“Artificial Intelligence is a new digital frontier that will have profound impact on the World”
—WIPO Director General Francis Gurry
Introduction to Predatory Pricing
Predatory pricing, though not a new concept, has gained considerable importance in recent years due to increased market regulation and vigilant monitoring of market participants. The significance of pricing determination has amplified with the intensifying competition and the emergence of numerous players in crucial sectors. Moreover, the advent of e-commerce in the modern market system has presented additional complexities and hurdles in pricing goods and services sold online.
A price is commonly understood as the value at which goods and services are exchanged within the market. This notion of exchange extends beyond transactions involving money as a medium, encompassing barter-based trading as well. Therefore, the concept of price applies even in barter systems. However, conducting transactions with money simplifies the recording process, as it clearly indicates the desired outcome for each party involved. Currently, exchanging goods or services for money is the most prevalent method in the market. Nonetheless, there are situations where a party may choose to offer goods or services at a price that they deem suitable. This price can either be higher than the cost price or lower than the prevailing market price of the commodity being traded.
Predatory pricing is a market pricing strategy wherein goods or services are offered at an exceptionally low price, typically below the cost, with the intention of eliminating competition. This strategy is employed by dominant players who set prices so low that other existing market players are unable to compete effectively.
Enterprises with significant capital are more likely to adopt this strategy as they can absorb initial losses, anticipating greater profits in the future. Consequently, it becomes crucial to regulate such practices when they are employed by dominant players. However, implementing such practices can be expensive and risky due to the uncertainty surrounding potential future benefits.
The advent of new technologies such as artificial intelligence (AI), pricing analytics, and algorithm-based pricing comparisons has transformed the landscape of pricing goods and services. Sellers are now utilizing these technologies to assess and compare their competitors’ prices, which influences their own pricing decisions. An example of this can be observed in the Civil Aviation Sector, where AI-based technologies and comparative price analytics are employed for price determination. The Aviation Ministry has recognized the issue of selling air tickets below cost price, as several major airline providers have reported negative annual profits.
Predatory pricing has been identified as a significant factor contributing to these substantial losses. This pricing approach in the e-commerce industry has resulted in the expulsion of smaller market players who struggle to compete against larger firms. Consequently, this situation can be perceived as a disruption of market competition, negatively impacting not only small players but also consumers.
Effects of Predatory Pricing on an Industry
Short-Term Effects
Predatory pricing initially benefits customers by providing them with significantly lower-priced options. However, it adversely affects competing enterprises in the industry. This practice has the potential to disrupt market competition as all existing players would experience a decline in profitability. In order to redirect consumer traffic and meet customer expectations, competitors would be compelled to lower their prices. The company that can withstand this “price war” and remain in the market may ultimately gain long-term advantages such as increased market share. However, it is unlikely for them to establish a monopoly in the industry.
Long-Term Effects
When a dominant enterprise successfully eliminates competitors from the market, it becomes the sole player and may subsequently increase prices to recover the previously lost profits. As prices rise, buyers’ willingness to pay decreases, which is particularly effective for non-flexible goods. Consequently, in the long run, buyers suffer from higher prices, while the near-monopoly company benefits. Furthermore, the absence of competing enterprises may lead to a decline in product quality and limited innovation since the market is controlled by a single player.
Tracing Down the Probable Threats Posed by Artificial Intelligence to Competitive Markets
The definition of Artificial Intelligence (AI) lacks universal precision. In simple terms, AI refers to a process that replicates cognitive human functions, such as learning and problem-solving, through dedicated systems. It enables computer systems to imitate the problem-solving and decision-making abilities of the human mind. The foundation of AI lies in a set of predefined and unambiguous algorithmic instructions executed by machines. By appropriately feeding data or collecting information through online tools and computer systems, AI algorithms can comprehend and enhance their execution through the acquisition of new heuristics or even generate other algorithms.
Artificial intelligence is a disruptive technology with significant implications at the international economic level, offering the potential to revolutionize various industrial sectors. These technologies have the capacity to improve efficiency, benefit consumers, reduce production and operating costs, foster innovation, and introduce new and improved products and services.
However, AI presents theoretical and practical challenges for market regulators and law enforcement agencies. It is believed that AI can enable certain anti-competitive practices, introduce new issues, and challenge traditional tools for competition analysis. In certain cases, the use of AI may amplify concerns related to anti-competitive behavior, such as targeted marketing, real-time price fluctuations, and price prediction. AI operates at a speed and precision that surpasses human capabilities.
However, unlike the human brain, Artificial Intelligence (AI) lacks common sense and is unconcerned with ethics and legality. Consequently, the use of AI has raised legal challenges, particularly in relation to competition and antitrust laws. It is essential to focus on the potential anti-competitive issues that may arise from the utilization of AI. Competition authorities and courts have addressed algorithm-related matters in various cases, such as the “Online sales of posters and frames in the UK” and “Topkins in the United States.”
While AI holds the promise of providing consumers with better services and products tailored to their needs and preferences, it presents more complex challenges compared to traditional algorithms due to its data collection and processing capabilities. These capabilities enable AI to obscure different competitive threats. The particular concern to competition law is the use of AI in implementing and facilitating various forms of coordination.
