In this episode, we’re joined by Rav Dhaliwal, recovering software exec turned early-stage VC at Crane. A longtime CS leader and board-level advisor, Rav breaks down how AI is reshaping Customer Success, from onboarding and telemetry-driven predictions to agentic workflows, while pushing CS to converge with account management and get far more revenue-centric.
We spoke with Rav about what AI should (and shouldn’t) automate, how to keep relationships authentic, and how leaders actually drive adoption, treating AI not as a tool drop but a behavioral change program.
Here are some of the key questions we address:
- Will AI compress or redefine CS, and where does it create leverage vs. require human expertise?
- What does the CS–Account Management convergence look like in practice (discovery, multi-threading, commercial acumen)?
- Which AI use cases move the needle now: telemetry-based churn/upsell prediction, voice sentiment, and agentic next-best-action?
- How do you avoid the “AI for efficiency only” trap and tie it to revenue, cost, and risk outcomes that customers actually buy?
- What’s the playbook for AI adoption in GTM/CS? How do leaders run a change program (not a tool rollout) and measure progress?
- Where are the authenticity risks and how do you keep the customer relationship human?
- How far can we push AI-led onboarding and what’s the 90% automated vs. 10% bespoke split likely to be?
🎧 Tune in to hear Rav’s pragmatic take on CS in the age of AI: more signal, smarter workflows, tighter revenue alignment and leadership that treats AI as an operating change, not a shiny tool. Also, watch out for his new book coming out shortly on Founder-Led Sales!
