The future of artificial intelligence in the ski industry

Infrastructure and Application Solutions

China is developing AI not only as a high-tech sector but also as a part of everyday life. Today, algorithms are used in millions of applications:

– In the financial sector, AI processes hundreds of millions of transactions per day;

– In healthcare, it helps doctors make diagnoses and plan treatment;

– In education, it supports adaptive learning;

– In industry, it manages “smart” production facilities.

– AI has a distinct role in facial recognition and video surveillance, which raises privacy concerns but gives the government useful tools for control.

Science and Business Interaction

Academic and commercial domains are closely integrated in the Chinese AI development model. The government encourages partnerships between universities and companies, and many researchers also work at corporations such as SenseTime, Megvii, and iFlytek.

This enables the nation to quickly implement the results in products while simultaneously producing a large number of research publications. China already ranks first in the world in terms of the number of research articles and patents related to AI.

Regulation and Control

The development of AI in China is accompanied by clear and strict regulation. In 2023, the authorities introduced the world’s first official rules for generative AI, including mandatory registration of AI services and filtering of unwanted content.

This approach reflects the philosophy of “controlled innovation”: the state strives to use the capabilities of AI while minimizing risks, both political and social. China also takes an active part in international discussions on technology regulation and supports the idea of international coordination in this area.

Geopolitics and Technological Independence

As the technological confrontation with the United States intensifies, China is working to lessen its reliance on foreign parts, particularly American artificial intelligence chips. The government is investing in the growth of its own semiconductor industry and infrastructure for model training. Simultaneously, China is strengthening ties with other countries, developing AI partnerships in Asia, Africa, and Latin America, promoting its own digital platforms abroad, and exporting technologies as part of the Belt and Road Initiative.

Perspective through 2030

By 2030, China expects:

– surpass the United States in total AI infrastructure capacity;

– achieve technological autonomy in key areas;

– turn AI into the foundation of the digital economy.

– China claims to be the second center of power in the AI world, with the potential to become the first due to its centralized management, widespread implementation, and quick development of generative models.

3rd place – Great Britain: European Center for Responsibility, Science, and Ambition

Figure 1.8

The UK confidently holds the third place in the world in terms of the influence and maturity of the AI ecosystem. Both research and commercial technologies, including generative AI, are actively developing in the country. Leading researchers, multinational companies, and startups are drawn to London and Cambridge, which have developed into innovation hubs.

The UK is the top European country and the third globally (after the US and China) in terms of private investment in AI in recent years. It was also the first country to officially declare its intention to take a leadership position in AI security and ethics, especially in relation to generative models.

Investments and Government Initiatives

The UK actively supports AI at the national strategy level. Adopted in 2021, the UK National AI Strategy program aims to support startups, foster long-term technological development, and increase societal trust in AI. In 2023, the government established the Foundation Model Taskforce, the foundation for advanced AI models, and allocated £100 million for the creation of British language models and AI infrastructure.

Additionally, the authorities invested another £100 million in the expansion of the Alan Turing Institute, the largest AI research center in the country. In order to boost domestic growth and lessen reliance on outside resources, the British government also announced plans to build a national supercomputer and data centers for training large models.

Generative AI and Key Projects

The UK has played an important role in the development of generative AI. DeepMind, a Google subsidiary widely known for its breakthrough projects AlphaGo and AlphaFold, is based in London. It continues to participate in the development of open-access advanced models and algorithms.

The Stability Diffusion project, a London-based Stability AI startup, was established in 2022 and became one of the first democratized image generation models. Thanks to this development, generative algorithms are now freely available to thousands of users worldwide for creative and commercial purposes. The country saw the emergence of a number of new generative AI startups in 2023—2024, with a focus on text, visual, and audio platforms.

Research and Academic Environment

The Alan Turing Institute brings together scientists, engineers, and policymakers researching AI from an interdisciplinary perspective. In addition to fundamental discoveries in machine learning, the center pays special attention to issues of ethics, explainability, and fairness of algorithms. Major universities, including Cambridge and Oxford, are actively cooperating with the industry, and British postgraduate schools remain among the best in the world for training AI specialists. The nation is also making investments in staff training and educational initiatives; over the next several years, more than 1,000 new generative AI specialists are expected to be trained.

