A SaaStr AI + Annual Summit explored the automation of finance operations by OpenAI, Rippling, SnapLogic, and Gorgias, highlighting critical mistakes even AI-first companies encounter.
**The Panel:** Moderated by Lloyed Lobo – Co-founder of Boast.AI, author of “From Grassroots to Greatness”
– Sowmya Ranganathan – Ex-Controller at OpenAI and Rippling
– Ahsan Malik – CFO at SnapLogic, former VP Finance at BlueJeans
– Kunal Agarwal – CFO at Gorgias, former VP Finance at Navan
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**Quotable Moments**
– *Sowmya Ranganathan (Ex-Controller, OpenAI):* “99% of GAAP revenue is going touchless from Stripe all the way to NetSuite. Revenue close basically happens real-time.”
– *Ahsan Malik (SnapLogic):* “We ended up cutting essentially a day and a half out of close with AI and more importantly finding revenue that was essentially leakage — things that were entitled that we should have been billing for.”
– *Kunal Agarwal (Gorgias):* “I aspire to be Switzerland, so I try to be kind of a neutral party… I view a lot of my role as the chief accountability officer.”
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**What These Finance Leaders Actually Built**
**OpenAI: From 10 to 45 People, Not 300**
Sowmya joined OpenAI in March 2023, growing the finance team from 10 to ~45 by March 2025, whereas similar companies operate with 200-300 person teams.
**Automation Wins:**
– 99% touchless revenue automation from Stripe to NetSuite
– GPU cost reporting went from 15 days to real-time dashboards
– Teaching CPAs to code using Python with ChatGPT assistance
The key was transitioning Azure GPU reports into millions of rows manageable with Python scripts, aided by ChatGPT, processing in seconds.
**SnapLogic: Finding Hidden Revenue Through AI Agents**
SnapLogic, with a $100M+ ARR, operates a lean team but deployed AI agents internally.
**Breakthrough Use Case:**
– Order form reconciliation solved through AI, saving 1.5 days and uncovering revenue leakage.
– AI expanded for legal contract analysis on termination clauses, emphasizing tailor-made AI solutions.
**Gorgias: The Data-First Finance Strategy**
Kunal’s strategy at Gorgias includes finance intertwined with data analytics.
**AI Wins:**
– Predictive customer behavior modeling
– Churn risk scoring
– Inbound lead scoring with enriched market data
– Semantic layer database translating questions into plain English
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**The 5 Critical Mistakes Each Speaker Made**
**Sowmya Ranganathan (OpenAI):**
1. Overselling the “teach CPAs Python” narrative neglects resource limitations.
2. Ignored compliance aspects in automation.
3. Dismissed the impact of role elimination on teams.
4. No focus on change management.
5. Oversimplified technical requirements.
**Ahsan Malik (SnapLogic):**
1. Focused more on product than finance expertise.
2. Simplistic risk framework.
3. Underestimated people challenges.
4. Skipped integration complexities.
5. Late emphasis on customer data sensitivity.
**Kunal Agarwal (Gorgias):**
1. Possibly overstaffed data team.
2. More philosophical than practical focus.
3. Oversold semantic layer capabilities.
4. Avoided early hard AI questions.
5. Created role clarity confusion.
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**The Real Lessons for B2B Companies**
**Start with the Biggest Pain Point:**
– OpenAI: GPU cost allocation improved processing efficiency significantly.
– SnapLogic: Streamlined order form reconciliation.
– Gorgias: Enhanced customer behavior prediction for forecasting.
**Three-Layer Automation Strategy:**
1. **Data Layer:** Clean and accessible data foundation.
2. **Process Layer:** AI-assisted analysis with exceptions management.
3. **Decision Layer:** Human oversight augmented by AI.
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**What to Avoid (The Mistakes They Made):**
1. Don’t start with technology; focus on process needs first.
2. Maintain governance in automation strategies.
3. Avoid overselling AI simplicity.
4. Emphasize change management in automation efforts.
5. Differentiate efficiency from effectiveness.
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**The Tactical Playbook: What to Do Monday Morning**
**For Series A CFOs:**
**Month 1: Assessment**
– Review the time-consuming close processes.
– Map data sources.
– Identify reconciliation challenges.
**Month 2: Foundation**
– Prioritize data cleanliness.
– Ensure secure access to AI platforms.
– Establish risk tolerance levels.
**Month 3: First Automation**
– Choose a process with clear success markers.
– Aim for 80% automation with human validation.
– Keep comprehensive documentation.
**For Growth-