IBM(US:IBM) Xin Lang Ke Ji·2025-05-26 03:31Core Viewpoint - The integration of generative AI into business processes is becoming increasingly important for companies, as they seek to automate IT and business workflows effectively [1][2]. Group 1: Generative AI Integration - Companies are facing challenges in integrating AI capabilities into their operations due to issues related to data, systems, processes, and infrastructure [1]. - Gartner predicts that the proportion of enterprise software incorporating autonomous AI will rise from less than 1% in 2024 to 33% by 2028, with over 15% of daily work decisions being made by AI agents [1]. Group 2: Key Elements for Enterprise AI Development - Five essential elements for enterprise AI development include: 1. Data, which is the core productivity factor and must be of high quality [2]. 2. Models that incorporate both AI large models and internal expert knowledge [2]. 3. Security governance for data, models, and applications [2]. 4. Intelligent assistants or systems [2]. 5. Intelligent agents, which are often misunderstood but are essentially advanced applications with AI capabilities [2]. Group 3: IBM's AI Capabilities and Investments - IBM has invested $17 billion in automation over the past three years, including the acquisition of HashiCorp to enhance software-defined infrastructure automation [3]. - Users employing IBM's integrated automation tools in hybrid environments can achieve a return on investment of up to 176% within three years [3]. - IBM is upgrading its watsonx.data platform to unify and govern data across various environments, facilitating AI applications and intelligent agents [3]. Group 4: Business Growth through AI - Companies require flexible, secure, and cost-effective AI platforms and tools to integrate data, automate workflows, and drive business growth [4]. - IBM aims to assist companies in rapidly building and scaling AI capabilities that align with their business objectives, ensuring governance throughout the AI lifecycle [4].