Current trends in ecosystem development in Russia
After a period of adaptation to new economic and geopolitical conditions, the dynamics of ecosystem development in the country’s consumer markets began to show certain signs of slowing down. Thus, this is reflected in the abandonment of unpromising areas and concentration on key ones, in a decrease in the growth rate of subscription penetration, and in general in greater pragmatism, caused, among other things, by the tightening of monetary and financial policy by the end of 2024. Of course, ecosystems will continue to improve consumer ecosystem-wide mechanics and existing services, but in building up product portfolios, we can expect efforts to shift from self-development and M&A to attracting partners and integrating their products into the integrated offerings of their ecosystems.
At the same time, most ecosystems have a new organizational and commercial focus — B2B, that is, a segment of services for companies: B2B product portfolios are being formed around basic, key competencies (for example, SBER, Yandex, VK, and, of course, ecosystem marketplaces with their “helping” services for sellers), plans have been announced even by completely separating such business areas from individual players. This trend is related both to the great prospects in B2B compared to saturated consumer (B2C) markets in general (the growing demand for further digitalization, automation and robotization of internal business processes of companies and their sales channels, the transition to the so-called platform-based, as well as cloud-based solutions for the formation of industry marketplaces), and with the ability for ecosystems to reuse accumulated B2C market tools in the B2B segment, transferring “consumer” marketing and user mechanics there (using social networks, marketplaces and self-service sales channels, selling their advertising capabilities and capabilities of technology platforms and modules).
A certain transition from quantity to quality is observed in the field of AI: from the creation of experimental models and demonstration products, many ecosystems in Russia are moving to the practical implementation of large language and generative AI models in their basic products — or even to the creation of completely new products based on AI technologies. It should be expected that in Russia it is ecosystem companies with a wide range of both B2C and B2B products, human, technological and financial resources that will be able to develop AI most actively in the future.
Key development vectors: technological and business trends
In the telecom sector, the main trends have not changed over the year.
The growing penetration of 5G contributes to the unloading of mobile networks, but it still does not provide any clear advantages or any new products based on its base for ordinary consumers. Additional revenue from 5G is still expected to be driven by demand for new high-load services from B2B companies. At the same time, here in B2B, complex, integrated solutions are important (which include a “basic” high-speed mobile connection only as one of the components), which means that operators will have to compete not only with each other, but also with technological IT companies, and in Russia, with ecosystems that are beginning to be considered the business market as a new key area for itself. This applies not only to 5G, but also to other telecom and near-telecom services that some operators (including MTS) are developing, such as UCaaS, Telecom API, private LTE \ 5G.
The number of partnership agreements between satellite (primarily Starlink) and mobile operators in the field of “non-terrestrial” networks (NTN) for direct satellite-standard smartphone communication continues to grow. So far, efforts are focused on ensuring the delivery of text messages (SMS), but data transmission is also already possible. In the medium term, the introduction of a separate substandard (5G NTN) seems to be the most promising, which will probably ensure both higher communication quality and a seamless transition between terrestrial and satellite network segments.
As an example of a technology that is developing at a slower pace than expected, but at the same time has discovered an interesting niche, it is necessary to note eSIM and roaming communications: the lack of need to spend time buying a physical SIM card at the airport, the ability to choose the optimal tariff in advance and “install” the card into the phone has created a new type of mobile communication service.
In the field of artificial intelligence (AI), there is an active search and targeted implementation of solutions with understandable commercial effect in internal business processes (integrated chatbots, advanced analytics and HR tools, automation of contact centers, robotics) and certain types of commercial products (for example, software development and working with legal documents). Separately, it is worth noting various types of activities in the field of content creation (including amateur one): the expansion of the use of AI tools can have a significant impact on other industries, such as film production and UGC video services, both by reducing cost and increasing the variety of offerings. In general, the key direction in the field of AI (primarily generative) in the medium term — in addition to the ongoing race to increase the quality and capabilities of “ultimate” models — will be the search for ways to reduce the cost of training and retraining — in general, solving issues of economic efficiency and financial accessibility. Potentially, these areas can lead to the discovery of fundamentally new architectures and algorithms, which we can already see in the example of research in the fields of agent systems, specialized processors, the progress of “reasoning” models (which ensure an increase in quality and capabilities, including by “shifting” computational costs from the learning stage to the inference stage), and systematic use synthetic data from large models for training small ones. In addition, explosive growth in the field of robotics is possible due to synergies with generative and other types of AI models.
Issues of global politics, economics and demography — such as de-globalization, isolation of local markets, restrictions on the global Internet or the activities of digital giants, aging and population decline — already directly affect most companies on the path of technology development, creating well-known problems in supply, in attracting staff, but at the same time opening up new ones.