Google Gemini’s new business agent: what it does and how to pilot it
Google’s Gemini business agent can plan, run and audit tasks across Google Workspace, Slack, Jira and more. Here’s a practical guide to piloting it for workflow automation.
At a recent Google Cloud event, Google announced a Gemini AI agent that can not only answer questions but also get things done on a company’s behalf. The agent can be given objectives, plan work, call custom skills and connect to internal systems such as Google Workspace, Microsoft 365, Slack, Jira, Confluence, Git, BigQuery, Databricks, Postgres and Snowflake.
The announcement highlighted that the agent will initially be offered to businesses before any consumer rollout, allowing Google to focus on security, scale and performance challenges that come with powerful autonomous agents.
Key capabilities that matter for sales and ops
- Accepts objectives rather than simple commands, allowing it to break a goal into sub‑tasks.
- Can attach files or folders to a request, so a sales deck can be pulled from Drive and emailed automatically.
- Integrates with major productivity suites (Google Workspace, Microsoft 365) and collaboration tools (Slack, Jira, Confluence).
- Creates its own Workspace account with an email address, calendar access and audit trail, so actions are traceable.
- Offers a model picker that defaults to the best Gemini model but lets you choose third‑party models like Anthropic’s Claude.
Typical use cases
- Automate lead‑to‑op conversion: when a new lead enters the CRM, the agent drafts a personalized outreach email, schedules a follow‑up meeting and logs the activity.
- Generate routine sales reports: request a weekly pipeline snapshot and the agent pulls data from BigQuery or Snowflake, formats a deck and shares it on Slack.
- Process purchase orders: the agent extracts order details from an attached spreadsheet, creates a PO in the ERP system and notifies the finance team.
- Coordinate cross‑functional tasks: for a product launch, the agent assigns tasks in Jira, books stakeholder meetings in calendars and tracks progress in a shared inbox.
Security and compliance considerations
Google said the early focus on enterprise customers is meant to solve “harder problems around security, scale, and performance.” The agent operates with its own Workspace account, inheriting the same permission model as a human user. It can connect to any Model Context Protocol (MCP) server inside or outside the network, meaning you can keep data behind firewalls while still granting the agent controlled access.
Auditability is built in: every action the agent takes is recorded in a “tasks inbox” with an audit trail attributed to the agent rather than an individual. This visibility helps compliance teams verify who initiated each step and when.
Cost‑control features
Google announced flexible spending options, including multi‑model orchestration, smart routing and real‑time spend caps. These mechanisms let organisations set upper limits on AI spend and switch between models to optimise cost without sacrificing performance.
Because the agent can default to the best Gemini model or a third‑party model such as Anthropic’s Claude, you can experiment with cheaper models for low‑risk tasks while reserving the most capable model for complex workflows.
Steps to start a pilot
- Identify a single, repeatable workflow that currently consumes at least a few hours per week (for example, weekly sales reporting).
- Map the data sources and tools involved—Google Sheets, Salesforce, Slack, etc.—and confirm API access.
- Work with your IT or cloud team to grant the Gemini agent access via the Model Context Protocol or standard APIs.
- Define the objective in clear language (e.g., “Create a sales performance deck for the last week and post it to #sales‑reports”).
- Monitor the agent’s task inbox for audit logs, adjust prompts as needed and track spend against your real‑time caps.
What to do now
If you’re ready to experiment, reach out to our AI Solutions team. We can help you configure Gemini’s agentic features, integrate it with your existing CRM or ERP, and build a bespoke workflow that aligns with your sales and operations goals.
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Frequently asked questions.
Google announced the agent as part of Gemini Enterprise, which is already used by many Fortune 100 firms. The announcement did not specify pricing or a separate licence, so you should contact Google Cloud sales to confirm eligibility for your organisation.
The source says the agent can connect to any Model Context Protocol server inside or outside the company’s network. That includes on‑premise systems as long as you expose them via a compatible MCP endpoint.
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