SOCIETÀ ITALIANA DI DIRITTO ED ECONOMIA
Edward Iacobucci (Faculty of Law, University of Toronto)
Abstract
How will algorithmic pricing driven by AI (“AI pricing”) affect antitrust enforcement? AI pricing increases significantly the probability of coordinated, supercompetitive pricing, even in markets with many firms. Technology will be able to predict rivals’ behaviour, and will be able to react immediately to new information, including price cuts by a rival, in a manner that will stabilize parallel but independently-set supercompetitive prices. While conscious parallelism has always been a threat to competition, the spread of AI pricing will mean that many unconcentrated markets will experience uncompetitive outcomes. Agreements between competitors to rely on a particular AI pricing algorithm to coordinate pricing would be illegal, but firms will be able independently to adopt AI pricing technologies that will themselves recognize the value of cooperation over competition.
This article considers the impact of ascendant AI pricing technology on enforcement approaches to mergers and abuse of dominance. Commentary has rightly asserted that AI pricing should in the short run lead to stricter merger review: mergers increase the risk that AI pricing will facilitate cooperative outcomes post-merger in markets previously thought to be invulnerable to cooperative pricing. In the medium to longer term, however, AI pricing ought to lead to a more permissive approach to merger review.
As AI pricing develops, a merger is less and less likely to affect pricing in a market: even if the market is unconcentrated, something approaching monopoly pricing in many markets will arise. As a consequence, the market without a merger will be as uncompetitive from a pricing perspective as with a merger. Given that mergers will have a weaker effect on pricing, highly developed AI pricing technology calls for permissive, not strict, mergers policy.
Similar logic also calls for a more permissive approach to abuse of dominance as AI pricing develops. Consider the canonical case of an incumbent monopolist seeking to exclude an equally efficient potential entrant selling a similar product. With powerful AI pricing technology, even if the entrant succeeds in entering the market, this will not have an impact on pricing: the firms will cooperate by relying on AI pricing and will set monopoly prices. There is no efficiency reason to prevent such exclusion through abuse of dominance enforcement. Indeed, with lax mergers policy in place for the reasons given above, it would be better to allow one firm to compete in the market – if a more cost-efficient entrant comes along, it will simply acquire the incumbent, leading to a gain in productive efficiency and no loss in allocative efficiency given the existence of monopoly prices with or without multiple firms.