Philip Lacor, CRO of Personio—a $3B+ HR and payroll platform with 1, 500 employees, 15, 000 customers, and a 400-person sales team—shared an insightful AI transformation journey at SaaStr AI London that serves as a template for revenue leaders aiming to deploy AI effectively in go-to-market (GTM) strategies. While many AI-native companies like Replit and Harvey are excelling, Personio faced a distinct challenge: operating a large, traditional B2B company burdened with legacy processes. In May 2024, their CEO launched “AI Surge Week, ” sparking a remarkable transformation within six months. This led to 90% of their team using large language models (LLMs) weekly, the creation of 400+ AI assistants, a drastic cut in research time for sales reps (from two hours to 15 minutes), and an AI-driven SDR booking 140 meetings in just seven days. **Key Lessons from Personio’s AI Transformation:** 1. **Combine Top-Down and Bottom-Up Initiatives:** Initial excitement and widespread AI use didn’t automatically mean transformation. True change required leadership making hard decisions about resource allocation, budget, and prioritization. Personio established an “AI Powered Go-To-Market” working group to pair grassroots experimentation with strategic top-down support. Bottom-up drives innovation; top-down enables scale. 2. **Cross-Functional Collaboration is Essential:** Successful AI in GTM demands teamwork across data and systems teams, revenue operations, GTM engineers, and business users like sales and marketing. Without this integration, tools either lack business relevance or users do not get proper support. Personio’s 15-member working group built broad cultural buy-in and practical solutions bridging all areas. 3. **Use Jobs-to-Be-Done to Prioritize Ruthlessly:** Excitement led to many half-finished AI projects before they prioritized effectively. By shadowing account managers and mapping every role’s daily tasks against the customer journey, they identified where time was wasted most and focused AI efforts on solving high-impact pain points—avoiding the trap of chasing every shiny AI use case. 4. **Cultivate an AI Culture through Leading, Sharing, and Celebrating:** Transformation multiplies when leaders model AI adoption, teams share their AI innovations openly, and successes are celebrated. Personio encouraged curiosity by reserving President’s Club seats specifically for top AI contributions.

This fostered widespread engagement and sustained momentum. 5. **Great AI Depends on Your Data, Workflow, and Context—not Just Tools:** Rather than buying every new AI tool, Personio focused on layering LLMs onto their core stack (Salesforce/HubSpot, Gong, Qualified, Snowflake, Amazon Bedrock) and deeply cleaning and connecting their data (eliminating duplicates, integrating disparate systems). They enriched models with company-specific information like ICP definitions, pitch decks, and training materials—making AI tailored and truly useful. **Four AI Use Cases That Drove Impact:** - **Win/Loss Intelligence:** Leveraged conversation and CRM data to generate dynamic, actionable battle cards with 10-15% new insights, informing coaching, marketing, and product decisions. - **Expansion SDR Assistant:** Cut SDR research time from two hours to 15 minutes by pulling data from 10-20 systems into Salesforce with smart cross-sell recommendations, doubling pipeline per rep. - **Intent Scoring for Outbound:** Built a dynamic intent model using various signals (web visits, reviews, former user movements) to identify buying signals and prioritize accounts with visual scoring in Salesforce. - **AI Chat/SDR (“Nia”):** Deployed 24/7 AI chat on the website, instantly booking demo meetings and capturing customer insights, resulting in 140 meetings booked in one week and revealing real-time customer concerns and behavior. **Five Critical Mistakes to Avoid:** 1. **Avoid Endless Surface-Level Tool Testing:** Deep, focused engagement with a few tools trumps shallow trials across many. 2. **Move Beyond Just Learning AI—Start Doing AI:** Practical deployment, iteration, and experimentation drive progress more than theory. 3. **Assign Dedicated People to Monitor AI Agents Daily:** Continuous training and adjustment are crucial; otherwise, AI can produce errors or miss opportunities. 4. **Never Build Without Business Context:** LLMs and AI must be built with a thorough understanding of sales processes and customer journeys. 5. **Don’t Expect Plug-and-Play Solutions:** Significant effort cleaning data, connecting systems, and adding company-specific knowledge is required to unlock real AI value. **Looking Ahead: Can AI Enable Growth Without Increasing Headcount?** Personio is spending multiple six figures on AI tools, with each SDR agent’s AI costing about $100K. While some teams may shrink, others—like channel and partner teams—might grow. The goal isn’t layoffs but smarter scaling and reallocating resources. The central question every CRO should ask: “Can we double revenue without doubling headcount?” **Summary:** In just six months post “AI Surge Week, ” Personio achieved a transformative AI-led GTM revolution built on leadership backing, a cross-functional team, job-focused prioritization, a supportive AI culture, and deep integration of AI into their existing tech stack and data. They avoided common pitfalls by focusing on doing over learning, monitoring closely, and grounding AI in business realities. Philip’s closing advice: lean into AI now—everyone’s roles will evolve. While AI-native companies flow fast, real SaaS businesses can outpace expectations with the right playbook. Philip Laheurte’s candid sharing at SaaStr AI London (flown in from NYC) highlights a pragmatic, tested roadmap for AI adoption in mature B2B organizations—proving that with the right combination of strategy, culture, and execution, AI can genuinely transform revenue operations.