Agentic AI is the next phase of artificial intelligence innovation. It refers specifically to systems that can act autonomously and make decisions or take actions independently to achieve specific goals. But what does Agentic AI mean in comparison to the generative models already deployed? In this blog, we break down the concept, explore the key benefits and practical examples, and look at how organisations can prepare their digital infrastructure ahead of its implementation.
What is Agentic AI?
Unlike traditional AI, which often relies on human input for each decision, Agentic AI is fully autonomous. It can understand its environment, plan a course of action, and execute a number of tasks with minimal intervention. It acts as an agent, allowing it to handle the management of workflows, control automated equipment, or even navigate virtual environments to achieve goals.
What is an Example of Agentic AI?
The autonomous characteristics of Agentic AI can be applied to supply chain management. In this use case, Agentic AI systems monitor inventory levels, supplier performance, demand forecasts, and logistics in real time., Agentic AI takes proactive actions to prevent any disruptions to systems and workflows. For example, it might automatically reroute shipments to avoid bottlenecks and improve resilience.
But to provide value, the infrastructure which sits behind Agentic AI systems needs to access real-time data and operations, including edge and cloud computing for quick processing, and secure encryption and access controls to protect sensitive data.
Generative AI vs. Agentic AI: What’s the Difference?
Generative AI focuses on creating new content, including text, images, music, or code, based on patterns learned from large datasets. It can generate outputs when prompted, but it relies on data input.
On the other hand, Agentic AI is built to function as an autonomous decision-maker. It acts with a degree of independence, continuously perceiving its surrounding environment, setting relevant goals, and executing plans. Early adoption of Agentic AI has been used in customer service. A generative AI chatbot answers questions by generating natural language responses based on the input. The characteristics of an Agentic AI system can understand a customer’s issue, but also take proactive steps to resolve it.
Benefits of Agentic AI for Enterprises
Agentic AI provides numerous benefits to adopters:
Autonomous decision-making & efficiency: Operates independently to automate commonly repetitive tasks, freeing human resources to be deployed for more strategic activities.
Improved agility & adaptability: Responds quickly to real-time data and adjusts actions based on changing conditions, improving business agility.
Scalability & consistency: Handles increased workloads without additional human resources and can delivers reliable, repeatable outcomes.
Enhanced problem-solving & risk management: Identifies solutions that might be missed by humans, and proactively detects and addresses potential issues.
24/7 availability & better customer experience: Continuous operations with local data processing, personalising interactions, and predicting customer needs for tailored solutions.
The Infrastructure Behind Agentic AI: Why It Matters
Infrastructure that supports its technical and operational needs is key to enabling Agentic AI. This infrastructure should include:
- Scalable, carrier-neutral colocation facilities, which provide flexibility for connecting to multiple networks and cloud platforms;
- Low-latency, high-bandwidth connectivity to ensure real-time data processing;
- Secure environments to protect sensitive data;
- Sustainable, energy-efficient data centres using renewable energy and advanced technologies such as liquid cooling to help meet growing computational demands responsibly.
How Telehouse Supports the Future of AI
Telehouse is a foundational provider of AI workloads, offering a robust infrastructure that supports machine learning, edge computing, and AI pipelines. Telehouse London Docklands facilitates fast connections with ISPs and cloud service providers, including crucial low-latency edge network connectivity, to meet the demand posed by Agentic AI. Telehouse is also supporting AI and machine learning innovations in autonomous vehicles, smart manufacturing, and smart cities.
Recently, the Magny 2 data centre was launched in France, which incorporates high-density AI-ready infrastructure, combining innovative cooling, optimal energy efficiency, and AI sovereignty.
Agentic AI FAQs
What is the difference between Generative AI and Agentic AI?
Generative AI creates content based on patterns from large datasets, such as text or images, but requires human input to function. In contrast, Agentic AI is fully autonomous, capable of making decisions, and taking actions without human intervention to achieve specific goals.
What are the benefits of Agentic AI for businesses?
Agentic AI can improve efficiency, reduce operational costs, enhance decision-making, and increase scalability by automating tasks.
What infrastructure is needed to support Agentic AI?
Agentic AI requires fast, secure, and scalable infrastructure, including low-latency networks, real-time data processing, and secure environments.
How does Telehouse support Agentic AI?
Telehouse offers robust, scalable infrastructure with low-latency connectivity and secure environments, enabling AI solutions to function efficiently and responsibly.
Want to find out more about Agentic AI and Telehouse’s role in AI innovation? Speak to an expert here.