The AI sector is set to shift from theoretical concepts to practical applications, marked by advancements in AI architectures and the emergence of smaller, more efficient models. This evolution includes the development of 'world models' that offer AI systems a more comprehensive understanding of their environments, leading to more dependable AI agents. A notable trend is the rise of physical AI, integrating AI with physical systems for real-world problem-solving. The focus will be on creating AI products tailored for tangible, everyday use, signalling a move towards pragmatic AI solutions across various industries.
Smaller AI models are gaining traction due to their efficiency and reduced computational demands, making AI implementation more accessible. World models enhance AI's reasoning and decision-making capabilities by providing a richer context. Reliable AI agents are crucial for applications requiring consistent and trustworthy performance. Physical AI represents a significant step in robotics, automation, and IoT, enabling AI to directly interact with and manipulate the physical world. This convergence of AI with practical applications is expected to drive innovation and create value in diverse sectors.
Overall, 2026 is poised to be a transformative year for AI, with the industry prioritising real-world impact and usability. This shift towards pragmatism promises to unlock new opportunities and address existing challenges, paving the way for broader adoption of AI technologies.
