Google Launches Advanced Agentic AI Tools for Data Scientists and Engineers

Google introduced a suite of new agentic AI capabilities aimed at data engineers and data scientists at the Google Cloud Next Tokyo 2025 conference. These tools are designed to simplify complex data workflows and enhance productivity by leveraging generative AI.

New AI Agents and Tools

The new offerings, all currently in preview, include:

• Data Engineering Agent in BigQuery: Enables data engineers to simplify and automate complex data pipelines using natural language prompts. It supports workflows from data ingestion (e.g., Google Cloud Storage) to data transformation and quality maintenance.
• Data Science Agent in BigQuery Notebooks: Powered by Google's Gemini large language model, this agent assists with exploratory data analysis, data cleaning, machine learning predictions, and feature engineering. It can plan, execute code, reason about results, and collaborate interactively with data scientists.
• Conversational Analytics Agent and Code Interpreter: Designed for business users and analysts, this tool translates complex natural language queries into Python code to facilitate data analysis.
• Spanner Migration Agent: An AI-powered service that helps data engineers simplify migrations from database systems like MySQL to Google Spanner.
• Gemini CLI GitHub Actions: A free AI coding agent to assist developers with coding tasks.
• Gemini Data Agents APIs: These APIs orchestrate different agents and enable integration with systems. The first API, the Conversational Analytics API, integrates Looker's natural language processing and code interpreter capabilities into applications.
• Agent Development Kit and Data Agents API: Allow data scientists and engineers to create custom AI agents tailored to their workflows.

Industry Context and Expert Insights

Google’s focus on agentic AI reflects a growing industry trend toward autonomous AI agents that can handle complex enterprise data workflows. While agentic AI has traditionally centered on customer service and developer tools, the new data-focused agents aim to tackle more intricate problems in enterprise data engineering and science. Chirag Dekate, an analyst at Gartner, noted that enterprises are on a long-term journey to reimagine and reconstruct their operations in an AI-native context. These new tools represent an important step toward improving productivity for data teams. Bradley Shimmin, an analyst at Futurum Group, highlighted that agentic AI tools are a “Godsend” for data scientists and engineers, who previously spent much of their time searching for data rather than building applications and workflows. Shimmin also emphasized the importance of trust in these AI models, noting that while they are improving at tool use and structured output, users must remain aware of the semistructured nature of business data that these agents process.

Collaborations and Recent Advances

Google is expanding its collaboration with Wells Fargo to help the financial institution deploy AI agents across various departments, including corporate and investment banking and customer service. Additionally, Google recently announced advancements in its Gemini AI platform:
• Veo 3 and Veo 3 Fast: Video generation models now generally available on the Vertex AI GenAI platform, offering text-to-video and upcoming image-to-video capabilities.
• Gemini 2.5 Deep Think: Now more widely available to Google AI Ultra subscribers.

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Esther Shittu is a news writer and podcast host covering AI software and systems for Informa TechTarget.

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Source: Originally published at TechTarget on August 5, 2025.

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Frequently Asked Questions (FAQ)

Google's New AI Agents for Data Professionals

Q: What are Google's new agentic AI tools designed for? A: These tools are designed to simplify complex data workflows and enhance the productivity of data engineers and data scientists by leveraging generative AI. Q: What is the Data Engineering Agent in BigQuery used for? A: It allows data engineers to simplify and automate complex data pipelines using natural language prompts, covering everything from data ingestion to transformation and quality maintenance. Q: How does the Data Science Agent in BigQuery Notebooks assist data scientists? A: Powered by Google's Gemini model, it helps with exploratory data analysis, data cleaning, machine learning predictions, and feature engineering, offering interactive assistance with code execution and result reasoning. Q: Who is the Conversational Analytics Agent and Code Interpreter for? A: This tool is designed for business users and analysts, enabling them to translate natural language queries into Python code for data analysis. Q: What problem does the Spanner Migration Agent address? A: It simplifies the process of migrating data from other database systems, like MySQL, to Google Spanner using AI capabilities. Q: Are the Gemini CLI GitHub Actions free to use? A: Yes, the Gemini CLI GitHub Actions is a free AI coding agent to assist developers with their coding tasks. Q: What is the purpose of the Gemini Data Agents APIs? A: These APIs are built to orchestrate various agents and facilitate integration with other systems. The Conversational Analytics API, for instance, brings Looker's natural language processing and code interpreter features into applications. Q: Can users create their own AI agents with these new tools? A: Yes, the Agent Development Kit and Data Agents API allow data scientists and engineers to build custom AI agents tailored to their specific workflows. Q: What is the industry trend reflected by Google's release of these agentic AI tools? A: It reflects a growing industry trend towards autonomous AI agents capable of managing complex enterprise data workflows. Q: What expert insights were shared regarding these new AI tools? A: Analysts noted that these tools are a significant step towards improving data team productivity and are seen as a "Godsend" for data scientists and engineers, potentially freeing them from data searching to focus on application building. Q: What advancements were recently announced for Google's Gemini AI platform? A: Google announced the general availability of Veo 3 and Veo 3 Fast for video generation on the Vertex AI GenAI platform, and increased availability of Gemini 2.5 Deep Think.

Crypto Market AI's Take

Google's push into advanced agentic AI tools for data professionals signifies a critical evolution in how businesses will interact with and derive value from their data. This mirrors the advancements we are seeing in the cryptocurrency space, where AI is increasingly being used to analyze market trends, automate trading, and provide predictive insights. Our platform at Crypto Market AI leverages similar AI capabilities to offer sophisticated tools for traders and investors. By integrating advanced machine learning and natural language processing, we aim to democratize access to powerful market intelligence, making it more efficient and accessible for everyone. Just as Google's new agents simplify complex data pipelines, our AI-driven solutions aim to simplify the complexities of the crypto market, offering intelligent insights and automated trading strategies for enhanced performance and risk management.

More to Read:

• AI Agents: Capabilities, Risks, and Growing Role
• How to Use Google Gemini for Smarter Crypto Trading
• AI-Driven Crypto Trading Tools Reshape Market Strategies in 2025