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Google Cloud has just introduced a whole suite of new AI agents aimed at transforming data engineering, data science, and migration workflows. These new tools are built to automate complex tasks, with the goal of making it easier for both technical users and beginners to utilize AI and data.
AI for everyone: from engineers to business analysts
Google Cloud’s new AI agents are aimed at productivity. For data engineers, the new Data Engineering Agent for BigQuery makes it much easier to automate complex data pipelines with simple natural language prompts. This means no more manual coding to load, clean, and join data tables. Just tell it what you need, and the agent takes care of the rest.
For data scientists, the new Data Science Agent for BigQuery and Vertex AI (by Gemini) handles the heavy lifting of tasks like exploratory data analysis, data cleaning, and machine learning predictions. It runs the code, analyzes the results, and presents the findings, with users getting to provide real-time feedback and collaborate.
For non-technical users, Google Cloud is elevating its conversational analytics agent with the new Code Interpreter. This tool utilizes Gemini’s advanced reasoning to convert natural language questions into Python code, making it extremely easy for anyone to delve into complex data analysis. Whether it’s customer segmentation or a more detailed analysis, the Code Interpreter generates the code, explains it clearly, and provides interactive visualizations, all within Google’s secure Data Cloud.
The new era of agentic AI
As Google Cloud Managing Director Yasmeen Ahmad puts it, “The agentic era begins with a new workforce of specialized AI agents, providing an AI-native interface to turn intent into action.” These agents aren’t just designed to help users; they’re creating a collaborative, interconnected ecosystem that aids businesses in streamlining their data workflows. Through the launch of the Gemini Data Agents APIs, Google is helping developers to integrate these AI agents into their own intelligent systems, which will really open up the possibilities for customization and automation.
Google’s push for an interconnected network of agents also includes the launch of a new migration agent for Spanner, designed to simplify the migration of legacy databases, such as MySQL, to Spanner. This agent automates tedious tasks, making it easier to transition to a more scalable, modern cloud architecture.
Boosting the future of data with AI
Google Cloud’s AI-native foundation brings together both transactional and analytical data, allowing agents to access real-time insights. With the new Spanner columnar engine and BigQuery’s AI Query Engine, AI-powered reasoning is baked right into Google’s databases, making it easier to quickly answer questions like, ‘Which customer reviews are the most frustrated?’
As Google rolls out these AI agents, they’re changing the way businesses interact with data.
“The world is not just changing; it’s being re-engineered in real-time by data and AI,” says Ahmad. “The way we interact with data is undergoing a fundamental transformation, moving beyond human-led analysis to a collaborative partnership with intelligent agents. This is the agentic shift, a new era where specialized AI agents work autonomously and cooperatively to unlock insights at a scale and speed that was previously unimaginable.
“…we’re not just participants in this shift — we are building the core intelligence, interconnected ecosystems, and AI-native data platforms that power it.”
Trend Micro and Google Cloud recently strengthened their long-standing alliance with an expanded partnership that combines Trend Micro’s cybersecurity expertise with Google Cloud’s infrastructure and AI leadership. Read more here.
