CRM & Automation10 min read

HubSpot Breeze AI Agent Workflows: 2026 Guide

HubSpot shipped 11 platform updates on January 27, 2026, headlined by the GPT-5 migration for Breeze Studio agents, customer message insights with audit cards, and the new Run Agent workflow action. This guide covers what changed, what it means for your CRM automation strategy, and how to configure agent-powered workflows across marketing, sales, and service hubs.

Digital Applied Team
February 2, 2026
10 min read
11

Updates Released Jan 27

GPT-5

Default LLM Upgrade

9+

Supported Channels

100

Credits per Conversation

Key Takeaways

GPT-5 now powers Breeze Studio agents: As of January 12, 2026, Breeze Studio agents default to GPT-5 instead of GPT-4.1. Marketplace agents including Deal Loss, Customer Health, Customer Handoff, and Social Post were automatically upgraded. Customer, Prospecting, and Data Agents are excluded from this change.
Audit cards bring transparency to AI actions: When the Customer Agent identifies customers, qualifies leads, or modifies CRM properties, a new audit card displays exactly which actions the agent performed, building verifiable trust in automated workflows.
Run Agent workflow action enters private beta: Teams can now trigger AI agents directly within HubSpot workflows, configuring which agent runs, what context it receives, and how outputs feed back into the CRM ecosystem for follow-up actions.
Omnichannel deployment across nine channels: Breeze Customer Agent now supports ecosystem-built channel integrations including SMS, Instagram, Telegram, LINE, WhatsApp, and Slack through the Custom Channels API, alongside existing chat, email, and Messenger channels.
Credit-based pricing replaces feature bundling: HubSpot's usage-based model charges 100 credits per Customer Agent conversation, 100 credits per monitored Prospecting contact monthly, 10 credits per Data Agent prompt, and 10 credits per Breeze workflow action.

January 2026 Breeze AI Updates

HubSpot's January 27, 2026 release delivered a focused set of upgrades across customer agent capabilities, Help Desk functionality, workflow automation, and CRM visualization tools. The updates collectively address three priorities: trust through audit trails, flexibility through workflow integration, and extensibility through developer tools.

The headline changes center on Breeze AI agents. The GPT-5 model migration for Breeze Studio agents landed on January 12, followed by the customer message insights, Run Agent workflow action, and expanded omnichannel support in the January 27 batch. Together, these updates move Breeze from an isolated AI feature set toward a comprehensive agent infrastructure that integrates with the full HubSpot automation stack.

Full January 27 Update Summary

Customer Agent Insights
Live
Audit cards show which CRM properties were modified, lead qualification status, and data points collected during agent conversations.
Run Agent Workflow Action
Private Beta
Trigger AI agents inside HubSpot workflows with configurable context, agent selection, and output routing back into CRM records.
Help Desk Blocking
Live
Block and unblock senders to prevent spam tickets from overwhelming support queues. Available across all Service Hub tiers.
Map Visualization for CRM
Private Beta (Enterprise)
Visualize contacts and companies geographically within the CRM. Available to Enterprise users in private beta.
Business Days Workflow Delays
Beta
Workflow delay actions can now exclude weekends from delay calculations, ensuring time-based triggers fire on business days only.
Team @Mentions
In Development
Tag entire teams in notes and engagements instead of individual users. Currently in development with rollout expected in Q1 2026.

GPT-5 Migration for Breeze Studio Agents

According to HubSpot's developer changelog, Breeze Studio agents now default to GPT-5 instead of GPT-4.1. This migration affects marketplace agents and custom agents in private beta. Existing agents created before December 1, 2025 were automatically upgraded as of January 12, 2026.

The upgrade is selective. Customer, Prospecting, and Data Agents are excluded from the GPT-5 migration and continue operating on their current models. This distinction matters for teams planning automation around specific agent capabilities, as the model backbone directly affects response quality, reasoning depth, and action planning.

