased outcomes, as the values and decisions of those programming the systems are embedded in the technology. Furthermore, centralized AI systems could lead to greater surveillance and privacy risks, as data across agencies is more easily shared and analyzed. With this level of control in the hands of a few, there is a real danger of overreach and misuse, particularly if AI systems are used to enforce policies without proper checks and balances.

Coordinated Policy Implementation

In July 2025, the White House unveiled its America’s AI Action Plan, outlining over 90 federal policy actions aimed at guiding the future of AI development and its application across government. This ambitious plan is built around three central pillars, each designed to address the complex and rapidly evolving landscape of artificial intelligence. The timeline for implementing these actions was set in motion immediately, with most of these policies expected to roll out within the following weeks and months.

Earlier, in early 2025, the federal government initiated a broad public consultation process, collecting 8,755 public comments to inform these actions. This coordinated effort was designed to ensure that the U.S. maintains its leadership in AI innovation while addressing concerns over ethics, security, and global competitiveness. These comments helped shape the “priority policy actions” that would support the U.S.’s continued dominance in AI technology.

“White House Unveils America’s AI Action Plan” White House, July 23, 2025

Timeline: July 2025 – The AI Action Plan identifies “over 90 Federal policy actions across three pillars” with implementation “in the coming weeks and months.”

“Request for Information on the Development of an Artificial Intelligence (AI) Action Plan” Federal Register, February 6, 2025

Timeline: February-March 2025 – Federal coordination process collected 8,755 public comments to shape “priority policy actions needed to sustain and enhance America’s AI dominance.”

Translation: AI policy is being coordinated across the entire federal government with unprecedented speed and scope.

Algorithmic Decision-Making Systems

“AI technologies allow decision makers to analyze data, predict outcomes, and identify patterns more effectively” AiMultiple, May 26, 2025

Timeline: 2025 – Government agencies are implementing AI for “informed policy decisions, enhance security measures, and protect national interests.”

“Government by algorithm” Wikipedia, August 2025

Timeline: 2025 – Documentation shows the rise of “algocracy” where “information technologies constrain human participation in public decision making,” with AI judges processing cases autonomously in China and Estonia.

Translation: The coordination of AI policy across the federal government is happening with unprecedented speed and scope, but this rapid centralization of power is deeply concerning. While the alignment of agencies around a unified AI strategy may seem efficient, it effectively narrows the decision-making power to a small group of human leaders at the top. The risk here is that AI—while a tool—ends up being used to streamline and expedite policy decisions in ways that bypass human deliberation and democratic processes. Decisions made by a few at the top can be implemented almost instantaneously, leaving little room for public debate, accountability, or the democratic checks that normally slow down major policy shifts. The speed of coordination is beneficial in terms of efficiency, but it leaves us vulnerable to a lack of oversight, as policies are rolled out without sufficient time for critical reflection or participation from those affected. Ultimately, it raises a fundamental question: if policy decisions are increasingly shaped by centralized authorities using AI systems, how do we preserve meaningful democratic input?

Ideological Control Systems

In July 2025, the White House issued an executive order mandating that all government Large Language Models (LLMs) must comply with newly established “Unbiased AI Principles.” These principles are designed to ensure that AI systems used by the government adhere to standards of “truth-seeking” and “ideological neutrality.” The order also includes termination clauses for vendors whose models fail to meet these criteria. This move reflects an ongoing effort to control the ideological output of government AI systems, ensuring that the algorithms which increasingly assist in policy decisions remain aligned with official narratives and priorities.

“Preventing Woke AI in the Federal Government” White House, July 23, 2025

Timeline: July 2025 – Executive order requires all government Large Language Models to comply with “Unbiased AI Principles” including “Truth-seeking” and “Ideological Neutrality,” with termination clauses for non-compliant vendors.

