Generative AI in the Antitrust Spotlight: EU Regulators Gear Up

With the recent spate of inquiries into generative AI investments, there is no doubt that the spotlight of EU competition authorities is on one topic: generative AI. The authorities' determination for greater oversight of AI is backed by the EU's ambitious AI Act and the establishment of the EU Artificial Intelligence Office. But that's not all: with the current Call for Contribution 'Competition in Virtual Worlds and Generative AI', open until 11 March 2024, the European Commission is calling on regulatory experts to gather views on AI from a competition perspective. In other words, the EU Commission is gearing up for competition regulation of AI at EU level.

This briefing provides an overview of current antitrust topics from EU competition authorities' lens. Together with recent EU regulatory developments, these should be anticipated by generative AI model providers and their investors or partners alike.

This briefing is the first in a series of AI briefings, spotlighting current AI-related hot topics in competition law, public procurement law, trade/foreign direct investments (FDI), and ESG.

Competitive challenges related to AI 

EU competition authorities are equipped with powerful tools to scrutinize the AI ecosystem. Generative AI model providers are likely to encounter competitive challenges in key antitrust areas such as anti-competitive collusion, abuse of dominance, and merger control.          

Anti-competitive agreements and concerted practices

Article 101 TFEU prohibits anti-competitive agreements (vertical or horizontal) between companies. This applies not only to traditional antitrust agreements (e.g. on prices, product quality or total output), but also to anti-competitive concerted practices.

Competition authorities are concerned that the risk of anti-competitive agreements and concerted practices may increase in digital markets. Digital markets are often characterised by strong vertical integration and conglomerate structures leading to parallel activities in several markets. These concerns are further amplified by the emergence of AI. In particular, the following constellations may attract the attention of the authorities:

• In markets with widespread use of AI, e.g. where AI is used for competitive decision-making, there is generally an increased risk of collusion: By processing consumer, competitor and market data, AI models are able to increase overall market transparency. This applies to (vertical) online marketplaces especially. The line into anti-competitive collusion is crossed when companies use AI to communicate about price signals, detect deviations from agreements and use algorithms to enforce agreements.

• As AI models are often associated with conglomerate business models, companies that partner with or offer generative AI technologies are more likely to be active in multiple markets. Such multi-market competitors are in principle more susceptible to collusion. This is because the potential gains from collusion are higher than in a single market. In addition, such multi-market companies have incentives to leverage their market power across multiple markets.

Abuse of dominance

Article 102 TFEU enables competition authorities to address abusive behaviours by dominant companies. Access to AI technology could become an (even more) important competitive factor in digital markets. Several factors can determine their market position: How quickly companies react to market changes, how accurately they predict and interpret data and how they use AI to develop better and cheaper products.

Dominant AI companies must therefore take particular care to ensure that they do not engage in abusive behaviour:

• Competition authorities could investigate AI technology from the perspective of ‘essential facilities’. For example, a dominant provider of generative AI models that restricts or impairs access for application developers of competitors could be subject to scrutiny. Blocking access to APIs or key training data essential for market entry could also be considered abusive conduct.

• Another critical area could be multi-platform integration strategies, i.e. the integration of generative AI into multiple products. This could have a leverage effect if, for example, a dominant platform service unfairly promotes its own services over competing offerings.

The related gatekeeper regulations aimed at tackling the dominance of Big Tech companies in digital markets - the EU Digital Markets Act (DMA) and its German counterpart Section 19a ARC - are unlikely to affect pure generative AI model providers, at least for the time being:

• Under the DMA, only designated gatekeepers providing a ‘core platform service’ (CPS) are bound by the specific obligations and prohibitions (see our latest briefing on the DMA). As generative AI does not fall under the category of CPS (yet), they are currently not covered by the DMA. However, rumours in EU competition circles suggest that the DMA's scope might be extended to generative AI. This is in line with recent regulatory AI trends, particularly the AI Act, and the Commission’s Call for Contribution.

• German Section 19a ARC would, in principle, already allow the designation of large generative AI model providers as gatekeepers. This is because it is based on the broad concept of whether a company is of ‘paramount significance across markets’ (see our latest briefing on Section 19a ARC). So far, the FCO has designated Alphabet, Amazon, Apple, Meta as gatekeepers, and is still examining Microsoft. However, it has not initiated any designation proceedings against any of the stand-alone AI players.