Which Agents Got GPT-5

AgentModelStatusType
Deal Loss AgentGPT-5Auto-upgradedMarketplace
Customer Health AgentGPT-5Auto-upgradedMarketplace
Customer Handoff AgentGPT-5Auto-upgradedMarketplace
Social Post AgentGPT-5Auto-upgradedMarketplace
Custom Agents (Beta)GPT-5Auto-upgradedPrivate Beta
Customer AgentUnchangedNot affectedCore
Prospecting AgentUnchangedNot affectedCore
Data AgentUnchangedNot affectedCore

The GPT-5 backbone brings improved reasoning, better context retention across longer conversations, and more reliable action planning for multi-step agent tasks. For AI transformation initiatives, the model upgrade means agent-driven workflows can handle more complex decision trees without degrading output quality.

Customer Message Insights and Audit Cards

The audit card feature, now live for all accounts with the Breeze Customer Agent, delivers transparency into what the agent does during conversations. When the Customer Agent identifies a customer, qualifies a lead, or modifies CRM properties, an audit card appears showing the specific actions performed.

This is a direct response to the primary objection teams raise when deploying AI agents: uncertainty about what the agent actually does behind the scenes. Audit cards convert that uncertainty into verifiable records, which is critical for compliance-sensitive industries and teams scaling agent deployment beyond pilot programs.

What Audit Cards Display

CRM Property Changes
Displays which contact or company properties were modified, the previous value, and the new value set by the agent during the conversation.
Lead Qualification Status
Shows the qualification outcome (qualified, partially qualified, or unqualified) along with the specific data points the agent used to reach that determination.
Customer Identification
Records how the agent identified the customer, whether through email matching, account lookup, or information provided during the conversation.

Practical Impact on Support Operations

Before audit cards, support managers had to manually review conversation transcripts and cross-reference CRM records to verify agent behavior. Now, every agent action generates a timestamped card visible in the conversation timeline. This cuts audit time significantly and gives supervisors the ability to spot-check agent performance at scale.

  • Quality assurance: Review agent actions without reading full transcripts. Filter audit cards by action type (property changes, qualifications, handoffs) to focus QA efforts on high-impact interactions.
  • Training feedback: Identify patterns where the agent makes incorrect qualification decisions or sets wrong property values. Use these patterns to refine agent instructions in Breeze Studio.
  • Compliance documentation: Audit cards serve as records of AI-driven CRM changes. For regulated industries, this paper trail demonstrates that automated actions were logged and reviewable.
  • Escalation context: When the agent hands off to a human rep, the audit card summarizes everything the agent already did, preventing the customer from repeating information.
Implementation Tip

Set up a weekly audit review cadence during the first 30 days after enabling the Customer Agent. Focus on conversations where the agent qualified leads differently than your team would have. Adjust the agent's qualification criteria in Breeze Studio based on these discrepancies. Most teams find the agent stabilizes to acceptable accuracy within 2-3 rounds of instruction refinement.

Run Agent Workflow Action

The Run Agent workflow action, currently in private beta, addresses a limitation that constrained Breeze adoption since launch: agents were confined to Breeze Studio and could not be triggered by external events. The new action lets teams embed agent execution inside any HubSpot workflow, connecting AI agent reasoning to the full automation stack.

This is where Breeze shifts from a standalone AI tool to an automation primitive. Instead of agents waiting for users to invoke them, workflows can trigger agents based on any CRM event: deal stage changes, form submissions, lifecycle stage transitions, ticket creation, or scheduled cadences.

Configuration Options

Agent Selection
  • Choose from marketplace agents or custom agents built in Breeze Studio
  • Configure agent-specific instructions for the workflow context
  • Chain multiple agents in sequence for complex multi-step processes
Context Configuration
  • Pass enrolled record properties as agent input context
  • Include associated records (company, deal, ticket) for richer context
  • Map agent output fields to workflow branches and downstream actions

Example Workflow Patterns

Lead Qualification on Form Submission

Trigger: Contact submits a demo request form. Action: Run the Customer Health agent to research the company, score fit against ICP criteria, and update the lead status property. Branch: Route qualified leads to sales, partially qualified to nurture, and unqualified to a polite decline email.