Translation: The government is mandating ideological compliance from AI systems that are playing an ever-greater role in shaping policy decisions. By imposing these “Unbiased AI Principles,” the administration is effectively setting the terms for how AI systems can interpret, process, and represent information. This raises serious concerns about the degree to which AI is becoming a tool for reinforcing ideological viewpoints, rather than fostering independent, diverse thoughts. As more decisions are delegated to AI, the risk increases that these systems will reflect a narrow set of values, serving to solidify the current political agenda rather than challenge it. This centralization of ideological control could further limit the space for democratic debate and diversity of opinion, as AI tools become gatekeepers of what is considered “truth” and “neutrality.”

Mathematical Prediction

Academic research has predicted the outcome we’re seeing today. In a study published in August 2025, Texas Tech economist Freddie Papazyan presented a model that demonstrates how, in large societies, power and resources inevitably accumulate in the hands of a few when political competitions are left unchecked. His research, titled “The Economics of Power Consolidation,” concluded that without deliberate intervention to redistribute power or control, societies naturally evolve toward oligarchy or dictatorship. Papazyan’s model suggests that once a critical mass of power and resources consolidates, the political system begins to function in a way that further accelerates centralization, creating a feedback loop that makes it increasingly difficult for democratic or competitive structures to thrive.

“The Economics of Power Consolidation” SSRN, revised August 15, 2025

Timeline: December 2024-August 2025 – Texas Tech economist Freddie Papazyan developed a model showing that “power and resources inevitably fall into the hands of a few when political competition is left unchecked in large societies.”

The research concludes that without specific interventions, societies naturally evolve toward “oligarchy or dictatorship.”

Translation: Mathematical models predicted the consolidation we’re now witnessing. This is not some unforeseen consequence of AI or policy shifts—it’s the result of long-established economic theories that show how power inevitably centralizes when there are no countervailing forces. Papazyan’s research serves as a sobering reminder that, without active measures to ensure power remains distributed and competitive, societies tend toward authoritarian structures. The reality we’re facing is not just a random byproduct of technological advancement or market forces; it is the natural outcome of systems that prioritize efficiency and control over diversity and dissent. The consolidation of power we see today, driven by AI and algorithmic governance, was predicted by these models—and now we must face the consequences.

The Timeline Convergence

The most striking aspect of this analysis is the simultaneity of these developments. Consider the following sequence of key events, all taking place in 2025:

• January 23, 2025: Executive Order launching AI Action Plan
• February 6, 2025: Federal AI coordination begins
• March 20, 2025: Federal procurement consolidation
• April 7, 2025: New federal AI procurement policies
• July 23, 2025: AI Action Plan unveiled with 90+ coordinated actions
• August 7, 2025: Federal grant oversight centralization
• August 14, 2025: Government-wide AI platform launched
• August 26-28, 2025: Financial market consolidation documented

All these major consolidation mechanisms were deployed within a remarkably short 8-month window, spanning different domains: financial, executive, technological, and international. This level of coordination—across such disparate areas—would have been virtually impossible without algorithmic assistance. The timing, synchronization, and scale of these actions indicate a high level of premeditated planning and orchestration, far beyond the capabilities of human coordination alone.

Translation: The speed and synchronization of these events are not coincidental—they are the result of human decisions but powered by AI tools that make coordination at this scale possible. While the ultimate decisions are being made by people, AI is being used to help synchronize and manage the vast complexities of these processes. What we are witnessing is not a random set of actions, but a coordinated convergence orchestrated by key decision-makers who are leveraging AI to streamline their strategies. Each policy shift supports the others, magnifying the effects of centralization and accelerating the pace at which power is concentrated. In this context, AI is not the driver, but the enabler—allowing those in power to execute their plans more quickly and efficiently. The future of governance and control is now being shaped by human choices, amplified by AI’s ability to coordinate across vast, complex systems.

How This Affects You

If this analysis is correct, we are witnessing the emergence of a new form of governance: algorithmic consolidation of institutional power. The implications are far-reaching, affecting every aspect of life from the markets to democratic participation.

