创新奇智(02121)公布2025年中期业绩，收入约6.99亿元，同比增长22.26%;毛利约2.45亿元，同比增长 26.55%;期内亏损为6051.3万元，同比收窄67.21%;经调整净亏损668.1万元，同比收窄82.14%。 创新奇智始终重视研发投入和科技创新，确保技术领先。截至2025年6月30日，公司累计申请专利1,394 件，其中发明专利1,145件;累计确权专利630件，其中发明专利407件。"奇智孔明 AInnoGC工业大模 型"通过国家网信办《生成式人工智能服务》备案，成为青岛市首批获得备案的大模型。"奇智孔明 AInnoGC工业大模型"成功入选山东省2025年工业领域行业大模型"揭榜挂帅"攻关项目。此外，公司联 合中国信通院人工智能研究所共同发布《人工智能+製造业应用落地研究报告》，深入剖析人工智能在 制造业技术应用的现状与关键创新方向，并结合创新奇智服务制造业客户的典型案例，揭示人工智能技 术在研发设计、生产制造、运营管理和产品服务等全流程中的智能化升级作用，展现了深刻的行业洞 察。 公司坚持"技术产品+行业场景"双轮驱动的模式，链接上下游合作伙伴，打造产业生态。在工业软件领 域，公司 ...

Core Viewpoint - The industrial sector is transitioning from digitalization to intelligentization, with varying degrees of adoption among companies based on their digital maturity [2][6]. Group 1: Industrial Software Market Growth - The Chinese industrial software market has grown significantly, with total revenue increasing from 72.9 billion RMB in 2012 to 282.4 billion RMB in 2023, and the PLM segment expected to exceed 40 billion RMB by 2025 [3][4]. - The market is projected to reach 657.5 billion RMB by 2030, indicating a robust growth trajectory [4]. Group 2: AI Integration in Industrial Software - The emergence of AI models has revitalized the software industry, leading to increased efficiency and new applications in industrial software [5][6]. - AI's integration is enhancing the intelligence of industrial software products, with companies acquiring AI firms to bolster their capabilities [5][6]. Group 3: Application Scenarios of AI in Industry - AI applications in the industrial sector are categorized into four main areas: data governance, knowledge processing, process optimization, and decision support [9][10]. - Successful implementations include significant improvements in efficiency and product quality, with examples such as a 50% increase in CAE simulation efficiency and a 28.4% reduction in product development cycles in advanced smart factories [8][10]. Group 4: Challenges and Future Directions - Despite advancements, the true potential of intelligent agents in the industrial sector remains underutilized, primarily limited to knowledge-intensive areas [11]. - The industry is moving towards a more integrated approach, aiming to connect various applications and enhance data utilization for broader impact [11].