Regulation and International Coordination

The UK was one of the first to initiate an international dialog on the regulation of generative AI. The first AI Security Summit in history took place at the renowned Bletchley Park in November 2023, with representatives from 28 countries, including the US, China, and the EU, in attendance. They discussed the risks associated with large language models, including their possible impact on society, the economy, and security.

Prime Minister Rishi Sunak declared during this summit that the UK would act as a coordinator for global AI regulation and the promotion of common standards. The government is also establishing the AI Safety Institute, a specialized body tasked with testing, certifying, and auditing AI models before mass adoption.

Economics and the Startup Environment

The British startup ecosystem is still the most developed in Europe. In terms of the number of AI unicorns, the UK ranks third in the world (after the USA and China), ahead of France, Germany, and Canada. Well-known companies include Stability AI (image generation), Darktrace (cybersecurity with AI), Synthesia (AI-based video), Faculty AI (data analysis for businesses and government agencies).

London remains attractive for venture capital, and the open legal environment and access to English-speaking markets are contributing to the growth of companies focused on the global user.

Forecast through 2030

The UK relies on a combination of innovation, openness, and ethics. The country plans to:

– ensure independence in teaching and implementing large language models;

– create its own cloud and computing infrastructure;

– consolidate the role of a leader in international AI coordination and security.

By 2030, the UK is expected to become a European center for generative AI, focused on humanistic values, a high standard of transparency, and technological sovereignty.

4th place – France: the European Engine of Open and Sovereign AI

Figure 1.9

France occupies a key position in the European AI ecosystem and seeks to create an alternative to English- and Chinese-centric AI models, focusing on openness, multilingualism, and technological sovereignty. AI is seen by the government as a strategic industry that can guarantee both economic growth and technological independence in vital areas. The French AI development model is based on three pillars: a strong academic base, an actively growing startup sector, and a strict regulatory framework focused on protecting citizens’ rights.

Government Strategy and Investment

President Emmanuel Macron was one of the first European leaders to declare AI a national priority. The AI for Humanity program, which allocated €1.5 billion in investments, was launched in 2018. In 2021, a new phase of the program was launched, with a budget of more than €2.2 billion until 2025, including funding for research, commercialization, and training.

In 2023, the authorities announced the allocation of another €500 million to support “national AI champions,” including startups working with large language models. France is also involved in joint EU investment initiatives, including projects to create European data centers, supercomputers, and cloud platforms.

Generative AI and Technological Advances

In an effort to provide European alternatives for OpenAI or Google products, French researchers and businesses are actively working on generative models. BLOOM, an open language model with 176 billion parameters, is one of the most significant recent projects. It was developed as a component of the BigScience international scientific project in Paris, which was coordinated by Hugging Face. This model has grown to be a landmark achievement, demonstrating that Europe is able to develop competitive, large-scale solutions founded on open-access principles.

The French startup Mistral AI was established in 2023 with the goal of developing independent European Large Language Models (LLM). The company raised over €100 million in its first few months of operation, and its initial models were actively used in public and business applications.

Academic and Startup Ecosystem

France has a powerful AI academic school. Organizations such as INRIA (National Institute for Research in Digital Science and Technology), CNRS (French National Centre for Scientific Research), as well as leading engineering universities (École Polytechnique, ENS Paris, HEC) are actively involved in the development of algorithms, theories, and applied models. The government funds the creation of interdisciplinary AI centers and national AI schools and supports the international mobility of young researchers.

The French startup environment is also thriving. In addition to Mistral and Hugging Face, notable projects include:

– LightOn, that develops optical AI processors and large language models;

– Nabla, that implements generative AI in medical services;

– Owkin, that works with biomedical data and AI for clinical research.

– France is proving that it can be both entrepreneurially flexible and scientifically rigorous.

Regulation and Leadership in Ethics

France is one of the main ideologists of ethical and responsible AI in the international arena. It was the French representatives who led the development of UNESCO’s “Recommendation on the Ethics of Artificial Intelligence,” adopted in 2021. The country actively supports the adoption of the European AI Act, the first comprehensive law on AI regulation, which is expected to go into effect in 2024—2025.

In its domestic policy, France demands that AI products comply with the principles of transparency, fairness, and explainability. These standards are particularly relevant for generative AI, from text and image applications to automated decision-making systems in the public sector.

