At the moment, humanity has almost fully realised the potential of weak AI. By 2030, strong AI will start to develop, which will be equal to human intelligence and able to understand all aspects of human thoughts and emotions. AI acts as a driver that multiplies technological progress by facilitating the development of other digital technologies.

Generative AI, computer vision and predictive analytics are the main AI technologies that are used both independently and in addition to other digital technologies, significantly increasing their efficiency. The main digital technologies where AI is used are: augmented and virtual reality, robotics, chatbots, unmanned and autonomous vehicles, and digital twins.

The markets of digital technologies that already use artificial intelligence (unmanned vehicles, chatbots) will grow 3-5 times. Digital technology markets that are just gaining momentum in the use of AI (AR/VR, digital twins) will grow 6-11 times. The key drivers are increasing labour productivity, reduced errors, improved quality of services and increased availability of structured data in a growing number of industries.

The main AI development driver industries will be healthcare, education, agriculture, construction, security and high-tech manufacturing.

The key risks of AI development are related to the threat of its criminal use in the creation and distribution of fake information, as well as the violation of privacy when AI gains unauthorised access to personal information.

Generative AI

Generative AI converts input data (text, images, files, etc.) into any content: text, code, speech, music, images, video, 3D models, animation. The generative AI markets that will achieve the highest growth by 2030 include healthcare (12x), education (10x), construction (7x), entertainment and video games (6.5x), and media and communications (3.5x). Among the drivers of this growth is AI's ability to imitate human behaviour, automate content creation and personalise learning plans, thereby transforming the functioning of these industries. In the world, generative AI is already becoming a key part of many business processes, while in Russia it is still exotic and is used in small projects to solve local problems.

Computer vision

There are 3 main types of computer vision: image recognition, face recognition and speech recognition. The first is used for automatic classification and sorting of content, the second is used in security systems, device unlocking and social media, and the third is used for call centre automation and more. The computer vision markets that will achieve the highest growth by 2030 include transport (9.5x), healthcare (9x), security via video surveillance (2x), and engineering (1.6x). The role of computer vision will significantly expand in improving the accuracy of disease diagnosis, in the efficiency of security systems, and in reducing human labour costs in surveying and mapping. In Russia, computer vision is developed primarily in the security sector, while the rest of the world is introducing it steadily in manufacturing, medicine and other industries.

Predictive analytics

There are 4 main models of predictive analytics: classification model, clustering model, regression model, neural networks. Predictive analytics is most developed in healthcare (predicted to grow 4.6x by 2030, with a market size of $64bn). Predictive analytics is also developing in the industrial, transport, and financial sectors (4x, 3.8x, and 3.7x, respectively). This growth is due to the growing dependence on data to make informed decisions, which emphasises the role of predictive analytics in technological progress. Russian businesses are taking their first steps to implement predictive analytics, drawing on international experience. International best practices are 2-3 years ahead of Russia's development in this area.

Chatbots

Chatbots are based on natural language technologies: natural language processing (user intent recognition, entity extraction, sentiment analysis), natural language understanding, natural language generation, generative AI. The greatest potential for the adoption of chatbots by 2030 is in the financial sector (5x), healthcare (4x), retail and e-commerce (3.5x), and tourism (3x). The growth is driven by significant progress in natural language processing and growing demand for customer service automation. Russia is not lagging behind the global trends in the development of chatbots. The main purpose of chatbots is to communicate with and support customers.

Augmented and Virtual Reality (AR/VR)

AR/VR uses almost all available AI technologies: computer vision, generative AI, natural language processing, recommendation systems, simulation and behavioural modelling. The fastest growing areas for AR/VR include retail and e-commerce (11.3x by 2030), tourism (9.2x), education (6.3x), video gaming (6.2x), and healthcare (5.3x). This growth is driven by demand for immersive experiences and personalised experiences, indicating the transformative potential of AR/VR in engaging consumers. The use of specialised AR and VR platforms in Russia is underdeveloped, while in the consumer sector it is in line with the global level.

Unmanned and autonomous vehicles

Autonomous vehicles use AI non-stop: computer vision to recognise traffic situations; machine learning and deep learning to analyse data from sensors and cameras; predictive analytics to predict the actions of other road users; and route planning and decision-making systems to determine the optimal route. The segments of the unmanned and autonomous vehicles market that will achieve the highest growth by 2030 include passenger cars (3.6x), trucks (2.2x), unmanned aviation systems (1.9x), agricultural machinery, water and rail transport (1.8x). The main focus is on improving vehicle efficiency, traffic safety and reducing human labour costs for operation. In all major areas of development of unmanned and autonomous vehicles, except for rail transport, Russia, in general, does not lag behind global trends.

Robotics

The main AI technologies supporting the development of robotics are computer vision, natural language processing, edge computing and mixed reality. The greatest potential for robotics adoption by 2030 is in the service sector (7.5x), logistics and healthcare (3x), and manufacturing (2.3x). This growth reflects the increasing role of robotics in automating routine tasks and improving efficiency and quality of service in various industries. In all areas of robotics application, except for manufacturing, Russia is not lagging behind the world.

Digital twins

Digital twins utilise 4 main technologies: the Internet of Things, machine learning, cloud computing and AR/VR. The fastest growing areas for digital twins by 2030 are healthcare (9x), manufacturing (7.7x), and construction (7.7x). The automotive segment accounts for 44% of the market for AI technologies in manufacturing, which will grow 6.7x by 2030. This growth underlines the importance of digital twins for modelling, analysis and optimisation in various sectors, highlighting their role in future technological development. Russia is keeping pace with global trends in the development of digital twins in key areas of the economy.