The future of artificial intelligence in the ski industry

– Dependence on technology. With the increasing reliance on AI, there is a risk that society will become too dependent on this technology. In case of failures or anomalies in the work of AI, this can lead to a loss of skills and independence and can become a problem.

– Lack of responsibility. The issue of responsibility for AI decision-making remains a complex one. In case of errors or negative consequences, it is difficult to determine who is responsible: the developers, the owners of the system, or the technology itself.

– Social inequality. Social inequality may worsen as a result of the development and application of AI. Those with access to advanced technology will benefit, while others may be left out, which risks widening the gap in society.

– AI’s limited nature. AI’s capabilities and contextual awareness are still constrained, despite its immense power. This can lead to situations where AI systems draw erroneous conclusions due to incomplete information.

Table 1.2 – The risks of using AI

1.8. How to Make AI Safe for Everyone: Key Steps

Intelligent technologies are developing faster than any laws or habits of society. It is vital to consider the rules of the game, not only new AI functions, if it is to become a trustworthy helper rather than a source of danger. Here are the key areas that can help make the development of AI responsible, safe, and humane:

– Come up with clear and fair rules. It is important to agree in advance on how AI can and cannot be used. Ethical standards can help to avoid discrimination, manipulation, and irresponsible use of technology. Instead of being merely formal, these rules ought to be incorporated into the development process from the start.

– Teaching people to understand AI. AI is already working alongside us – in medicine, education, and business. However, it requires new knowledge to be used consciously. Experts who can do more than simply press buttons should be trained; they should know how and why AI makes decisions, as well as its limitations and dangers.

– Protect systems and data from hacking. Complex algorithms present both opportunities and vulnerabilities. Protection against cyberattacks, fraud, and leaks is becoming a necessary part of any AI system. Without this, trust in technology is impossible.

– Create laws that keep up with technolog. The world is changing, and the legal system must keep up. We need clear laws that determine where AI is acceptable and where it is dangerous. This is especially important for systems that make decisions without human involvement: from loans and diagnostics to transport management.

– Support those whose jobs are changing. AI is able to replace many routine professions. But this should not mean that people are left out. Retraining, new forms of employment, and social support programs are all necessary to ensure that the transition to the AI era is fair and not traumatic.

– Making AI transparent and open. The more complex a system is, the more important it is to understand how it works and what its decisions are based on. This applies to both the data and the models themselves. Openness is the path to trust. People should be able to ask questions and get honest answers from the systems that affect their lives.

1.9. The Potential of AI: Steps beyond the Horizon

Figure 1.13

In the coming years, artificial intelligence will be used not only to optimize individual processes or create generative models but also to solve more complex and ambitious tasks:

– Creation of fully autonomous systems: development of technological solutions capable of functioning without human intervention, from autonomous vehicles and drones to industrial complexes and controlled AI infrastructures.

– Development of intelligent robots: creation of machines capable of performing complex actions in an unpredictable environment, interacting with people, interpreting commands, and adapting to new tasks.

– Formation of elements of artificial consciousness: research in the systems that can potentially demonstrate the properties of self-awareness, the ability to reflect and understand their own role in the context.

– Integration of quantum computing into AI: the use of quantum algorithms for data processing and analysis to solve problems inaccessible to classical computing systems, such as modeling complex molecules, real-time optimization, and cryptanalysis.

– Creation of general-purpose artificial intelligence (AGI): development of universal systems capable of learning, adapting, and solving a wide range of tasks at a level comparable to human intelligence. These systems will have the capacity for knowledge transfer across domains, autonomous decision-making, and creativity.

Figure 1.14

Table 1.3 – The areas of AI application

1.10. Artificial Intelligence in Russia: Key Areas and Developments (2025)

AI in Russia is developing in two main directions:

– Mass consumer technologies (voice assistants, multimodal services, computer vision);

– Corporate solutions and generative models focused on process automation, efficiency improvement, and digital transformation.

Voice and multimodal assistants

– Alice (Yandex)

– It is one of the most popular AI assistants in Russia, available on mobile devices, browsers, speakers, and other “smart” gadgets. Since 2024, Alice has been using the YandexGPT model, which is capable of conducting a logical dialogue, generating texts, poems, explanations, and instructions. Supports multimodality: recognizes images, can describe them, and works with voice.

– “Marusya” (VK)

– VK voice assistant is embedded in the ecosystem of RuStore, VK Music, smart speakers, and TV devices. In 2023—2024, it received the support of the generative model from SberDevices and the opportunity to “talk about certain topics,” create fairy tales, jokes, forecasts, and even answer simple legal or everyday questions.

– Salyut and GigaChat (Sber)

– The Salyut assistant works on the basis of GigaChat, a large language model developed by Sber. Since 2023, GigaChat has become the basis both for a household assistant and for corporate applications in call centers, banking, and workflow. The model has been trained on Russian-language sources, adapted to high security requirements, and is already used in Sberbank products for government and business clients.