Founder, CEO & Strategist since 2001. Anders provides thoughts and reflections about how to think about onlinification and digitalisation in B2B.
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In many B2B organisations, post-sale teams are still caught in a reactive cycle—responding to tickets, chasing usage, and trying to save renewals. But this model no longer scales. Your best customers expect proactive, personalised engagement. And your teams need to deliver high-touch outcomes without growing headcount.
That’s where agentic AI comes in.
In this article, I’ll explore how to evolve your post-sale motion with agentic AI—intelligent systems that don’t just wait for input but act with purpose. You’ll get the framework for leading your team through the four stages of agentic maturity, see how AI agents are helping leaders scale without sacrificing quality, and understand what it takes to get your organisation ready.
Retention is the new growth. But customer expectations have changed. The days of “wait and respond” support are over, especially for enterprise accounts. Today’s VPs of Customer Success, Services, and Support are expected to:
This is achieved while maintaining a constant headcount. Agentic AI makes this possible by transforming systems into intelligent actors, rather than just passive tools.
To lead your team through this shift, you need a clear model. Here’s a simplified version of the agentic maturity framework to guide your evolution:
You rely on human effort, dashboards, and standard automation. AI is minimal or rules-based.
Example: A customer success manager manually checks usage reports and sends follow-up emails.
AI helps surface insights, but humans still drive all actions.
Example: An AI tool flags at-risk accounts, but the CSM decides whether to act.
AI recommends actions and can execute some tasks autonomously within constraints.
Examples: Agents trigger personalised nudges or check-ins based on usage thresholds.
AI operates independently within defined guardrails—anticipating, acting, and learning.
Example: Agents orchestrate onboarding, escalate issues, and propose upsells—without waiting for human prompts.
The goal isn’t to replace humans—it’s to elevate them. Human oversight remains essential, especially at higher levels of complexity and relationship management.
Agentic AI unlocks the ability to do more with less. Here’s how VPs are leveraging agents to extend the impact of their teams:
Agents guide users through personalised steps based on their role, product usage, and behaviour.
Agents identify and address issues before customers even become aware of them.
Agents help maintain QBR prep, track milestones, and surface expansion opportunities.
AI recognises account readiness and drafts customised upgrade proposals.
Instead of hiring more heads, you scale impact through intelligent workflows.
You can’t leap to full autonomy overnight. Becoming genetically ready requires preparation on three fronts:
Agents are only as effective as the data they act on. This means:
Disconnected tools and silos limit agent potential. Your tech stack must enable agents to see context and take action across systems.
Your team must be prepared to work with AI. This includes:
Agentic AI is not science fiction—it’s already reshaping how the best post-sale teams operate. But success doesn’t start with tools. It begins with a clear framework, aligned leadership, and a readiness to evolve how your team thinks, works, and wins.
If you want to deliver proactive, high-touch experiences at scale, now is the time to begin your journey toward agentic maturity.
For more in-depth understanding, here's a downloadable PowerPoint based on The Four Stages of Agentic Maturity.