Google Whitepaper ‘Agents’: All You Need To Know About AI Agents In Businesses

As artificial intelligence (AI) continues to rule the digital era, Google launched a white paper, titled “Agents“. The white paper was published without any ‘big announcements,’ in September last year.

AI agents in business 

The whitepaper ‘Agent’, focuses on a future where AI can play a more independent and important role in business. The white paper is a 42-page document and is now gaining attention on  LinkedIn and X.com (formerly Twitter). One of the most promising advancements in AI agent will be the use of retrieval-augmented generation (RAG). This technique allows agents to know about external data sources, when their training data falls short. This includes structured documents and vector databases.

AI agents can also access real-time information, interacting with external systems through tools. This is the plus point which makes them more appropriate for real-world applications. For example, an agent can help you with planning a business trip. It will use an API extension to check flight schedules in real-time.

Additionally, Vertex AI, a AI agent making tool, offers features such as debugging, testing and performance evaluation. This makes it easier to deploy production-grade agents. Also other AI agent driven frameworks such as chain-of-thought (CoT), reasoning and acting (ReAct) and tree-of-thoughts (ToT) can provide structured methods for simplifying complex tasks.

AI ‘Agents’: Boon or bane

To conclude, Google’s white paper on AI agents is an ambitious and detailed vision of where AI will be at the forefront. The tech giant has also highlighted that AI agents can be very fruitful for enterprises. So, the message is clear! In the coming future AI agents will not just be a theoretical concept. They are made to be a practical tool capable of reshaping how businesses operate.

However, as of now AI agents can represent both an opportunity and a challenge. Using AI agents needs careful planning and then experimentation. Also, there should be room to rethink traditional workflows. “No two agents are created alike due to the generative nature of the foundational models that underpin their architecture,” the paper highlights.