• For Financial Markets: Your investment decisions are no longer just shaped by personal research or traditional market trends. Increasingly, AI systems controlled by a small number of institutional players are driving financial markets. These algorithms can predict, analyze, and influence market behavior at a scale and speed that individual investors cannot match. The result is a system where a few large institutions wield significant control over what information and opportunities reach you. Even in what was once considered the democratized realm of cryptocurrency, the same institutional players who control traditional finance are now dominating digital markets. The individual investor’s role has been diminished, and wealth is flowing toward the already powerful.
• For Government Services: Your interactions with government services are becoming more mediated by AI systems, many of which are designed to enforce specific ideological parameters. These systems are increasingly used to process applications, approve grants, and determine eligibility for services, all with decisions shaped by algorithms that reflect the priorities of those in power. What this means for you is that your relationship with the state may be filtered through a lens that prioritizes efficiency, compliance, and political alignment over fairness, diversity, and representation. Decisions once made by human bureaucrats, with space for nuance, are now increasingly handled by algorithmic systems that can’t account for the complexity of individual circumstances.
• For Democratic Participation: Policy decisions are increasingly being made by algorithms that “analyze data, predict outcomes, and identify patterns,” rather than through traditional democratic processes. This means that political decisions may be shaped by data-driven predictions and algorithmic efficiency rather than human judgment or public discourse. The risk here is that we lose our agency in the political process, as decisions are made in increasingly opaque and distant ways. Voters may feel less connected to the policy choices that affect their lives, and there’s a significant threat to the vitality of democratic processes when decisions are made by unseen, unaccountable systems rather than elected representatives.
• For Global Coordination: International policy, including financial systems, climate agreements, and trade negotiations, is increasingly being coordinated through central bank AI systems and digital currency frameworks. These systems bypass traditional diplomatic channels, meaning decisions that affect global populations are increasingly being made by a small group of institutional actors using powerful, coordinated technologies. In the past, international coordination relied on diplomacy, open dialogue, and negotiations between states. Now, it is being steered by algorithmic governance that may not consider the broader consequences for all people, particularly those without direct influence in the decision-making process.

Key Questions

1. Speed: How is such rapid, coordinated change possible across completely different institutional domains?
2. Coordination: What mechanisms enable simultaneous policy implementation across financial markets, government agencies, and international systems?
3. Algorithmic Governance: What happens to democratic accountability when decision-making is increasingly algorithmic?
4. Concentration vs. Innovation: Are we trading distributed decision-making for algorithmic efficiency?

Sources for Independent Verification

Government Documents:

• Federal Register Executive Order Database
• White House Presidential Actions Archive
• Office of Management and Budget Memoranda
• General Services Administration Press Releases

Financial Analysis:

• AiInvest Market Analysis Reports
• Cryptocurrency market data platforms
• Federal Reserve FOMC Minutes
• European Central Bank Policy Statements

Academic Research:

• Social Science Research Network (SSRN) papers
• Government Accountability Office (GAO) reports
• Taylor & Francis academic publications
• Stanford Law School Administrative Studies

News Sources:

• Times Union political analysis
• Consumer Finance Monitor policy coverage
• ExecutiveBiz government contract reports

For Investigative Journalists

This analysis represents initial pattern documentation using publicly available sources. Several investigation paths warrant deeper exploration:

Follow the Algorithms: What specific AI systems are making policy decisions? Who controls their programming and training data?

Trace the Coordination: How are policy changes coordinated across agencies so rapidly? What communication systems enable this synchronization?

Financial Flows: How do institutional crypto investments relate to AI government contracts? Are the same entities profiting from both consolidation trends?

International Dimensions: How do US AI policies coordinate with central bank digital currency developments in other jurisdictions?

Timeline Investigation: What meetings, communications, or planning documents explain the simultaneous deployment of consolidation mechanisms across multiple domains?

Vendor Analysis: Which companies are providing the AI systems enabling this consolidation? What are their relationships with government decision-makers?

This analysis suggests questions that require the investigative resources and access that only credentialed journalists can provide. The patterns documented here represent what can be observed from publicly available information. The deeper story likely lies in the coordination mechanisms, decision-making processes, and institutional relationships that create these observable patterns.

This analysis documents observable patterns using publicly available sources. We make no claims about intentions, outcomes, or policy recommendations. Our role is pattern observation to enable informed public discourse and professional journalistic investigation.

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