Google Executives Say Increased Access To AI Agents, Capabilities Are Differentiators For Channel Partners

Google is enhancing its Google Cloud Platform by expanding access to specialized artificial intelligence agents and introducing new AI capabilities within BigQuery. These advancements are designed to bolster Google Cloud's position as a leading destination for AI workloads, particularly for solution providers utilizing Google Cloud technology. Yasmeen Ahmad, managing director of data and analytics at Google, highlighted the growing demand for Gemini data agents from services partners, emphasizing Google's commitment to making Google Cloud an AI-first cloud environment. Ryan Salva, senior director of product management at Google, explained that these new AI tools are empowering thousands of partners within Google's ecosystem to accelerate software development cycles and improve the quality of their offerings. By developing proficiency with these tools, partners can more effectively achieve their business objectives and enhance profitability. Google's AI agents are facilitating the creation of additional intellectual property, augmenting custom prompts, and enabling specialized integrations, which allows solution providers to differentiate themselves in the competitive market. Several new specialized agents are currently in preview, including the Gemini CLI GitHub Actions agent. This agent can streamline issue triaging, expedite pull request reviews, and assist in writing tests and implementing code on demand. Building on the June release of Gemini CLI, an open-source AI agent for developer terminals, this GitHub Actions agent expands its utility to automation events. Google also plans to further open Gemini CLI, allowing developers to instantiate it as a container in various environments. Other agents available in preview include:

• Data engineering agent in BigQuery: Designed to accelerate data preparation, thereby speeding up pipeline development.
• Data science agent in BigQuery Notebooks: Aims to reduce the infrastructure management burden for users.
• Conversational analytics agent and code interpreter: These tools allow business users and analysts to query data insights using natural language.
• Migration agent for Spanner: Intended to simplify database migration processes.
• New API: Enables developers to integrate conversational AI experiences directly into their applications.
BigQuery's AI query engine is also previewing generative AI capabilities that integrate directly into SQL, offering a more intuitive way for data practitioners to interact with data. This includes hybrid search, which combines Google's semantic search with traditional keyword search, and adaptive filtering in AlloyDB to enhance vector query speed and recall. Furthermore, BigQuery now supports autonomous embeddings generation and indexing for improved large-scale analytics.

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Originally published at CRN on August 6, 2025.

FAQ

Google Cloud AI Agent Capabilities

Q: What are the primary benefits of Google's new AI agents for solution providers? A: These AI agents empower solution providers to deliver software faster and with higher quality, facilitate the development of additional intellectual property, augment custom prompts, and enable specialized integrations, ultimately helping them differentiate themselves in the market and increase profitability. Q: What specific functions can the Gemini CLI GitHub Actions agent perform? A: The Gemini CLI GitHub Actions agent can triage issues, accelerate pull request reviews, and collaborate on demand to write tests and implement code. Q: Which BigQuery agents are currently in preview, and what do they offer? A: The preview agents in BigQuery include a data engineering agent for faster data preparation, a data science agent in BigQuery Notebooks to reduce infrastructure management, a conversational analytics agent and code interpreter for natural language data querying, and a migration agent for Spanner to simplify database migrations. Q: How does BigQuery's AI query engine enhance data interaction? A: BigQuery's AI query engine integrates generative AI capabilities directly into SQL, allowing data practitioners to interact with data more intuitively. It also features hybrid search, combining semantic and keyword search, and supports autonomous embeddings generation and indexing for advanced analytics. Q: What is Google's vision for Gemini CLI? A: Google aims to further open Gemini CLI, enabling developers to instantiate it as a container anywhere for broader accessibility and application.

Crypto Market AI's Take

Google's strategic push into more accessible and specialized AI agents, particularly within its BigQuery ecosystem, aligns perfectly with the evolving landscape of data-driven solutions. For businesses leveraging cloud infrastructure, these advancements signal a significant leap in operational efficiency and innovation potential. In the realm of cryptocurrency, where data analysis and predictive modeling are paramount, the integration of such powerful AI tools can unlock new opportunities for market participants. Imagine utilizing these sophisticated agents to analyze on-chain data, predict market trends, or even automate complex trading strategies. This move by Google underscores the growing convergence of AI and financial technology, a trend we actively explore and support on our platform. We believe that by democratizing access to advanced AI capabilities, companies like Google are paving the way for a more intelligent and efficient future for all industries, including the dynamic world of crypto.

More to Read:

• AI Agents: The Future of Business Automation and Customer Engagement
• How to Use Google Gemini for Smarter Crypto Trading
• The Rise of AI-Powered Crypto Scams