By [Your Name], Professional Journalist and Editor
The rapid evolution ofAI is transforming businesses at an unprecedented pace. From intelligent customer service to automated production lines, AI-powered applications are reshaping operational models and competitive landscapes. In thisera of rapid AI advancement, building intelligent systems has become a crucial path for enterprises seeking digital transformation.
Chief Information Officers (CIOs), the key technology leaderswithin organizations, are acutely aware of this shift. While their core responsibility remains information system management, the rise of AI has elevated the importance of Intelligence beyond Information. This dynamic has presented both challenges and opportunities for CIOs and theirrespective business units.
To understand the impact of AI on enterprise CIOs, InfoQ’s C-Suite Face-to-Face series sat down with Alibaba Cloud CIO and aliyun.com head, Jiang Linquan (aka Yan Yang), for a discussion on the evolving role of CIOs in the AI era, the path to enterprise intelligent transformation, AI implementation practices, and talent development.
The Evolving Role of the CIO in the AI Era
InfoQ: How has the role of the CIO evolved in the AIera?
Jiang Linquan (Yan Yang): The fundamental principle remains unchanged: CIOs must align with business strategy, stay close to operations, support business objectives, and leverage information technology to drive business growth. The key difference now is that AI technology is revolutionizing the way information systems are developed, leading tosignificant efficiency gains. This is the most impactful change AI has brought to the CIO role.
I strongly believe that the I in CIO should now stand for Intelligence. CIOs must integrate intelligent capabilities to drive business transformation and guide the evolution of enterprise information systems toward intelligence.
InfoQ: Whatinsights have you gained from the recent wave of AI innovation?
Jiang Linquan (Yan Yang): The past year has witnessed remarkable progress in text-based foundation models. We’ve seen significant improvements with each model upgrade. However, the rate of improvement has begun to plateau. This is particularly evident in therealm of large language models (LLMs).
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