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Google intros array of technical AI agents across its apps
agentic-ai

Google intros array of technical AI agents across its apps

Google unveils new agentic AI tools for data engineers and scientists to boost productivity and simplify complex workflows.

August 6, 2025
5 min read
Esther Shittu

Google unveils new agentic AI tools for data engineers and scientists to boost productivity and simplify complex workflows.

Google has unveiled a new generation of agentic AI capabilities specifically designed for data engineers and data scientists, aiming to streamline complex data workflows and boost productivity through generative AI. Announced at the Google Cloud Next Tokyo 2025 conference, these tools represent a significant stride in applying advanced AI to enterprise data challenges. The suite of new offerings includes:
  • Data Engineering Agent in BigQuery: This agent empowers data engineers to automate and simplify intricate data pipelines using natural language prompts. It facilitates essential tasks such as data ingestion from Google Cloud Storage, data transformation processes, and the maintenance of data quality.
  • Data Science Agent in BigQuery Notebooks: Leveraging Google's powerful Gemini large language model, this agent supports data scientists in exploratory data analysis, data cleaning, machine learning predictions, and feature engineering. It can autonomously plan, execute code, interpret results, and engage in interactive collaboration.
  • Conversational Analytics Agent and Code Interpreter: These tools enable business users and analysts to interact with data more intuitively by translating natural language queries into executable Python code.
  • Migration Agent for Spanner: An AI-driven service designed to simplify the process of migrating databases, for instance, from MySQL to Google Spanner.
  • Conversational Analytics API and Gemini CLI GitHub Actions: The API allows for the integration of Looker's natural language processing and code interpreter features into custom applications, while the Gemini CLI GitHub Actions provide free AI coding assistance.
    • Furthermore, Google offers an Agent Development Kit and Data Agents API, providing the flexibility for data scientists and engineers to create custom AI agents tailored to their specific workflows. Industry analysts note that while agentic AI has historically been applied to customer service and developer tools, these new offerings mark a significant expansion into addressing complex enterprise data problems. Gartner analyst Chirag Dekate observes that this development aligns with the enterprise trend of reimagining operations in an AI-native context, thereby enhancing data team productivity. Bradley Shimmin of Futurum Group highlights the value of generative AI in automating laborious tasks like data discovery, allowing professionals to concentrate on application and workflow development. The expanded collaboration with Wells Fargo exemplifies the practical application of these tools, assisting the financial institution in building AI agents across various divisions like corporate banking, investment banking, and customer service. These advancements underscore Google's commitment to equipping data teams with AI-driven automation and intelligence, positioning agentic AI as a crucial driver for enterprise innovation.
    Originally published at TechTarget on August 5, 2025.

    FAQ

    What are the key benefits of Google's new agentic AI capabilities for data professionals?

    These tools aim to simplify complex data workflows, automate time-consuming tasks like data ingestion and transformation, enhance data analysis and machine learning processes, and ultimately increase the productivity of data engineers and data scientists.

    How does the Data Science Agent in BigQuery Notebooks utilize Google's AI technology?

    It is powered by Google's Gemini large language model, enabling it to assist with exploratory data analysis, data cleaning, machine learning predictions, feature engineering, and interactive collaboration with data scientists.

    Can business users interact with data more easily using these new tools?

    Yes, the Conversational Analytics Agent and Code Interpreter are designed to translate natural language queries into Python code, making data interaction more intuitive for business users and analysts.

    What is the significance of these AI agents for enterprise data management?

    These tools represent a shift towards using agentic AI for more complex enterprise data problems, moving beyond customer service and developer applications to directly improve data team efficiency and the ability to reimagine operations in an AI-native context.

    How can developers and engineers customize these AI capabilities?

    Google provides an Agent Development Kit and Data Agents API, which allow users to create custom AI agents tailored to their specific workflows.

    Crypto Market AI's Take

    Google's introduction of agentic AI tools for data professionals marks a significant evolution in how businesses can leverage artificial intelligence for critical data operations. This aligns with our perspective at Crypto Market AI, where we see AI not just as a tool for market prediction, but as a fundamental enabler for optimizing workflows and driving innovation across various sectors. For data-intensive industries, these advancements promise to unlock new levels of efficiency and insight, mirroring how AI is transforming financial markets. We believe that the integration of such powerful AI agents into data pipelines will accelerate discovery and decision-making, much like how our own AI crypto trading bots leverage advanced algorithms to provide a competitive edge in the volatile cryptocurrency landscape. The focus on natural language interaction and automation is key to democratizing access to complex data, a principle we also champion in making sophisticated financial tools accessible to a wider audience.

    More to Read:

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  • How to Use Google Gemini for Smarter Crypto Trading
  • The AI Gig Economy: Earning Crypto in the Age of Automation