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In the ever-evolving world of artificial intelligence, a new frontier is emerging—Agentic AI. This revolutionary concept goes beyond the traditional models of AI that we’ve grown accustomed to. Instead of simply following explicit instructions, agentic AI systems are designed to act autonomously, make decisions, and adapt dynamically. In other words, they can “think” independently to achieve specific goals.

What’s the cost of a slow network if you are working in financial circles? A one-second delay in trade execution can mean millions in lost revenue. A lag in payment processing? That’s frustrated customers raising thousands of support tickets that your team would struggle to handle and potential compliance fines. For CIOs, CTOs, and IT leaders in financial services, keeping networks up and running is a business imperative.

APIs are the heart of most modern applications. Due to their simplicity and lightweight design, RESTful APIs are a popular choice for client-server communication in most applications. However, APIs can become limiting when fetching complex or related data. The front end may over-fetch or under-fetch the meaningful data. For example, different pages require different responses. RESTFul APIs require different field endpoints, each involving repetitive complex joining conditions.

At Google Cloud Next, one statement particularly caught the attention of innovators and cybersecurity professionals alike: Google’s introduction of Agent 2 Agent (A2A) marks a major evolution in AI architecture. It enables autonomous agents to collaborate across services, platforms, and domains—unlocking powerful use cases across virtually every industry.