Why Is Antitrust Scrutiny Increasing for AI?
AI markets are attracting intense antitrust scrutiny from regulators in the U.S., EU, and globally due to rapid consolidation and market concentration among a few dominant players, concerns about data advantages creating insurmountable barriers to entry, vertical integration across AI development, deployment, and infrastructure, and acquisition of promising AI startups by technology giants potentially foreclosing competition.
Regulators including the FTC, DOJ Antitrust Division, and European Commission are investigating whether companies like Microsoft, Google, Amazon, and others are using dominance in AI or adjacent markets to restrict competition. High-profile transactions like Microsoft’s investment in OpenAI and partnerships between cloud providers and AI developers face regulatory review.
For AI companies pursuing M&A, forming strategic partnerships, or growing market share, understanding antitrust constraints and regulatory expectations is essential for compliance and strategic planning.
Antitrust Legal Framework
Sherman Act and Monopolization
Section 2 of the Sherman Act prohibits monopolization and attempts to monopolize markets. Monopolization requires possessing monopoly power in a relevant market and willfully acquiring or maintaining that power through exclusionary conduct.
Mere market dominance isn’t illegal—companies can grow through superior products, business acumen, or historic accident. However, using dominance to exclude competitors or foreclose competition violates Section 2.
Clayton Act and Mergers
Section 7 of the Clayton Act prohibits mergers and acquisitions that may substantially lessen competition or tend to create monopolies. The FTC and DOJ review significant transactions for competitive effects.
AI acquisitions face heightened scrutiny even at relatively small deal sizes due to concerns about nascent competition.
FTC Act and Unfair Methods of Competition
Section 5 of the FTC Act prohibits unfair methods of competition, providing the FTC with broader authority than Sherman or Clayton Acts. The FTC can challenge conduct beyond traditional antitrust boundaries.
EU Competition Law
Articles 101 and 102 of the Treaty on the Functioning of the European Union prohibit anti-competitive agreements and abuse of dominance. The European Commission actively enforces competition law in AI markets.
EU merger control requires notification of transactions exceeding revenue thresholds.
Market Definition Challenges in AI
Defining Relevant AI Markets
Antitrust analysis begins with defining relevant product and geographic markets. For AI, market definition is complex because AI applications span numerous use cases and industries, general-purpose AI models may compete with specialized systems, substitutability between different AI approaches is uncertain, and rapid technological change makes market boundaries fluid.
Narrow market definitions suggest higher market shares and greater competitive concerns. Broad definitions minimize apparent market power.
Two-Sided and Multi-Sided Markets
Many AI platforms operate in two-sided or multi-sided markets serving developers consuming AI services, end users benefiting from AI applications, and data providers contributing training data.
Traditional market definition tools may not capture competitive dynamics in multi-sided markets.
Monopolization Concerns in AI
Data Advantages and Network Effects
Companies with vast user bases can collect extensive data for training AI models. This creates potential competitive advantages where more users generate better data, better data produces superior AI, and superior AI attracts more users, creating self-reinforcing cycles.
Regulators examine whether data advantages constitute insurmountable barriers preventing competitive entry.
Essential Facilities and Access
If certain AI infrastructure, datasets, or compute resources become “essential facilities” that competitors need but cannot reasonably duplicate, dominance over those facilities may create antitrust obligations to provide access on reasonable terms.
For example, foundational AI models or specialized datasets might be deemed essential.
Tying and Bundling
Companies with market power in one product cannot unlawfully tie sales of that product to purchases of separate products. AI companies with dominance in adjacent markets may face challenges if they bundle AI services with other products to foreclose competitors.
For instance, bundling cloud infrastructure with AI model access might raise concerns.
Exclusive Dealing and Foreclosure
Agreements preventing customers from using competitors’ AI services can constitute unlawful exclusive dealing if they substantially foreclose competition. This applies to both explicit exclusivity requirements and de facto exclusivity through discounts or other incentives.
Merger Review for AI Transactions
HSR Act Filing Requirements
The Hart-Scott-Rodino (HSR) Act requires parties to notify the FTC and DOJ of transactions exceeding size thresholds and wait for review before closing. Current thresholds adjust annually but generally capture transactions over $100 million.
Parties submit extensive information about businesses, markets, and transaction structure.
Regulatory Review Process
After HSR filing, agencies have 30 days for initial review. If agencies identify concerns, they issue Second Requests demanding extensive additional information, extending timelines by months.
Agencies can challenge transactions through administrative litigation or federal court.
Theories of Harm for AI M&A
Regulators evaluate whether AI acquisitions harm competition through horizontal overlap eliminating direct competitors, vertical integration foreclosing input or customer access, acquisition of nascent competitors before they mature, or elimination of potential competition and innovation.
Recent enforcement emphasizes preventing acquisitions of nascent competitors even at early stages.
Killer Acquisitions
“Killer acquisitions” involve acquiring potential competitors to eliminate competitive threats rather than realizing innovation. Regulators scrutinize whether acquirers intend to continue target development or shelve competitive products.
