August 6, 2025
5 min read
Esther Shittu
Google launches new AI agents for data engineering, science, and migration to enhance workflows and productivity in enterprises.
Google Unveils Advanced Agentic AI Tools to Boost Data Science and Engineering Productivity
Google Cloud Next Tokyo 2025 was the venue for Google to announce a suite of new agentic AI capabilities designed to streamline complex workflows and enhance productivity for data engineers and data scientists by leveraging generative AI.New Agentic AI Offerings
The newly previewed AI agents include:- Data Engineering Agent in BigQuery: This agent allows data engineers to automate and simplify intricate data pipelines using natural language prompts. It supports essential workflows such as data ingestion from Google Cloud Storage, data transformation, and maintaining data quality.
- Data Science Agent in BigQuery Notebooks: Powered by Google's Gemini large language model, this agent is designed to assist data scientists with exploratory data analysis, data cleaning, machine learning predictions, and feature engineering. It can autonomously plan, execute code, interpret results, and facilitate interactive collaboration.
- Conversational Analytics Agent and Code Interpreter: Tailored for business users and analysts, this tool translates complex natural language queries into executable Python code.
- Migration Agent for Spanner: This AI-powered service simplifies the process of migrating databases from systems like MySQL to Google Spanner.
- Gemini CLI GitHub Actions: A complimentary AI coding agent intended to support developers. Google also introduced the Conversational Analytics API and Gemini Data Agents APIs to facilitate the orchestration of these agents and their integration into existing enterprise systems. Furthermore, the Agent Development Kit and Data Agents API empower enterprises to create custom AI agents specific to their unique requirements.
- Veo 3 and Veo 3 Fast: These video generation models are now generally available on the Vertex AI GenAI platform, offering text-to-video capabilities and upcoming image-to-video functionalities.
- Gemini 2.5 Deep Think: This advanced model has recently become more widely accessible to Google AI Ultra subscribers.
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- Understanding AI Agents: Capabilities, Risks, and Growing Role
Industry Context and Expert Insights
The enthusiasm surrounding agentic AI continues to build, with many industry experts anticipating widespread enterprise adoption in the near future. Gartner analyst Chirag Dekate noted that enterprises are actively focused on reimagining and restructuring their operations within an AI-native framework, with agentic AI playing a pivotal role in enhancing the productivity of data teams. Bradley Shimmin, an analyst at Futurum Group, emphasized how these agentic AI tools enable data scientists and engineers to dedicate more time to building applications and workflows, and less time to data discovery. He described the application of generative AI to augment and automate data processes as a "Godsend." Dekate also pointed out that while current tools excel at improving agility and precision for simpler workflows, future development will likely concentrate on addressing more complex enterprise ecosystem integrations. Shimmin further highlighted the crucial aspect of trust in AI models, commending their increasing ability to comprehend semistructured data and execute tasks with enhanced context and accuracy.Strategic Partnerships and Recent Advances
Google has expanded its collaboration with Wells Fargo to implement AI agents across various departments, including corporate and investment banking, as well as customer service, utilizing Google Agentspace. Recent advancements within the Gemini platform include:Esther Shittu is an Informa TechTarget news writer and podcast host covering AI software and systems.
Source: Originally published at TechTarget on August 5, 2025.