AI agents are nothing new. AI itself was old but is new again, and AI agents and agentic AI are another chapter. Agentic AI, known for its autonomous decision-making and complex goal management, radically transforms enterprise operations. The significant change is that public cloud providers are often not the desired platform of choice. Companies big and small are instead looking for smaller, more distributed platforms, including on-premises hardware servers and smaller devices. Let’s explore the driving forces behind this transition and its future implications for enterprise AI.
Agents are on the rise
Agentic AI refers to artificial intelligence systems designed with autonomous decision-making capabilities, enabling them to act independently to achieve specific goals. We’ve seen many instances of this idea over the years, more recently with personal digital assistants on our phones and devices and automated everything, from home HVAC systems to automobiles.
These systems possess advanced reasoning, learning, and adaptive functionalities, allowing them to process complex information, make informed choices, and execute tasks without continuous human oversight. Using sophisticated algorithms and vast data sets, agentic AI can analyze environments, predict outcomes, and initiate real-time actions. This form of AI aims to enhance efficiency and effectiveness by providing intelligent, goal-directed solutions across various domains, such as healthcare, finance, and transportation.
Historically, public cloud services from AWS, Microsoft Azure, Google Cloud, and others have dominated the cloud landscape. However, the unique demands of agentic AI are now leading enterprises to reconsider and ultimately move away from public cloud solutions for several reasons:
