Gen AI adoption is on the rise. Despite being a relatively new technology, generative AI has captured the public and professional imagination and is quickly becoming a widespread phenomenon. Most organizations are already using GenAI for at least one use case, with many looking to expand this function across their business. But are they ready to implement this new technology at scale? The challenge for many enterprises comes down to being prepared from an infrastructure perspective.

Cost, data quality, and integration needs are hurdles, but security remains the top concern for 38% of respondents in a recent survey. Within the field of security, it is data privacy, confidentiality, potential misuse, and unauthorized access that all pose serious challenges. If GenAI is to be introduced at the enterprise level and deployed across multiple verticals, companies must be equipped to answer these security questions. Increasingly, this means finding the right vendor partners to lead them through this journey.

Join Jo Peterson and her panel of expert guests in this first episode of Cloud Cover in 2025. The conversation will explore the spectrum of deployment options, from public to fully private, as well as recent thinking on key criteria for selecting a vendor and a deployment model.

Enterprise Infrastructure for Generative AI

As artificial intelligence (AI) continues to revolutionize industries, the need for more flexible and efficient infrastructure to manage AI workloads has become paramount. Hybrid AI, which enables the intelligent routing of AI workloads between artificial intelligent personal computers (AI PCs) leveraging small language models and cloud servers for large language models, is emerging as a critical solution.

Hybrid AI: The Future of Intelligent AI Workload Orchestration from AI PCs to the Cloud

AI PC

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IT Service Management

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Hybrid AI: The Future of Intelligent AI Workload Orchestration from AI PCs to the Cloud

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Intel-Deloitte