As digital infrastructure grows more complex, traditional network management tools are struggling to keep up. This article reveals how agentic AI is being used to reshape network behavior and connectivity strategy. You will learn how enterprises are testing agentic models to automate traffic routing, security enforcement, and resource allocation. Read the article and connect with Precoh for guidance on next steps.
Agentic AI refers to a type of artificial intelligence that can learn, adapt, and act autonomously without needing constant human input. Unlike traditional AI systems, such as chatbots that require prompts to function, agentic AI can teach itself and perform tasks it hasn't been specifically trained on. This represents a shift towards more intelligent systems that can operate independently.
How does agentic AI impact networks?
Agentic AI is transforming network management by enabling networks to operate autonomously. This means they can learn from data, adapt to changes, and make decisions without manual intervention. For instance, AI-enabled networks can analyze traffic in real time, detect bottlenecks, and automatically reroute data to maintain smooth operations, leading to higher reliability and less downtime.
What role does IoT play with agentic AI?
The integration of agentic AI with IoT enhances business operations by enabling intelligent communication and collaboration among devices. This allows for real-time data insights and proactive responses, which can redefine business models and improve efficiency. For example, IoT devices can work together to optimize urban environments, such as traffic signals adjusting themselves to reduce congestion, ultimately leading to smarter and more sustainable operations.
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