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Read Aviatrix CTO Anirban Sengupta’s latest article on the network security challenges emerging with Agentic AI. Agentic artificial intelligence (AI) represents the next frontier of AI, promising to go beyond even the capabilities of generative AI (GenAI). Unlike most GenAI systems, which rely on human prompts or oversight, agentic AI is proactive because it doesn’t require user input to solve complex, multi-step problems. By leveraging a digital ecosystem of large language models (LLM), machine learning (ML) and natural language processing (NLP), agentic AI performs tasks autonomously on behalf of a human or system, massively improving productivity and operations.
While agentic AI is still in its early stages, experts have highlighted some ground-breaking use cases. Consider a customer service environment for a bank where an AI agent does more than purely answer a user’s questions when asked. Instead, the agent will actually complete transactions or tasks like moving funds when prompted by the user. Another example could be in a financial setting where agentic AI systems assist human analysts by autonomously and quickly analyzing large amounts of data to generate audit-ready reports for data-informed decision-making.
The incredible possibilities of agentic AI are undeniable. However, like any new technology, there are often security, governance, and compliance concerns. The unique nature of these AI agents presents several security and governance challenges for organizations. Enterprises must address these challenges to not only reap the rewards of agentic AI but also ensure network security and efficiency.