How the Era of Economic Statecraft Is Reshaping Government Institutions

About This Report

This report examines the global emergence of economic security as a primary vector of national security policy – a shift that has accelerated dramatically across allied democracies since 2022 and is now reshaping how governments, regulated industries, and critical infrastructure operators approach intelligence, compliance, and vendor risk.

The central thesis: three consecutive US administrations, spanning both political parties, have independently arrived at the same conclusion – corporate ownership structures, supply chain relationships, and financial networks are national security infrastructure. The same conclusion is being reached simultaneously in the UK, EU, Japan, Australia, Canada, and Singapore. This convergence is not coincidental; it reflects a structural shift in how great power competition operates in the 21st century.

Chapter 1: The Doctrine Shift – Three Administrations, One Direction

The evolution of US economic security policy over the past 12 years is best understood not as a policy choice by any particular administration, but as an institutional recognition of a structural shift in how great power competition operates. Three successive administrations – with very different worldviews and foreign policy philosophies – have independently escalated economic security tools, each building on the infrastructure created by their predecessor.

This bipartisan continuity is significant. Economic security policy is not a political position that will reverse with the next election. It is a durable institutional mandate – one generating growing agency budgets, new legislative authorities, and expanding commercial requirements.

The Key Doctrinal Shift

The most important change across these three administrations is the move from entity-based economic security to structure-based economic security. Traditional approaches asked: “Is this company on a list?” The modern approach asks: “Who owns this company, what are their corporate relationships, and does any connection in this ownership chain create national security exposure?”

This shift has profound operational implications. A company can have no name-match against any watchlist and still represent a critical national security risk – if its beneficial owner is a designated entity operating through layers of shell companies, or if it is a subsidiary of a state-owned enterprise in a restricted sector.

Chapter 2: The Corporate Structure Problem

Economic security threats – sanctions evasion, technology diversion, forced labor supply chains, foreign investment risk – share a common feature: they hide in corporate structure. The bad actor is rarely the entity at the surface of a transaction. They are behind it: the beneficial owner of a shell company, the state-owned parent of an innocuous-sounding commercial subsidiary, or the third-tier supplier operating in a restricted jurisdiction behind two layers of legitimate intermediaries.

Three Structural Evasion Patterns

• Beneficial ownership layering: A sanctioned individual controls a company through 3-7 layers of shell companies across multiple jurisdictions. List screening checks direct counterparty names – it cannot follow ownership chains through intermediaries, especially across jurisdictions with limited disclosure requirements.
• State-owned enterprise subsidiaries: A Chinese or Russian state-owned enterprise creates commercial-facing subsidiaries specifically to avoid list exposure. The subsidiary is not on a list. The parent may not be listed for the specific subsidiary relationship. Standard screening misses the connection entirely.
• Supply chain infiltration: A Tier 1 supplier is legitimate and fully screened. Their Tier 2 or Tier 3 material supplier sources from a restricted region or is connected to a restricted entity. The Tier 1 supplier may not know – or may not disclose.

Chapter 3: Allied Nation Strategies

The US is not alone in this doctrinal shift. Across the democratic alliance network, governments have independently arrived at the same conclusion: economic interdependence creates strategic vulnerability, and corporate ownership transparency is a prerequisite for managing that vulnerability.

The analytical requirement is common to all: know who actually owns the entity, trace the corporate structure behind the transaction, and verify that no part of the ownership chain creates strategic exposure. This is not a regulatory preference – it is now a legal requirement across the largest allied economies simultaneously.

Chapter 4: The Regulatory Architecture

The regulatory infrastructure for economic security is now built. What remains is the intelligence and compliance infrastructure to execute against it. The gap between what regulations require and what most organizations can actually do is the defining commercial opportunity of this decade.

Key Architecture Pillars Built Since 2022

• UFLPA (2022): Rebuttable presumption standard for Xinjiang goods. Burden of proof on importer. CBP now traces supply chains to raw material sources, not just direct suppliers.
• CHIPS and Science Act (2022): $52B+ in semiconductor investment, with guardrails requiring recipients to disclose and limit relationships with “foreign entities of concern.”
• Outbound Investment Screening (2023-2024): US Treasury framework for screening outbound investment in advanced semiconductors, quantum computing, and AI – extending economic security from inbound to outbound capital flows.
• Advanced Semiconductor Export Controls (2022-2024): Three successive expansions of BIS controls on semiconductor technology and equipment. Foreign Direct Product Rule now covers global semiconductor manufacturing.
• Corporate Transparency Act (2024): Beneficial ownership disclosure requirements for 32M+ US companies. Creates the domestic data infrastructure for ownership-based risk screening.

