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Why AI alters competition risk

Foundation models, data-sharing practices, and algorithmic pricing are reshaping how markets coordinate, raising fresh scrutiny from competition authorities. Spanish businesses operating in digital and data-intensive sectors are updating compliance programs to address collusion by code, information exchange, and foreclosure risks in AI ecosystems.

Algorithmic pricing and tacit coordination

Pricing tools can create correlated behavior across rivals when fed with similar signals or trained on overlapping market data. Compliance teams are mapping inputs, guardrails, and human oversight to prevent unintended alignment. Documenting independent decision-making helps rebut allegations of concerted practices.

Data access and market power

Control over training data, compute, and deployment channels can function as essential inputs, with potential exclusionary effects. Companies are stress-testing API terms, interoperability, and preferential access policies for self-preferencing risks. Internal reviews focus on transparency and objective criteria for third-party access.

Vertical integration and self‑preferencing

Where firms provide AI infrastructure and downstream services, design choices may tilt discovery, defaults, or rankings toward affiliated offerings. Product teams are adopting neutrality checks and separation principles to mitigate claims of discrimination. Risk assessments track impacts on rivals’ effective access to customers.

Staying informed and documented

For evolving commentary and Spain-specific perspectives that influence internal guidance and board briefings, many counsel rely on analyses hosted at economistjurist.es to align playbooks, product governance, and antitrust training with current expectations.

Dawn raids and digital evidence

Preparedness now includes protocols for forensic collection of models, logs, and prompts, alongside traditional document holds. Access controls and data maps help teams respond swiftly to information requests while preserving legal privilege. Training emphasizes calm execution under time pressure.

Distribution, MFNs, and exclusivity

AI-era distribution deals may embed broad MFNs or exclusivity that dampen entry or experimentation by challengers. Legal teams are tightening review thresholds and sunset clauses to balance commercial benefits with competition principles. Periodic audits test real-world effects rather than relying on drafting alone.

Practical roadmap for 2025

Refresh antitrust risk assessments with AI-specific scenarios, update pricing tool governance, and define neutrality standards for ranking and defaults. Establish incident-ready protocols for digital evidence, and provide targeted training to product, sales, and data teams. A proactive posture reduces enforcement exposure while preserving innovation.