International Influence

Paris has made a commitment to represent Europe on the international AI agenda. France regularly organizes international conferences (Global Forum on AI for Humanity), promotes the ideas of open scientific collaborations, and actively participates in multilateral alliances, including GPAI (Global AI Partnership), OECD, and UNESCO.

The country is also building bilateral scholarly and technological ties, for example, with Germany, Great Britain, and Canada. France is in favor of building a pan-European computing infrastructure and making models publicly available so that the EU can compete with China and the US, two of the world’s largest technology giants.

Forecast through 2030

By 2030, France intends to:

– consolidate leadership in open and multilingual generative models;

– ensure the EU’s strategic autonomy in AI;

– create a “French-style AI model” that combines technology, humanism, and public trust.

France is developing a reputable and respected alternative to the American and Chinese approaches to AI by fusing a solid scientific foundation, government support, and a strict regulatory approach.

5th place – Germany: Industrial AI and Digital Sovereignty of Europe

Figure 1.10

With a focus on practical applications for business, logistics, healthcare, and energy, Germany is one of the top nations in the world for AI development. The German strategy blends rigorous engineering, in-depth scientific research, and the goal of securing Europe’s technological independence. The government sees AI as the foundation of the future “Industry 4.0,” a highly automated, flexible, and sustainable manufacturing economy. At the EU and international organization levels, Germany is also actively participating in the creation of ethical and legal standards for AI.

Government Strategy and Financing

In its National AI Strategy, which was adopted in 2018, the German government stated its goal to become a global leader in this area. The initial budget was €3 billion until 2025, but it was subsequently expanded with private investment to reach more than €6 billion. The funding is allocated to research center development, AI professorships (more than 100 positions), interdisciplinary platform development, computing infrastructure expansion, and the integration of AI into small and medium-sized enterprises. Germany is also involved in financing European initiatives, including Gaia-X (the European Cloud Infrastructure Project), EuroHPC supercomputers, and common efforts to create “sovereign” LLMs within the EU.

Generative AI and Key Projects

Although Germany is not as vocal in generative AI as the United States or France, it has already demonstrated potential in this area. One of the key players was the Aleph Alpha, a startup from Heidelberg, which has developed a multilingual large language model, Luminous, capable of competing with GPT-3. A special feature of the project was the attention to explainability and transparency, which are important aspects for a legal and state-oriented environment.

Germany also participated in the international development of Stable Diffusion, with one of the authors of the algorithm, L. Rombach, representing the University of Munich. The model has become the basis of an open-source generative tool that is actively used worldwide. Prominent universities such as the Technical University of Munich and the Max Planck Institute are vigorously developing research in neural networks, diffusion models, and multimodal systems.

Applied implementation and industry

AI is widely used in the industrial and corporate sectors:

– Siemens introduces AI into automation and power management systems;

– Volkswagen and BMW use machine learning algorithms to optimize logistics, quality control, and autopilot development;

– Bosch develops AI solutions for smart manufacturing and the Internet of Things (IoT).

Germany focuses on highly responsible AI systems functioning in the real sector rather than on mass content creation. Reliability, testability, and legal certainty – qualities for which the nation has long been renowned – are essential in the real sector.

Academic Foundation and Personnel

The DFKI, German Research Center for Artificial Intelligence, remains one of the largest and oldest in Europe. In collaboration with academic institutions, it runs extensive programs for specialist education and training. Network cooperation is also actively developing: the government finances innovative AI centers in 12 regions, each of which specializes in a certain industry (medicine, agriculture, transport, etc.). The Digital Hub Initiative program helps connect academia and business, and the KI für KMU program (AI for Small and Medium-sized Businesses) provides entrepreneurs with access to AI technologies through consulting centers and grants.

Regulation and International Influence

Germany is an active participant in the development of the European AI Act, advocating a balanced approach between innovation and the protection of human rights. Particular attention is paid to banning high-risk AI applications, ensuring transparency of algorithms, and access to explicable results. In the international arena, Germany is building partnerships within the EU, participates in the G7 and the OECD, and actively supports sustainable AI standards. The country also seeks to preserve Europe’s technological sovereignty by investing in local data centers, cloud platforms, and training its own models.