Chapter 5: The Analyst Mission

Economic security analysis is not a single mission – it is nine overlapping mandates that share a common data infrastructure requirement. Understanding this landscape explains why generic data products fail and why purpose-built commercial world models are becoming mission-critical infrastructure.

The Nine Mandates

• CFIUS investment screening: Real-time beneficial ownership tracing for foreign acquisitions. Requires corporate registry data from 250+ jurisdictions with deterministic entity resolution.
• Sanctions evasion detection: Following ownership and financial networks beyond designated entities to identify undisclosed exposure – the 72% of risk that is off-watchlist.
• Export control compliance: Mapping end-user networks and technology transfer chains. Entity List screening plus extended beneficial ownership analysis for entities not yet designated.
• UFLPA / forced labor: Sub-tier supply chain tracing to identify Xinjiang connections at Tier 2, 3, and beyond. Trade data cross-referenced with corporate registries.
• Counterproliferation: Identifying front companies, procurement networks, and financial facilitators for WMD programs. Corporate structure analysis is the core method.
• FOCI determination: Foreign Ownership, Control, or Influence screening for defense contractors and cleared facilities. Requires both formal ownership data and informal influence network analysis.
• Threat finance: Tracing financial flows through corporate networks to identify sanctions evasion, terrorism finance, and narco-trafficking infrastructure.
• Critical infrastructure protection: Identifying foreign ownership or control in energy, telecommunications, water, and financial infrastructure sectors.
• Counternarcotics: Mapping the corporate and financial infrastructure of drug trafficking organizations – increasingly a hybrid of commercial and criminal network analysis.

Chapter 6: The AI Inflection

AI is transforming economic security analysis – but not in the way most vendors describe. The value of AI in this context is not automation of obvious decisions. It is the ability to surface judgment-quality intelligence on ambiguous entities, novel networks, and emerging risk patterns at a scale that no human analyst team can replicate.

Why Accuracy Is the Only Metric That Matters

In a sanctions or UFLPA context, an AI recommendation carries direct legal and financial liability. A false negative – an entity assessed as clean that is actually connected to a restricted network – is not a product quality issue; it is a regulatory enforcement action. This is why the accuracy gap between AI systems matters more in economic security than in any other enterprise AI application.

Sayari Scout’s approach to this problem: eliminate hallucinations at the data layer, not the model layer. Deterministic entity resolution against 11.7B+ primary government registry records – not probabilistic matching against aggregated commercial datasets – is the foundation. When the ground truth is government-sourced and analyst-reviewed, the inference pipeline can operate on verified facts rather than inferred associations.

Recommendations for Agency Leaders

Based on policy analysis, platform deployment data, and mission interviews, Sayari recommends the following priorities for government agency leaders building economic security intelligence infrastructure:

• Move from entity-based to structure-based screening – platforms that match names against lists cannot answer the questions that modern economic security analysis requires; require vendors to demonstrate corporate graph traversal, not just watchlist matching
• Require primary-source data provenance – any intelligence platform used for economic security analysis should trace every record to a specific government filing, not an aggregated or resold commercial dataset
• Build interagency data infrastructure now – the CFIUS review that draws on equities from nine agencies simultaneously requires shared data architecture, not ad hoc coordination; the infrastructure must exist before the crisis
• Evaluate AI on hallucination rate, not capability list – require vendors to demonstrate false negative rates on your actual mission entity set, in your jurisdiction footprint, before any AI capability claim is accepted
• Treat commercial world model access as mission infrastructure – the same corporate registry, trade, and financial data that economic security analysis requires is now available commercially; agencies that build proprietary alternatives are duplicating infrastructure that exists and is continuously updated
• Plan for the allied coordination requirement – economic security is inherently an interagency and allied-nation problem; data platforms that cannot support secure information sharing across agency and national boundaries will not meet the coordination requirements of the next decade