The dynamic development of the computer games market has led to a significant change in the monetization models used by game producers and publishers. The traditional sales model, based on a one-time purchase of a product by the consumer, has been largely replaced by solutions based on long-term user engagement and generating revenue through micropayments (microtransactions). Mechanisms known as loot boxes, consisting in the paid purchase of virtual packages with random content.
You see a video, a product catches your eye, and an “add to cart” button is already blinking in the corner of the screen. A few seconds later the order is placed, paid for, and on its way — all without leaving the app. That’s how TikTok Shop works: a closed-loop model in which the path from watching a piece of content to completing a purchase has been cut to the bare minimum. That very immediacy is its greatest strength and, at the same time, the source of its most serious concerns.
Just a few years ago, online store owners primarily had to ensure terms and conditions, privacy policies, and efficient order processing. Today, this is clearly not enough. EU regulations such as the Omnibus Directive and the Digital Services Act (DSA), as well as the increasing role of artificial intelligence in assessing store credibility, force businesses to consider their platforms much more broadly. It is no longer just about regulatory compliance, but also about building digital trust, which influences a store’s visibility, legal security, and customer purchasing decisions. Below, we present a practical checklist of the most important actions to implement to reduce the risk of sanctions and increase the credibility of an online store.
The dynamic development of artificial intelligence-based technologies is revolutionizing not only the commercial sector but also the area of state oversight of the digital market. The implementation of multi-agent systems by the Office of Competition and Consumer Protection (UOKiK) opens a new era in consumer rights enforcement, enabling the mass and automated identification of unfair market practices. With the Digital Services Act (DSA) and the Omnibus Directive in force, traditional control methods are giving way to algorithmic interface analysis aimed at eliminating so-called dark patterns and price manipulation. However, the use of “digital controllers” raises fundamental questions for legal science and business practice about the limits of automated decision-making processes in public administration. Although AI agents significantly improve the effectiveness of detecting violations, their legal status as a source of evidence remains the subject of heated debate. The main thesis is that while AI can be a powerful auxiliary tool for regulatory bodies, the ultimate responsibility for determining the facts and assessing the legitimate interests of a party must rest with humans, which is the foundation of a fair procedure in a state governed by the rule of law.
