Agentic AI Explained: The Next Level of AI Automation

Agentic AI is emerging as the next level of artificial intelligence, moving beyond simply generating information. This technology allows autonomous agents to execute complex tasks and deliver outcomes for users. Instead of just drafting an email, agentic AI could plan an entire overseas business trip, including flight details and itineraries. These agents can also help with recruitment or streamline customer service. Organizations in the UK are looking to move from experimenting with AI to gaining tangible value, and agentic AI offers a way to automate workflows and enhance human decision-making. AI agents are complex, often using a planning large language model with smaller, specialized models. They can also involve a single model orchestrating tasks by calling tools, APIs, or querying databases. A key aspect is reliably connecting to enterprise data sources, using architectures like Retrieval-Augmented Generation. This helps ground agent responses in accurate, real-time data. However, agentic AI can significantly increase computational costs due to higher token counts. Even so, open-source inference engines like vLLM and projects like llm-d are making it possible for organizations to bring LLM infrastructure in-house. This development has implications for how businesses will leverage AI for complex operations.