Rippling's unified data graph proves AI needs clean data to deliver real GTM value

The Gist

• Rippling's AI strategy hinges on a single connected database across 25+ products
• Their employee graph enables AI to generate actionable insights and workflows in seconds
• Competitors with patched-together data struggle to match Rippling's AI accuracy and trust
• The demo showed AI building company dashboards and top-performer reports from natural prompts

• Rippling's AI success hinges on a single, unified database underlying all its products, ensuring clean and connected data.
• AI can only deliver real value when it operates on a clean, connected data graph, not fragmented or acquired data.
• Rippling's AI demo showcased three stages: insights, actions, and proactive workflows, illustrating a product arc for AI in business data.
• Permissions and strong typing are critical for AI to take actionable steps without causing liabilities.
• The winners in the AI race will be companies with connected data layers, not just advanced models.
• Rippling's decade-long focus on building a unified data graph positions it as a leader in AI-driven business intelligence.

• Audit your data layer before focusing on AI models to ensure clean, connected data.
• Implement strong permissions and data typing to enable AI to take actionable steps safely.
• Build AI product arcs that start with insights, progress to actions, and culminate in proactive workflows.
• Focus on becoming a system of intelligence, not just a system of record, by leveraging connected data.

• 25+ products (Rippling's employee graph underpins all its products, including payroll, HR, recruiting, and more.)
• 1 million queryable fields (Rippling's database covers extensive employee data, from titles to tax handling for part-time employees in Germany.)
• 71% of top performers had six or more years of tenure (Insight from Rippling's AI analysis of employee performance data.)
• 400+ LinkedIn posts (User-generated content highlighting the impact of Rippling AI within two months of early release.)