Agentic AI’s meteoric rise has IT leaders scrambling to redefine their CPU and GPU estates.
The growing adoption of agentic AI will require IT leaders to rebalance their CPU and GPU estates, tightly integrate data layers, and redesign human workflows, according to Dell Technologies CTO John Roese. This seismic shift in enterprise architecture is being driven by the increasing complexity and sophistication of AI systems, which are now capable of making decisions autonomously and adapting to new situations.
**Agentic AI’s Unique Requirements**
Agentic AI, a subset of artificial intelligence that enables systems to take independent action, has transformed the way organizations think about enterprise architecture. Unlike traditional AI, which relies on pre-programmed rules and data, agentic AI requires a more fluid and dynamic approach to processing and analysis. This means that IT leaders must rethink their use of CPU and GPU resources, as agentic AI systems demand more flexible and scalable architectures.
For example, agentic AI systems require access to vast amounts of data, which must be integrated across multiple layers and sources to support real-time decision-making. This has led to a proliferation of data lakes and warehouses, which in turn has created new challenges for data governance and management.
**Redesigning Human Workflows**
As agentic AI systems take on more responsibilities, human workflows are also undergoing a radical transformation. With AI systems making decisions autonomously, human workers are free to focus on higher-level tasks that require creativity, empathy, and critical thinking. However, this shift also requires IT leaders to redesign workflows and processes to take advantage of AI’s capabilities.
According to John Roese, IT leaders must prioritize the development of more agile and adaptive workflows that can evolve in response to changing business conditions. This will require a more collaborative approach to IT, with humans and AI systems working together to achieve common goals.
**What this means**
The growing adoption of agentic AI will require IT leaders to think differently about enterprise architecture and human workflows. By rebalancing CPU and GPU estates, integrating data layers, and redesigning human workflows, organizations can unlock the full potential of AI and drive business success. In short, it’s no longer just about building a robust AI system – it’s about creating a whole new ecosystem that can support autonomous decision-making and drive real-time innovation.