Deal Risk Assessment on Stage Change

Trigger: Deal moves to negotiation stage. Action: Run the Deal Loss agent to analyze deal history, engagement patterns, and comparable closed-lost deals. Output: Risk score property updated on the deal record. Branch: High risk deals trigger manager notification and mandatory review meeting task.

Churn Prevention on Ticket Escalation

Trigger: Support ticket escalated to Tier 2. Action: Run the Customer Health agent to assess overall account sentiment from recent tickets, NPS scores, and usage data. Output: Health score updated on the company record. Branch: At-risk accounts trigger customer success manager outreach.

Breeze Agents: Features by Hub

HubSpot organizes Breeze agents around its three core hubs: Marketing, Sales, and Service. Each hub has dedicated agents optimized for its workflows, plus shared infrastructure through Breeze Studio and the Data Agent. Understanding which agents map to which hub is essential for planning your marketing automation strategy and CRM investment.

Core Breeze Agents

Content Agent
Marketing Hub

Drafts marketing materials by analyzing existing content and CRM data to match your brand voice. Generates blog posts, email copy, social posts, and landing page content.

  • Brand voice matching from existing assets
  • Multi-format output (email, blog, social)
  • CRM data integration for personalization
Prospecting Agent
Sales Hub

Automates outbound sales by researching contacts, building company profiles from domain data, and generating personalized email sequences.

  • Contact research and enrichment
  • ICP and value proposition inference
  • Personalized sequence generation
Customer Agent
Service Hub

Conversational support agent trained on your knowledge base, website content, and help articles. Handles customer inquiries across nine supported channels.

  • Trains on PDFs, KB articles, 1,000+ pages
  • Personalized actions (order status, resets)
  • Omnichannel: chat, email, WhatsApp, SMS
Knowledge Base Agent
Service Hub

Identifies gaps in your documentation by reviewing support tickets and drafting help articles to fill missing coverage areas.

  • Ticket analysis for documentation gaps
  • Automated article draft generation
  • Content quality recommendations

Data Agent Workflow Actions

The Data Agent operates across all hubs and provides three workflow-specific actions for processing CRM data at scale. These actions consume 10 credits per execution and can be combined with the Run Agent action in complex workflows.

ActionFunctionUse Case
Custom PromptAnalyze, summarize, or categorize enrolled record data using a custom AI promptSentiment analysis on support tickets, lead scoring commentary
ResearchResearch a company or contact using web data and domain analysisEnriching new leads, competitive intelligence on deal contacts
Fill Smart PropertyPopulate CRM properties with AI-generated data based on record contextAuto-filling industry, company size, or technology stack fields

Pricing, Credits, and Plan Requirements

HubSpot's Breeze pricing model has shifted toward transparent, usage-based billing. Features consume credits from a monthly allocation included with your subscription tier. Understanding the credit economy is essential for budgeting agent deployments and avoiding unexpected costs.

Credit Consumption by Feature

FeatureCredits UsedBilling Unit
Customer Agent100 creditsPer conversation
Prospecting Agent100 creditsPer monitored contact/month
Data Agent10 creditsPer research prompt
Breeze Workflow Actions10 creditsPer action execution
Buyer Intent10 creditsPer company created/monitored
Standard Data EnrichmentFreeIncluded with Core Seat

Plan Requirements for Breeze Agents

Marketing Hub
Professional$800/mo
Enterprise$3,600/mo

Billed annually. Content Agent + Data Agent workflow actions for email personalization.

Sales Hub
Professional$450/mo
Enterprise$1,500/mo

Billed annually. Prospecting Agent + Deal Loss Agent + selling profile generation.

Service Hub
Professional$450/mo
Enterprise$1,500/mo

Billed annually. Customer Agent + Knowledge Base Agent + Help Desk blocking.

For additional credits beyond your included allocation, Breeze Intelligence credits for data enrichment are available at $45/month for 5,000 credits. The quantity of included monthly credits varies based on the highest-level product edition in your subscription and credits are not additive across multiple subscriptions.

Practical Workflow Automation Templates

The following templates combine Breeze agents with standard HubSpot workflow actions to create end-to-end automation sequences. Each template specifies the trigger, agent action, output handling, and estimated credit consumption per execution.

