Amazon Q vs Google Agentspace: What’s the Best Enterprise Agent Tool?

Updated in May 2025

Enterprise AI assistants are no longer science‑fiction sidekicks. In 2025, they sit at the centre of board‑room conversations about productivity, cost control, and data‑driven decision‑making.

Two names dominate the space: Amazon Q Business and Google Agentspace. Both promise to help employees find answers, generate content, and even execute tasks—because they plug directly into a company’s own knowledge bases (wikis, file shares, SaaS data, ticketing systems). By indexing that private content and respecting existing permissions, each assistant can return answers that are specific to your organisation rather than generic web snippets.

Amazon Q is rooted in the AWS Cloud and prides itself on tight operational integrations, while Google Agentspace is born from Google Search and the Gemini model, promising unmatched discovery and multilingual reach. Choosing between them means understanding how those origins—and their connector catalogs—translate into day‑to‑day business value.

TLDR (Fast Compare)

Decision factor	Amazon Q Business	Google Agentspace
Overall verdict	Best if you’re all‑in on AWS, want built‑in DevOps/contact‑centre hooks, and need the lowest seat price.	Strongest semantic & multilingual search; no‑code Agent Designer automates work across many SaaS apps.
Pricing (2025)	Q Pro ≈ $20 user/mo (Lite starts at $3).	Agentspace Enterprise ≈ $25 user/mo (NotebookLM ≈ $9).
Search experience	Quick, permission‑aware, narrower scope.	Google‑grade semantic ranking & auto‑translation.
Automation	Q Apps automate single‑system tasks (AWS, QuickSight, Connect).	Visual Agent Designer chains multi‑step, cross‑app workflows.
Security	Inherits AWS IAM.	Uses Google IAM + VPC Service Controls.
Connector depth	50 + out‑of‑the‑box connectors → e.g. Confluence, SharePoint, Salesforce, ServiceNow, Jira, Slack/Teams, Gmail/Outlook, GitHub, Zendesk, Box, Snowflake, S3.	~60 pre‑built connectors → Gmail, Drive, Docs, Sheets, Calendar, Chat plus Confluence, Jira, Salesforce, ServiceNow, Slack, Workday, SAP, Snowflake, Databricks, SharePoint, Box, BigQuery, etc.

McKinsey finds that launching AI pilots is easy; scaling them so they actually shift revenue or cost curves is “harder than expected,” requiring companies to re‑wire processes and data governance before value shows up on the P&L. Agent platforms aim to make that rewiring less painful by sitting on top of existing systems and acting as a universal interface—ask, get answer, take action—all in the employee’s natural language.

What is Amazon Q Business?

Positions itself as “the most capable generative‑AI assistant for finding information, gaining insight, and taking action at work.” Users connect corporate data sources via 50 + native connectors—including Confluence, SharePoint, Google Drive, OneDrive, Gmail/Outlook, Slack, Teams, Salesforce, ServiceNow, Jira, GitHub, Zendesk, Box, Snowflake, Redshift, and any S3 bucket. Once indexed, employees can ask questions or request tasks and receive permission‑aware answers that cite those sources. A standout is Q Apps, a no‑code way to turn a chat into a lightweight workflow or dashboard. Because Q runs on AWS Bedrock, it can route requests to the best underlying model and respect IAM permissions automatically.

What is Google Agentspace?

Bills itself as the launch point for an “agent‑driven enterprise,” blending Google‑quality search with Gemini’s reasoning and a visual Agent Designer that lets business users build multi‑step “expert agents.” To ground its answers, Agentspace builds a private enterprise knowledge graph from Workspace content (Gmail, Drive, Docs, Sheets, Slides, Calendar, Chat) plus ~60 third‑party connectors: Confluence, Jira, Salesforce, ServiceNow, Slack, Workday, SAP, SharePoint, Box, Dropbox, Snowflake, Databricks, BigQuery, etc. Multi‑language support means employees can query or read answers in their own language without extra setup.

Feature Showdown

Search & discovery: Agentspace starts with what Google does best: search! It builds a customer‑specific enterprise knowledge graph and layers Gemini’s multimodal understanding on top, so a single query can traverse Gmail, Drive, Jira, Salesforce, ServiceNow—and even surface images or video transcripts—directly from the Chrome address bar. Because every result is semantically ranked and automatically translated where needed, global teams get one, relevant answer instead of a list of links. Amazon Q’s retrieval is fast and permission‑aware, but it remains a traditional connector‑based crawl; without Agentspace’s graph or cross‑language reasoning, employees often perform extra follow‑up queries to reach the same depth.

Generative intelligence: Agentspace ships with domain‑specialised expert agents—“Deep Research” can absorb hundreds of documents and output a structured brief, while “Idea Generation” runs autonomous brainstorming loops that grade and refine concepts before presenting the best ones. NotebookLM Enterprise adds another layer for long‑form synthesis. Amazon Q can summarise content, draft emails and even build simple dashboards, but its outputs are typically single‑pass responses; there is no built‑in concept of multi‑agent reasoning or adversarial idea testing.

Workflow automation:The new no‑code Agent Designer lets non‑technical staff chain actions across SaaS tools—update a CRM record, ping Slack, file a ServiceNow ticket—all from one visual canvas, then publish the workflow to an Agent Gallery for anyone to reuse. Amazon Q Apps are handy for turning a conversation into a lightweight utility, but they rarely exceed a single system unless a developer stitches in custom plugins. In practice, Agentspace automates end‑to‑end business processes; Q automates discrete tasks.

Bottom Line

For organisations that need high‑grade semantic search, multilingual reach and a true no‑code canvas for cross‑app automations, Google Agentspace is the more capable feature set. Amazon Q remains a smart choice for AWS‑centric shops focused on DevOps and contact‑centre use cases, but on pure functionality, Agentspace takes the crown.