Reinventing SaaS: Zuora's AI Transformation | Karthik Chakkarapani and Shakir Karim (Zuora)
From reinventing internal operations with AI agents to cutting deployment cycles from 14 days to 10 minutes, Zuora is transforming into an AI-native SaaS organization.
In this episode of LaunchPod, we’re joined by Shakir Karim (Senior VP of Product) and Karthik Chakkarapani (CIO & Senior VP of Corporate Operations) from Zuora, the company that helped define the SaaS era, and is now reinventing it with AI.
Here’s what we cover:
Why they believe AI is a bigger inflection point than web, mobile, or cloud
Their internal AI agent workflow that automatically resolves thousands of service requests instantly, freeing teams to focus on strategy
How they cut a major feature deployment step from 14 days to 10 minutes using Claude Code
Why prompt-a-thons and hackathons have been vital for driving not just AI adoption but AI literacy
1. The 10x AI Transformation (2:00)
Zuora’s AI transformation initiative started with a bold challenge: How do we become the most efficient SaaS company in our market?
Karthik describes this mission as not just automating processes, but completely reimagining the future of work:
“We don’t want to take a 10-step process and just automate it. We look at how people work today and ask how AI can amplify their potential — reducing friction, unlocking productivity, and creating intelligent systems that learn and evolve.”
The result?
A company-wide framework centered on four principles of the future of work: contextual understanding, smart search, agentic automation, and continuous learning, each supported by AI-native tooling and retraining initiatives.
2. Automating Workflows with AI Agents (7:00)
Before AI, internal service requests at Zuora took three to five days to resolve. Today, their internal AI agent handles 60% of those autonomously.
“We rolled out our first enterprise-wide AI agent for IT and HR a year ago. Now it manages about 10,000 interactions monthly. Employees ask questions in natural language, and the agent pulls from all company knowledge to resolve or fulfill requests instantly.”
The result?
A 60% self-service deflection rate and a seamless employee experience built into their daily workflow.
3. Reinventing SaaS Operations (10:00)
Using Trupeer has been a massive unlock for content creation at Zuora University.
“Every product feature used to require a four-week process to script, record, and localize educational videos,” says Shakir. “Now it takes four hours.”
By feeding rough-cut videos into an AI avatar system, the team automatically generates scripts, translations, and voiceovers, freeing creators to focus on strategy and reach more customers through localized content.
“That’s not just efficiency. That’s velocity.”
4. From 14 Days to 10 Minutes: AI-Powered Deployments (21:00)
For a company that operates as the financial system of record for many SaaS businesses, every feature must be auditable. Integrating new code used to take an entire sprint. Now, it’s done in minutes:
“With Cloud Code, we cut the deployment step from 14 days to 10 minutes. It automatically writes integration code for our immutable notary service. We’re seeing 30–40% efficiency gains in all integration work.”
That means more experiments, faster iteration, and a new threshold for innovation velocity.
5. Building AI Literacy at Scale (26:00)
Zuora didn’t just adopt AI tools; it built an AI-native culture. Through initiatives like AI Week, prompt-a-thons, and hackathons, every employee is encouraged to experiment and build.
Shakir shares:
“Our goal is 100% participation across product and technology. Everyone should have their hands on something — learning how their work will change and how AI can make an impact.”
Karthik adds:
“We’re not chasing small efficiencies. We’re asking: what do we do with the time we save? That’s where new value creation happens.”
Chapters
00:00: Intro
02:15: Zuora’s 10x initiative
07:00: Zuora’s internal AI agent
10:00: Accelerating content creation using Trupeer
12:00: Cutting video content creation down from 4 weeks to 5 hours
17:00: AI in practical workflow
22:00: Scaling AI innovation and literacy internally
28:32: AI prompathons and hackathons
29:54: Conclusion
Links
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