Internal documents discussing competitive threats can evidence anticompetitive intent.
Strategic Partnerships and Investments
Partial Ownership and Control
Minority investments in AI companies may require HSR filing if they confer control rights. The FTC scrutinizes whether investments create influence over competitive decisions even without majority ownership.
Joint Ventures and Collaboration
AI joint ventures and research collaborations can raise concerns if they involve competitors coordinating on pricing, output, or market allocation. However, efficiency-enhancing collaborations that don’t unreasonably restrain competition are lawful.
Structure collaborations to avoid unnecessary restrictions on independent competitive conduct.
Cloud Provider Partnerships
Partnerships between cloud infrastructure providers and AI developers face scrutiny when cloud providers have market power and partnerships foreclose competing AI developers or when AI developers have significant positions and partnerships exclude alternative infrastructure.
Licensing and Interoperability
API Access and Interoperability
Companies with market power may face pressure to provide API access or ensure interoperability with competing systems. Unilateral refusals to deal are generally lawful, but refusals by monopolists can violate antitrust law if they eliminate competition in downstream markets.
Standard Essential Patents
If AI technologies become incorporated into industry standards, patents covering those technologies may be deemed standard-essential. Holders must license on fair, reasonable, and non-discriminatory (FRAND) terms.
Pricing and Terms Discrimination
Algorithmic Pricing and Coordination
AI-powered pricing algorithms that facilitate coordination among competitors raise price-fixing concerns even without explicit agreement. The DOJ has indicated that using algorithms to coordinate pricing can violate antitrust law.
Discriminatory Pricing
While price discrimination is often lawful, using market power to impose discriminatory terms harming competition can violate antitrust law. This includes predatory pricing below cost to drive out competitors or price squeezes that disadvantage downstream competitors.
International Antitrust Coordination
Multi-Jurisdictional Review
Significant AI transactions require approval from multiple jurisdictions including U.S. (FTC/DOJ), EU (European Commission), UK (CMA), China (SAMR), and numerous other countries.
Each jurisdiction applies its own substantive standards and procedural requirements.
Divergent Regulatory Approaches
Different jurisdictions may reach different conclusions about competitive effects. Transactions approved in one jurisdiction may be blocked or conditioned in others.
Defending Against Antitrust Challenges
Efficiency Justifications
Transactions or conduct can be justified if they generate cognizable efficiencies that benefit consumers and cannot be achieved through less restrictive means.
For AI, efficiencies might include accelerated innovation through combined research, scale efficiencies in model training, or improved product integration.
Failing Firm Defense
Acquisitions of failing firms may be permissible if targets would exit the market absent acquisition, no other potential acquirers exist, and asset liquidation would not preserve competition.
This defense rarely succeeds but may apply to distressed AI startups.
Compliance Programs and Risk Mitigation
Antitrust Training and Policies
Implement antitrust compliance programs including training employees on prohibited conduct, policies against competitor coordination, review procedures for M&A and partnerships, and documentation of business justifications for potentially sensitive decisions.
Privilege and Compliance
Engage antitrust counsel early for privilege protection and strategic guidance. Privilege may protect legal advice about competitive implications, though business facts aren’t privileged.
HSR Filing Strategy
For transactions requiring HSR filing, develop comprehensive filing strategies including thorough market analysis and competitive justifications, early engagement with agency staff, and preparation for potential Second Requests.
Ongoing Regulatory Developments
FTC and DOJ Merger Guidelines
Updated Merger Guidelines from the FTC and DOJ emphasize concerns about digital markets including lower thresholds for nascent competition concerns, heightened scrutiny of vertical mergers, and focus on innovation competition beyond just price.
Congressional and Executive Initiatives
Congress has proposed legislation strengthening antitrust enforcement in technology markets. Executive orders direct agencies to prioritize AI competition concerns.
State Enforcement
State attorneys general increasingly pursue independent antitrust enforcement in technology markets including AI.
Conclusion: Navigating Antitrust in Evolving AI Markets
Antitrust enforcement in AI markets is intensifying as regulators scrutinize market concentration, data advantages, and strategic transactions. AI companies must understand relevant market definitions and dominance assessments, structure M&A to withstand regulatory review, design partnerships avoiding anticompetitive coordination, and maintain compliance programs preventing violations.
Proactive antitrust counseling enables companies to pursue growth strategies while minimizing enforcement risks.
Contact Rock LAW PLLC for Antitrust Counsel
At Rock LAW PLLC, we advise AI companies on antitrust compliance and regulatory strategy.
We assist with:
- M&A antitrust review and HSR filings
- Partnership and joint venture structuring
- Market dominance assessments
- Antitrust compliance programs
- Defense of regulatory investigations
- International antitrust coordination
Contact us for strategic antitrust guidance navigating competitive AI markets.
Related Articles:
- AI Startup Fundraising and Due Diligence
- Preparing for M&A Due Diligence
- Handling AI-Related Disputes
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