In the modern market of video management systems (VMS) software, there are three main types of products equipped with artificial intelligence. The first category consists of complex and expensive solutions designed for corporate clients. These systems are highly efficient and capable of providing advanced functionalities, but they come with significant operational costs, requiring specialized infrastructure and maintenance. The need for robust support and constant updates adds to the overall expense of these systems, making them suitable primarily for large-scale enterprises with substantial budgets and dedicated IT departments. While these solutions are highly effective in managing and analyzing video data, they present barriers for smaller businesses and individual users due to their complexity and price point. The second category includes outdated solutions that are difficult to use and possess limited capabilities. These older systems rely on traditional encoding algorithms that are no longer efficient in the modern technological landscape. These products often require high bandwidth connections to function correctly, which adds to the operational cost and limits their use in environments where resources are constrained. While these systems may still work in some situations, they are not suitable for businesses that require more advanced features, scalability, or ease of use. The third category represents cloud-based systems for recording and storing video footage with cloud services. Cloud VMS solutions provide a more flexible and scalable option, allowing users to access video data remotely and store large amounts of footage without the need for expensive on-premise hardware. The cloud service model can be particularly appealing for small to medium-sized businesses and individual users who seek an affordable and easy-to-manage video surveillance solution. However, these services still incur significant costs associated with data traffic and server maintenance, which can add up over time. Despite the advantages of cloud-based systems, the costs related to bandwidth and video stream encoding and decoding can become a substantial part of the overall expense. The irony is that despite the growing demand for affordable and reliable video surveillance systems, most users or small companies are still unable to access a quality product at a reasonable price. The effective solutions available on the market are often priced out of reach for individuals and smaller enterprises, leaving them with few options. Fortunately, recent advancements in peer-to-peer (P2P) technology have begun to offer an alternative that could change the landscape of video surveillance systems. P2P technologies eliminate many of the costs associated with cloud-based systems, such as data traffic and server maintenance. In this model, the server acts as an intermediary between cameras and remote devices, simplifying the setup and reducing the need for expensive cloud infrastructure. Object detection is performed using optimized deep neural network algorithms that are capable of running on relatively inexpensive microchips and processors found in low-cost microcomputers. The data is transmitted via peer-to-peer connections, bypassing cloud services altogether. This model offers a more affordable and scalable solution, making it accessible to a broader range of users. P2P-based video surveillance systems could be the key to democratizing access to high-quality VMS software for individuals, small businesses, and organizations with limited budgets. By leveraging the power of AI and efficient data transfer technologies, users can access effective surveillance systems without the need for expensive cloud services or outdated, cumbersome solutions. As P2P technology continues to evolve and improve, it is likely that these systems will become even more affordable and user-friendly, opening up new possibilities for personal and small-scale video surveillance. With the increasing demand for more accessible and cost-effective video management solutions, P2P technologies could play a pivotal role in shaping the future of the VMS software market.