Content: # Day Two of the Agentic Era: Operationalising AI Across the Funnel
The initial hype of generative AI (Day One) was about writing emails faster and summarizing calls. We are now entering Day Two: the Agentic Era. This is where AI moves from being a passive tool to an active agent, capable of executing complex, multi-step workflows across the entire GTM funnel.
This article explores how revenue leaders can operationalize agentic AI, moving beyond point solutions to build a truly AI-native revenue engine.
What We'll Cover
In this article, we will cover:
- The shift from Generative AI to Agentic AI
- What an AI-native GTM funnel looks like
- 3 agentic workflows for Sales, Marketing, and CS
- How to manage and govern AI agents
Understanding the Approach
Agentic AI refers to systems that can understand a goal, formulate a plan, and execute a series of actions across different software platforms to achieve that goal, with minimal human intervention. In RevOps, this means AI that can update CRMs, trigger marketing campaigns, and alert sales reps autonomously.
Example: An inbound lead comes in. An AI agent researches the company, determines it's a high-priority target, routes it to the best available AE, drafts a highly personalized intro email, and sends a Slack alert to the AE with a summary of the account—all in seconds.
Why This Matters
Operationalizing agentic AI is the key to achieving non-linear growth, allowing teams to scale output without scaling headcount.
- Before: RevOps builds complex, brittle rules in the CRM to route leads. After: An AI agent intelligently routes leads based on nuanced data and real-time context.
- Before: Reps spend hours orchestrating data between different tools. After: AI agents act as the connective tissue, seamlessly moving data and executing tasks across the stack.
The Complete Guide
Workflow 1: The Autonomous SDR
Objective: Automate the entire top-of-funnel research and outreach process.
Actionable Advice: Deploy an AI agent to monitor intent signals, identify target accounts, research the buying committee, and execute a multi-channel outreach sequence.
Best Practices: Ensure human oversight remains for the final review of messaging, especially for high-value accounts.
Workflow 2: The Deal Desk Assistant
Objective: Accelerate complex deals by automating approvals and pricing.
Actionable Advice: Use an AI agent to review incoming proposals against historical data, automatically approving standard discounts and flagging complex deals for human review.
Best Practices: Train the agent on your specific pricing guidelines and historical win/loss data.
Workflow 3: The Proactive CS Agent
Objective: Identify and address churn risk before the customer complains.
Actionable Advice: Configure an AI agent to monitor product usage telemetry and support tickets. If it detects a pattern indicative of churn, it automatically alerts the CSM and drafts a mitigation plan.
Best Practices: The agent should focus on leading indicators of churn, not just lagging indicators like a missed payment.
How to Implement This
RevOps is the command center for the Agentic Era. They are responsible for designing the workflows, deploying the agents, and establishing the governance frameworks to ensure the AI acts within company guidelines. Sales, Marketing, and CS leadership must redefine their team's roles, shifting them from task execution to strategy and relationship management.
Next Steps
The Agentic Era isn't about replacing your revenue team; it's about giving them superpowers. By operationalizing AI across the funnel, you build an engine that's faster, smarter, and more efficient than your competition.
Map out your current lead routing process. Identify the manual steps that slow it down. This is your first candidate for agentic automation. Ready to enter Day Two? Explore Brazn's agentic AI platform.
Day Two of the Agentic Era: Operationalising AI Across the Funnel
The initial hype of generative AI (Day One) was about writing emails faster and summarizing calls. We are now entering Day Two: the Agentic Era. This is where AI moves from being a passive tool to an active agent, capable of executing complex, multi-step workflows across the entire GTM funnel.
This article explores how revenue leaders can operationalize agentic AI, moving beyond point solutions to build a truly AI-native revenue engine.
What We'll Cover
In this article, we will cover:
- The shift from Generative AI to Agentic AI
- What an AI-native GTM funnel looks like
- 3 agentic workflows for Sales, Marketing, and CS
- How to manage and govern AI agents
Understanding the Approach
Agentic AI refers to systems that can understand a goal, formulate a plan, and execute a series of actions across different software platforms to achieve that goal, with minimal human intervention. In RevOps, this means AI that can update CRM systems, trigger marketing campaigns, and alert sales reps autonomously.
Example: An inbound lead comes in. An AI agent researches the company, determines it's a high-priority target, routes it to the best available AE, drafts a highly personalized intro email, and sends a Slack alert to the AE with a summary of the account—all in seconds.
Why This Matters
Operationalizing agentic AI is the key to achieving non-linear growth, allowing teams to scale output without scaling headcount.
- Before: RevOps builds complex, brittle rules in the CRM to route leads. After: An AI agent intelligently routes leads based on nuanced data and real-time context.
- Before: Reps spend hours orchestrating data between different tools. After: AI agents act as the connective tissue, seamlessly moving data and executing tasks across the stack.
The Complete Guide
Workflow 1: The Autonomous SDR
Objective: Automate the entire top-of-funnel research and outreach process.
Actionable Advice: Deploy an AI agent to monitor intent signals, identify target accounts, research the buying committee, and execute a multi-channel outreach sequence.
Best Practices: Ensure human oversight remains for the final review of messaging, especially for high-value accounts.
Workflow 2: The Deal Desk Assistant
Objective: Accelerate complex deals by automating approvals and pricing.
Actionable Advice: Use an AI agent to review incoming proposals against historical data, automatically approving standard discounts and flagging complex deals for human review.
Best Practices: Train the agent on your specific pricing guidelines and historical win/loss data.
Workflow 3: The Proactive CS Agent
Objective: Identify and address churn risk before the customer complains.
Actionable Advice: Configure an AI agent to monitor product usage telemetry and support tickets. If it detects a pattern indicative of churn, it automatically alerts the CSM and drafts a mitigation plan.
Best Practices: The agent should focus on leading indicators of churn, not just lagging indicators like a missed payment.
How to Implement This
RevOps is the command center for the Agentic Era. They are responsible for designing the workflows, deploying the agents, and establishing the governance frameworks to ensure the AI acts within company guidelines. Sales, Marketing, and CS leadership must redefine their team's roles, shifting them from task execution to strategy and relationship management.
Next Steps
The Agentic Era isn't about replacing your revenue team; it's about giving them superpowers. By operationalizing AI across the funnel, you build an engine that's faster, smarter, and more efficient than your competition.
Map out your current lead routing process. Identify the manual steps that slow it down. This is your first candidate for agentic automation. Ready to enter Day Two? Explore Brazn's agentic AI platform.
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About the Author
Alex Margarit, Sales AI Expert, SaaS Sales Leader, BMC, ServiceNow, Docusign — 25+ years in SaaS sales.
