ZARZA We are Zarza, the prestigious firm behind major projects in information technology.
Listen "197. Rav Dhaliwal, Investor and Limited Partner, Crane - CS Meets Revenue: AI, Agents, and the New Customer Success"
Episode Synopsis
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!
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!
In God we trust