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Core Insights - The article highlights the challenges faced by CEOs in scaling generative AI technology, with only 36% of global companies expected to achieve large-scale application by 2024, and just 13% having realized quantifiable financial returns in the past year [1][3] - There is a significant gap between the desire for AI adoption and the actual realization of its value, as many companies struggle to understand how to effectively implement generative AI for business benefits [1][4] Group 1: Current State of AI Adoption - Companies in China are increasingly recognizing the potential of generative AI, with over 57% of surveyed firms believing that AI solutions will see large-scale usage this year [4][3] - The focus of AI applications is shifting from non-production areas to more complex sectors like supply chain and R&D, indicating a deeper integration of AI into core business functions [6][4] Group 2: Challenges in Implementation - Companies face various challenges in implementing AI, including data governance, model selection, and interaction design, particularly in non-production scenarios [6][9] - The lack of a "middle layer" in data management complicates the deployment of AI, as many firms struggle with fragmented knowledge and data [8][9] Group 3: Strategic Approaches - To successfully implement AI, companies need a robust digital foundation, including GPU or cloud infrastructure, and must focus on essential applications like document management and knowledge sharing [13][14] - A comprehensive architecture that integrates digital platforms, data, AI, and security measures is crucial for maximizing the benefits of generative AI [14][16] Group 4: Future Outlook - The potential for productivity growth through generative AI is significant, with projections indicating that medium-growth companies could see productivity increases from 1.9% to 15.9% [12] - Companies that have effectively digitized their operations are better positioned to adapt to the evolving AI landscape, emphasizing the importance of resilience and adaptability in the face of technological change [15]