AI / Deep Learning
AI / Deep Learning: Technology Overview
Artificial intelligence technologies have seen a dramatic increase in public and media attention in recent years. The modern AI boom has been driven mainly by more powerful computers, the increased availability of data for training purposes, and better AI and machine learning algorithms. Today, AI is used in countless applications, including search engines, recommendation systems, targeted advertising, virtual assistants, autonomous vehicles, automatic language translation and facial recognition, to name a few.
Deep learning is a key subfield of machine learning. Deep learning uses complex structures called artificial neural networks that are loosely modelled on the human brain. Information flows through numerous layers of interconnected neurons, where it is processed and evaluated. In essence, AI learns by continuously reassessing its knowledge, forming new connections and prioritising information based on new data encountered. The term ‘deep learning’ refers to the vast number of layers that these networks can utilise. AI powered by deep learning has achieved remarkable advancements, especially in areas such as image and speech recognition.
Generative AI (GenAI) is one of the most powerful forms of AI. Unlike old rule-based AI applications, which could only perform a single task, modern GenAI models are trained on data from many different areas and can handle a wide range of tasks. Due to the vast amount of training data, these models can produce creative outputs. Modern GenAI chatbots, such as ChatGPT and Google Gemini, can generate human-like text and hold conversations on a variety of topics, rather than being confined to a predetermined script. Additionally, these chatbots can produce not only text, but also images, music, and computer code based on their training dataset.
Global trends: sharp rise in AI patents
Global Development of AI patents
AI Patents have risen tenfold over the last decade
The current AI boom is reflected in the significant increase in AI patent family publications, which increased from around 8,000 in 2010 to 435,500 in 2025. Even stronger patent dynamics are evident in the field of deep learning, where the number of patent family publications grew from 1,600 to 332,000 during this period. While GenAI currently accounts for only a small proportion of total AI patents (8% in 2025), it has experienced extraordinarily high growth in recent years.
Share of AI of all patent filings over time
Today, 17% of new patent applications are AI-related
Even more impressive is the rise of AI when considering only new patent filings. Between 1980 and 2013, AI patents consistently accounted for less than 1% of all patent filings. In 2017, the year after Google published the influential paper Attention Is All You Need, which introduced the Transformer architecture that underpins all modern large language models (LLMs), the share of AI patents increased to almost 2%. Today, more than 17% of all new patent filings are AI-related.
Deep Learning has become the key AI field
Patent development in different AI areas
70% of AI patents are based on Deep learning
Deep learning has become the leading subfield of AI. In 2025, 70% of all newly published AI patents are in the deep learning field.
Development of deep learning patents in selected applications
Deep learning is transforming various industries
Deep learning is becoming increasingly relevant in the context of mobility, health and industry applications. For example, it is transforming mobility by enabling vehicles to perceive and interpret their surroundings allowing them to detect pedestrians, cyclists and road signs in real time. In healthcare, deep learning is already proving invaluable in diagnostic imaging, where algorithms can detect anomalies in X-rays, MRIs and CT scans with a level of accuracy comparable to or even exceeding that of human experts. In industry, manufacturers use deep learning for quality control, identifying minute defects on assembly lines, and for predictive analytics, optimising energy use and reducing downtime.
Top research countries in AI/deep learning
Published patents per inventor country/region in AI
In terms of sheer number of patent publications in AI/deep learning, China is in a league of its own. As the graph below shows, China publishes more AI patents than all other countries combined. In 2025, around 332,500 AI patents came from China, compared to only around 28 thousand from the US.
Published patents per inventor country/region in Deep Learning
In terms of sheer number of patent publications in AI/deep learning, China is in a league of its own. The same picture emerges within deep learning. In 2025, China published almost 255,000 deep learning patents.
Active world-class patents per inventor country/region in AI
When only looking at active world-class patents, China’s lead is smaller. China had almost 82,000 AI world-class patents in 2025, compared to around 58,000 in the US.
Active world-class patents per inventor country/region in deep learning
China has around 64,000 world-class deep learning patents. The US is in the second place with around 34,500, Europe has 8,800 world-class patents, Japan and South Korea have less than 4,000.
AI / deep learning use in key application technologies
Key connected technologies for AI – country activities
Key connected technologies for Deep Learning – country activities
Top research companies in AI / deep learning
Bar Chart Race AI
Tencent currently holds most active world-class patents in AI
Until 2018, US tech companies such as Alphabet, Amazon, Microsoft and Qualcomm dominated AI / deep learning research and held the largest number of world-class patents. Since then, however, certain Chinese companies, first Ping An and later Tencent and Baidu, have climbed to the top positions in terms of active world-class patents.
OpenAI, now synonymous with GenAI following the success of ChatGPT, did not file any patents until early 2023. This reflects its origins as a non-profit organisation dedicated to open research and open-source releases, before shifting to a ‘capped’ for-profit model with Microsoft as a major investor. Anthropic has also only recently started filing patents.
Bar Chart Race Deep Learning
Tencent currently holds most active world-class patents in deep learning
Until 2018, US tech companies such as Alphabet, Amazon, Microsoft and Qualcomm dominated deep learning research and held the largest number of world-class patents. Since then, however, certain Chinese companies, first Ping An and later Tencent and Baidu, have climbed to the top positions in terms of active world-class patents.
OpenAI, now synonymous with GenAI following the success of ChatGPT, did not file any patents until early 2023. This reflects its origins as a non-profit organisation dedicated to open research and open-source releases, before shifting to a ‘capped’ for-profit model with Microsoft as a major investor. Anthropic has also only recently started filing patents.
