A SaaS founder asked me last week: his dynamic pricing tool serves dozens of clients in the same industry. The clients don't know each other. They never talk. Yet their prices are converging.
"Is this price fixing?" he asked.
My answer: it might be.
This is algorithmic collusion — and it's one of the hardest antitrust questions regulators face today.
Traditional cartels need a meeting of the minds. Enforcement agencies hunt for messages, emails, transcripts. Algorithmic collusion removes that paper trail.
Three patterns keep me up at night:
Hub-and-spoke: multiple competitors outsource pricing to the same third-party algorithm. They may never speak — but the algorithm coordinates them.
Predictable agents: each firm builds its own pricing bot, but bots learn from each other's public prices and quietly synchronize.
Autonomous learning: deep-learning models discover collusive equilibria without human instruction. Academic today, courtroom tomorrow.
China's 2022 Anti-Monopoly Law amendment explicitly names "data, algorithms, technology" as tools that cannot be used for monopolistic conduct. Enforcement is shifting from "hunting for agreement" to "reading market outcomes."
Three things I tell cross-border clients building AI-driven pricing:
- Document the independent business logic behind your algorithm. If audited, you need to show your model isn't just matching competitors.
- When choosing a pricing SaaS vendor, ask who else uses the same model in your industry — and put antitrust reps into the contract.
- Scrub internal documents. Phrases like "match leading competitor" are gifts to regulators.
AI is not an antitrust shield. Increasingly, it's the evidence.
If your business runs on algorithmic pricing across borders, worth a conversation.
#AntitrustLaw #AICompliance #CrossBorderLaw #AlgorithmicPricing #ChinaLaw
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Mike Wu, China-licensed Attorney · Cross-border practice
4 languages (CN/EN/ES/JA)
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