AI technology can be employed to develop and implement collusive schemes through human interaction. It can also assist in achieving, coordinating, and monitoring collusive structures by signaling firms’ willingness to engage in collusive agreements, organizing their implementation, and ensuring compliance. The speed, cost-effectiveness, precision, and information generated by AI systems significantly enhance the performance of cartels. This raises concerns regarding the effectiveness of competition law enforcement in tackling AI-managed processes.
Artificial intelligence (AI) technology has the capacity to adapt pricing policies to changing market conditions, giving firms a competitive advantage and greater stability. These sophisticated algorithms possess self-learning and predictive capabilities, allowing firms to promptly adjust their pricing strategies. It is important to recognize that AI technology can be employed for both exploitative and exclusionary conduct in the market. Pricing algorithms, in particular, have significant potential for engaging in discriminatory practices by collecting and analyzing precise information on consumers’ preferences and willingness to pay.
This enables the implementation of highly sophisticated forms of real-time price discrimination, approaching the level of personalized pricing. Furthermore, the strategic use of AI technology in mergers should be considered in terms of potential anti-competitive effects. The exceptional speed and effectiveness of intelligent adjustments by AI agents may increase the risk of coordinated effects, even in less concentrated markets. This raises the question of whether traditional legal concepts and tools related to competition analysis need to be revisited in light of AI advancements.
The exponential potential for autonomous intelligent adjustments offered by AI technology may lead to coordinated outcomes without the need for traditional explicit agreements. In summary, the strategic use of AI technology can significantly impact competition in the market, particularly through pricing practices and merger dynamics, requiring careful consideration and potential reevaluation of existing legal frameworks.
Artificial Intelligence, Predatory Pricing and Competition Regime
Artificial Intelligence (AI) presents a significant challenge in relation to predatory pricing and its impact on competition. AI enables firms to engage in exploitative and exclusionary practices, such as predatory pricing, by utilizing advanced algorithms to analyze factors like firm size, cost structure, and consumer base. This analysis helps firms assess the probability of success and profitability of such practices. Moreover, AI facilitates algorithmic pricing, which involves companies using computer systems and databases to set prices. The use of AI provides these companies with comprehensive knowledge about consumers and price dynamics, granting them a dominant position in the market. In summary, the utilization of AI allows firms to strategically implement predatory pricing and algorithmic pricing, giving them a competitive advantage and potentially leading to anti-competitive outcomes. This poses challenges for competition regulators in maintaining a fair and balanced market environment.
Conclusion
Artificial Intelligence (AI) stands out as a highly disruptive technology, fundamentally transforming traditional business and transaction models across various sectors such as healthcare, hotels, and the food and beverage industry. Its pervasive presence is evident in numerous areas. While AI offers significant business opportunities, it also poses certain threats to the market.
As with any technology, there are pros and cons associated with AI. Many businesses and companies embrace the use of AI as it enables them to establish a strong market position, leading to increased profits. However, regulators have legitimate concerns regarding potential consequences that cannot be ignored. The behavior of AI-based algorithms, which disrupts traditional brick-and-mortar markets, requires careful examination.
These algorithms have the ability to learn and adapt to prevailing market prices, potentially leading to predatory pricing practices. Moreover, determining the liability for AI-based anti-competitive practices under competition law remains uncertain. Regulators face the challenge of addressing the legal implications of AI’s impact on competition. In summary, while AI offers numerous benefits and opportunities for businesses, it also presents concerns for regulators. The disruptive nature of AI algorithms and their potential for predatory pricing require thorough study, and the allocation of liability in cases of AI-driven anti-competitive practices remains a complex issue.
AI agents themselves are not to be held accountable as they typically operate in the interests of specific companies. The question of liability for anti-competitive decisions does not have a straightforward answer and may vary depending on the case. It raises the important consideration of whether policy-makers and courts should update traditional notions, such as those of “undertaking” or “agreement,” to capture anti-competitive practices facilitated or directly enabled by AI. Preventing and detecting anti-competitive use of AI presents a challenge for regulatory agencies.
Various approaches can be adopted by competition law authorities, including the use of investigative powers and engaging external experts to assess the impact of self-learning algorithms and their underlying data and instructions. While understanding the intricacies of algorithms can be complex, competition authorities can indirectly assess their overall market impact. Alternatively, competition law rules and regulations can be adapted to ensure AI tools comply with them.
This may require providing additional resources and modifying recruitment policies for competition authorities to effectively review and interpret complex IT tools. On the other hand, AI can be utilized by competition law authorities to monitor and detect any wrongful practices in the market.
AI tools can enhance market monitoring and assessment, helping to identify anomalies and prevent anti-competitive practices. They can also streamline the review process in merger cases and antitrust proceedings, enabling more effective and cost-efficient monitoring of firms’ compliance with remedies and commitments.
It is crucial for in-house counsels, external lawyers, and economic consultants to be prepared to navigate the evolving regulatory landscape and harness the full potential of AI tools as the use of AI and competition law intersect. Ensuring the sophisticated and responsible use of AI tools and revising existing parameters are necessary steps to address the challenges posed by AI in the context of competition law.