Perspective through 2030

By 2030, Germany plans to:

– integrate AI into all key sectors of the economy;

– complete the formation of a national infrastructure for model training;

– establish partnerships within the EU to guarantee a presence in the global race for generative AI.

The country continues to build a European-type AI platform that is rigorous, verifiable, integrated into industry, and meets high standards of human rights protection. Priority is given to quality, control, and long-term sustainability, an approach that is likely to ensure Germany’s stable role in the global AI landscape.

Table 1.1 – Global Ranking of Countries in Research and Development of AI Technologies (2025)

1.6. Global trends and forecast though 2030

Figure 1.11

The last two years have seen a rapid evolution in AI development, transforming it from a field of technological enthusiasm into a potent instrument of cultural, political, and economic competition. Generative AI has become one of the most dynamic areas of this transformation, and countries that have been able to react quickly to the emergence of new technology are already gaining competitive advantages. Six major trends that influence the course of AI development until 2030 can be found based on the analysis of ten top nations.

– World leadership is distributed between two centers of power. The United States and China continue to set the pace of the race. The United States relies on private investment, a startup ecosystem, and international influence, while China is building a centralized, large-scale implementation system with strong government support. The gap in model quality between the two countries is narrowing, especially in languages other than English. By 2030, they will remain the main technological competitors and ideological opponents in matters of AI regulation.

– Europe is strengthening its position as a center of “responsible AI.” The UK, France, and Germany are building their own development model focused on security, transparency, citizens’ rights, and technological sovereignty. The European AI Act and similar initiatives form the basis for future regulatory legislation. By 2030, Europe can become a global AI ethics reference and exporter of regulatory standards.

– Generative AI goes beyond laboratories. While generative models remained the subject of technological demonstrations in 2022, by 2025 they had already begun to be actively used in education (personalized learning), medicine (diagnostics, image analysis, medical bots), the corporate sector (workflow automation, analytics), and the creative industry (texts, images, music, and videos). By 2030, generative AI will become a massive tool in most industries, like the Internet or smartphones.

– Investments are shifting from hypergrowth to infrastructure. The 2023—2024 investment boom will be followed by a phase of thoughtful scaling. The leading countries are investing not only in models but also in data centers and supercomputers, their own chips and accelerators, localized computing power, AI testing, auditing, and certification systems. An essential phase in the development of AI is the shift from “high-profile launches” to institutionalization.

– Regulation is becoming a global agenda. People realize that the lack of control over AI models creates threats, from fakes and manipulation to errors in decision-making systems. By 2030, a set of international standards is likely to be formed. It will define the risk levels of AI systems, requirements for transparency and explainability, and mechanisms for accountability and tracking. Countries that can offer balanced solutions will gain diplomatic and reputational advantages.

– The next wave is multimodal and universal models. The generative AI of the future is not just about text or an image. Major technological players are already developing multimodal systems capable of understanding and generating language, speech, video, tables, code, and actions. They will form the basis of the next generation of smart assistants – more contextual, personalized, and autonomous. By 2030, they may serve as the foundation for digital platforms as well as autonomous agents in science, business, and daily life.

Conclusion

AI is a new technological axis that is reshaping the global order of the 21st century. Leading countries not only invest and develop but also set the rules by which the digital world will live. Those who shape the framework of generative AI today also shape the future of creativity, thinking, and human-machine interaction in the decades to come.

1.7. The risk of using AI

Figure 1.12

Along with the obvious advantages, there are certain risks of further use of AI:

– Ethical risks. The bias of developers may be reflected in AI programs and algorithms, resulting in discriminatory or inaccurate decisions. The establishment of ethical standards should receive particular attention in order to prevent a detrimental effect on society.

– Loss of jobs. Certain industries may experience job losses as a result of AI-driven work process automation. This raises questions of social justice and the need to create new employment opportunities for those who lose their jobs due to automation.

– Data security and privacy. There is a greater chance of data security and privacy being compromised as AI advances. Hacker attacks can target systems, and users may suffer severe consequences if large volumes of personal data are accessed without authorization;

– Autonomous systems. The use of autonomous AI-based systems, such as self-driving cars or robots, poses new security challenges. Possible incidents and accidents require the development of strict norms and standards to prevent them.