联想智库发布2026企业AI十大趋势，揭示AI产业发展方向

Core Insights - The core viewpoint of the article is that by 2026, artificial intelligence (AI) technology will transition from "concept validation" to "deep integration into industries," with companies facing challenges in aligning AI with business strategies and organizational structures to achieve value creation rather than just efficiency improvement [2][3]. Group 1: Key Trends in AI - The report identifies ten major trends in enterprise AI, including the shift from "+AI" to "AI+" leading to the emergence of AI-native companies [3][4]. - The payment model for AI services is evolving from token-based payments for large models to result-based payments for intelligent agents, emphasizing business value over technology costs [7]. - The criterion for selecting and applying large models is shifting to "model-computing efficiency," which considers both model performance and computing costs [8][9]. Group 2: Knowledge and Governance - The standard for knowledge governance is transitioning to "AI-Ready," where knowledge is structured and can be effectively utilized by AI systems [10]. - AI governance is moving from a reactive to a proactive approach, focusing on building trust and resilience through comprehensive governance frameworks [11]. Group 3: Infrastructure and Demand - There will be a significant increase in demand for reasoning power as AI applications move from proof of concept to large-scale deployment, marking 2026 as a pivotal year for enterprise computing power procurement [12]. - The integration of software and hardware is driving a revolution in computing efficiency, with a focus on end-to-end optimization [13]. Group 4: Cost and Sustainability - The evolution of AI infrastructure is shifting towards a unified approach that integrates computing and energy, emphasizing cost and carbon efficiency [14]. - The concept of "Robot as a Service" (RaaS) is facilitating the scaling of physical AI capabilities in industries like logistics [15]. Group 5: Innovation in China - The development path of AI in Chinese enterprises is characterized by a dual drive of "domestic innovation" and "open-source accessibility," leading to a unique paradigm for AI growth [16].