Modern enterprises are looking out for secure, user-friendly, and versatile solutions for infrastructure development. This strategic endeavor aims to promote innovation and operational efficiency while facilitating the scalable delivery of products and services.
The emergence of disruptive technologies like AI is poised to reshape infrastructure management, elevating efficiency, reliability, and security. Given the increasing intricacies and prevalence of AI, there is a compelling necessity for advanced infrastructure management solutions to ensure smooth integration.
In a closed door discussion curated by CORE Media, powered by AMD, CIOs and Digital Leaders explored high-performing, secure, and efficient solutions for the seamless adoption of AI for efficient infrastructure management.
Sudhir Kamath, Country Director, CORE Media opened the conversation by talking about the need of robust infrastructure to optimize operations that drive business value. Joining him as co-host in this discussion was Vasuki K.S, Country Manager - Enterprise Business & Regional Head, AMD India.
Delving into modern business dynamics, the duo discussed the critical need for enterprises to adopt secure, user-friendly, and adaptable infrastructure solutions, propelling innovation and scalability. They acknowledged the transformative role of emerging technologies, particularly AI, in reshaping infrastructure management.
The session addressed critical aspects such as ensuring effective infrastructure management strategies supporting AI integration across industries, data security and privacy concerns, and outlining AMD's vision and strategies for shaping the future of AI infrastructure management.
Additionally, CIOs disclosed the intricacies involved in incorporating AI, articulating practical challenges encountered in their individual projects. Data silos impeded training efforts, outdated systems demanded restructuring, and skill gaps served as stumbling blocks to progress. Compatibility issues with legacy tools surfaced, accentuated by concerns regarding explainability and resistance to change. They emphasized the necessity for modernized infrastructure, standardized platforms, proficient teams, robust data governance, and agile development to effectively navigate these challenges and unlock the transformative potential of AI.