Marketing Hub: Lead Scoring and Nurture Routing

1

Trigger: Contact fills out content download form

Form submission enrollment triggers the workflow for all new leads from gated content.

2

Data Agent: Research company domain

Enrich the contact record with company data, industry classification, and estimated revenue. Cost: 10 credits.

3

Data Agent: Custom prompt for ICP scoring

Score the enriched contact against your ideal customer profile criteria. Update a custom lead score property. Cost: 10 credits.

4

Branch: Route by score

High score: Assign to sales rep. Medium: Enroll in 5-email nurture sequence. Low: Add to newsletter list only.

Total cost per lead: 20 credits | Monthly at 500 leads: 10,000 credits

Sales Hub: Deal Velocity Monitoring

1

Trigger: Deal sits in same stage for 14+ days

Scheduled workflow checks deal stage dates daily and enrolls stalled deals.

2

Run Agent: Deal Loss agent analyzes risk

Agent reviews engagement history, email open rates, meeting frequency, and comparable deals. Cost: 10 credits.

3

Output: Update deal risk score and recommended next action

Agent populates a custom risk score property and writes a recommended action note on the deal timeline.

4

Branch: Notify or escalate

High risk: Slack notification to sales manager + create task. Medium: Email reminder to deal owner with agent recommendations.

Total cost per deal check: 10 credits | Monthly at 200 stalled deals: 2,000 credits

Service Hub: Intelligent Ticket Routing

1

Trigger: New support ticket created

All incoming tickets from email, chat, or form submission enter the workflow.

2

Customer Agent: Attempt automated resolution

Agent searches knowledge base, provides answer, and asks if the issue is resolved. Cost: 100 credits per conversation.

3

Branch: Resolved or escalated

Resolved: Close ticket with satisfaction survey. Unresolved: Route to appropriate Tier 1 queue based on agent's category classification.

4

Audit card: Record agent actions

Audit card logs what the agent attempted, which KB articles were referenced, and why the issue was or was not resolved.

Total cost per ticket: 100 credits (if agent engages) | Monthly at 1,000 tickets: 100,000 credits

Strategic Recommendations for 2026

The January 2026 updates signal HubSpot's direction: agents as composable automation building blocks rather than standalone tools. Teams that treat Breeze agents as workflow primitives alongside standard actions like delays, branches, and property updates will extract the most value. Here is a structured approach to planning your deployment.

Audit Your Current Workflows
  • Identify workflows with manual decision points that agents could automate
  • Map current lead scoring rules that could be replaced by Data Agent analysis
  • Calculate credit consumption for your monthly workflow volume to budget accurately
Start with High-Impact, Low-Volume
  • Deploy agents first on high-value workflows with lower enrollment counts to control credit costs
  • Deal risk assessment on enterprise deals, not every contact form submission
  • Measure agent accuracy for 30 days before expanding to higher-volume workflows
Use Audit Cards for Governance
  • Establish a weekly review cadence for agent audit cards during pilot phase
  • Track agent qualification accuracy against human decisions as a benchmark
  • Document audit findings for compliance teams in regulated industries
Plan for Omnichannel Expansion
  • Prioritize channels by customer volume: deploy Customer Agent on your highest- traffic channel first
  • Train the agent on channel-specific FAQs, not just generic knowledge base content
  • Test WhatsApp and SMS channels separately, as message length limits affect agent response quality

Conclusion

The January 2026 Breeze updates mark HubSpot's transition from offering AI agents as standalone features to embedding them as composable primitives in the workflow engine. The GPT-5 migration improves reasoning quality for Breeze Studio agents. Audit cards solve the trust problem that held back agent adoption. The Run Agent workflow action removes the isolation constraint that limited agent utility.

For teams already on HubSpot Professional or Enterprise tiers, the practical next step is to identify one high-value, low-volume workflow where an agent can replace manual decision-making. Deploy it, measure accuracy using audit cards for 30 days, then expand based on results. The credit-based pricing model rewards targeted deployment over broad rollouts, so starting small is both the prudent and cost-effective approach.

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