2025年技术趋势报告

Industry Investment Rating - Hardware and infrastructure are currently in focus, with enterprise IT spending expected to shift accordingly [1] Core Perspectives - Hardware is reclaiming the spotlight as AI demands specialized computing resources, leading to advancements in chips and integration into end-user devices [51] - AI is transforming the IT function, with generative AI driving a shift from virtualization to AI-driven automation and innovation [51] - Core systems, particularly ERP platforms, are increasingly seen as critical assets, with the global ERP market projected to grow at 11% from 2023 through 2030 [18] Hardware and AI Integration - AI-embedded PCs are expected to future-proof technology infrastructure, reduce cloud computing costs, and enhance data privacy [120] - The market for chips used only for generative AI is projected to reach over $50 billion in 2024 [120] - AI hardware is poised to revolutionize the Internet of Things and robotics, with advancements in energy efficiency and sustainability [51] AI and IT Transformation - Generative AI is driving a shift in IT from a cost center to a competitive differentiator, with 60% of US-based technology leaders now reporting directly to their CEOs [13] - AI is expected to fundamentally change the role of IT, making it leaner but with a wider purview [13] - Enterprises are increasing investments in data-life-cycle management due to generative AI, with 75% of organizations surveyed reporting such increases [13] Spatial Computing - Spatial computing is breaking down information silos and creating more natural ways for workers and customers to interact with information [51] - The spatial computing market is projected to grow at a rate of 18.2% between 2022 and 2033, with applications in healthcare, manufacturing, logistics, and entertainment [63] - AI advancements are expected to lead to seamless spatial computing experiences and improved interoperability [51] AI Models and Applications - Enterprises are moving from large-scale AI projects to AI everywhere, with a focus on small language models, multimodal models, and agentic AI [87] - Small language models can be trained on smaller, highly curated data sets to solve specific problems, reducing time and effort [87] - Agentic AI is expected to transform how we work and live, with AI agents capable of executing discrete tasks autonomously [27] Robotics and Automation - Robotics and automation are becoming mainstream, with smart factories using computer vision, sensors, and data to build machines that can learn and improve [3] - Humanoid robots are expected to perform a broad variety of tasks, from cleaning sewers to performing surgeries, addressing labor shortages and freeing up human time for creative tasks [145] - The integration of AI into robotics could revolutionize manufacturing and other physical labor industries [135]