Merger control

Where the relevant thresholds are met, competition authorities will consider whether mergers would significantly impede effective competition. For example, by reducing competitive pressure and thus the incentive to innovate and ultimately benefit consumers:

• In horizontal mergers, constellations are conceivable where the combination of data sets or AI capabilities of competing companies creates or strengthens their dominant market power.

•  In vertical mergers, cases are likely to be relevant where competitors' access to key assets such as APIs, training data or AI technology is restricted.

• In conglomerate mergers, leveraging effects may play a particular role, e.g. if companies use tying and bundling of AI technology with their other products.

Transactions that may not immediately appear to affect market dynamics warrant careful consideration. These include joint ventures or significant investments in AI companies by larger (tech) companies. For instance, Amazon and Google’s investment in Anthropic, Nvidia’s funding of Inflection and Cohere, or Aleph Alpha’s significant funding round from industry leaders such as Bosch, Schwarz Group or SAP. These, and other notable investments in the AI sector, will have been closely watched by the competition authorities.

Providers of generative AI models operating in Germany need to be particularly cautious. The Federal Cartel Office (FCO) has the power to intervene in transactions even below the level of acquisition of control under the EU merger regime ("decisive influence").

A minority shareholding of 25% can already trigger a merger filing. But that’s not all: there is also the distinctive concept of "competitively significant influence". This covers situations where:

• a shareholding below 25 % is acquired, provided additional factors (so-called plus factors) that make the situation comparable to an acquisition of 25 % are present; and

• the acquired influence is relevant for competition (i.e. the acquirer obtains an influence that can have an effect on the way the target company (potentially) competes on the market).

Such plus factors can include any factors which, taken as a whole, give the acquirer/investor the de facto ability to influence the target (e.g. voting/information rights, equality of interests, superior market knowledge, personal dependencies).

The FCO has already examined an AI investment in the case of Microsoft's investment in OpenAI. However, it concluded, that the transaction was not currently subject to merger control.

EU AI regulation and enforcement

The AI Act, which was ratified by EU committees on 13 February 2024, and is scheduled for final plenary vote in EU Parliament on 10 /11 April 2024, represents the EU Commission’s pioneering effort to regulate AI. It is focusing on consumer protection and imposing significant penalties for non-compliance. The AI Act is applying a multi-level approach with transparency requirements for ‘general purpose AI models’ and additional obligations for AI models that pose a potential systemic risk (see our latest briefing on the AI Act).

But the road to the final text was not an easy one: it is a compromise resulting from intense discussions: Member States France and Germany, in particular, initially favoured a less stringent regulation for generative AI models. The main concern was not to put unnecessary obstacles in the way of promising start-ups such as Mistral AI and Aleph Alpha, which could potentially compete with US or Chinese AI companies.

The result is an AI law with a considerable degree of legal uncertainty due to a (still) large number of undefined legal terms. Given the rapid development of AI technologies, the law must remain in a state of dynamic change. The obligations of the AI Act will be demanding for generative AI model provider and require significant human and technical resources. Practice will show whether this is at the expense of effective competition and innovation.

The recently announced creation of a central EU authority, the European Artificial Intelligence Office, shall facilitate coordination between AI model providers, regulators and national authorities. However, the new Office is not toothless: it will also have investigative powers, such as collecting complaints, issuing document requests, conducting assessments and requesting enforcement action to mitigate breaches.

Outlook

As AI continues to evolve, the challenge for regulators and competition authorities is to foster an environment where innovation can flourish while preventing anti-competitive practices. The existing legal competition framework provides robust tools to address potential market distortions. This underscores the importance of a nuanced approach to AI regulation that benefits consumers and promotes market competition.

It is questionable to what degree an extension of EU competition regulation, in particular the DMA would bring benefits to Internal Market competition. In particular, if it is to apply beyond big tech companies. The DMA is already a highly technical regulation with extensive self-regulatory burdens on companies. The positive impact of AI on consumers should not be overlooked in the regulatory debate: AI applications generally have significant pro-competitive potential on both the supply and demand side of markets. They have the capacity to be drivers of innovation and competition. This can lead to a more dynamic and competitive market, benefiting consumers through increased choice, better quality and lower prices.

 BLOMSTEIN will closely follow current developments in antitrust law in the context of AI and the Federal Cartel Office's decision-making practice on AI and the digital economy and keep you informed. If you have any questions on antitrust law, please contact Max Klasse, Philipp Trube and Jasmin Sujung Mayerl.