AI at Rimini Street: A Computer Weekly Downtime Upload Podcast

Why It Matters

The efficiency gains lower labor costs and boost competitiveness for third‑party support providers, while the cautious approach highlights the need for responsible AI integration across the tech services sector.

Key Takeaways

• AI cuts support call handling time by 30%.
• Response time now under two minutes per case.
• Microsoft Copilot deployed to all employees for assistance.
• AI routes cases to optimal engineers, improving accuracy.
• Company remains in experimental learning phase with AI.

Pulse Analysis

The rapid evolution of artificial intelligence has reached the enterprise support arena, and Rimini Street is a vivid example. As a third‑party software support provider, the company faces intense pressure to keep costs down while maintaining high service levels. In a recent Computer Weekly Downtime Upload podcast, CEO Seth Ravin explained that AI is no longer a futuristic concept but a daily operational tool. This shift mirrors a broader industry trend where AI‑driven automation is reshaping how support teams triage and resolve customer issues. These capabilities also position Rimini Street to compete more effectively against original vendor support.

Rimini Street has deployed Microsoft Copilot and Google Gemini across its workforce, using them to route incoming calls to the most suitable engineers. The AI‑powered triage reduces average handling time by roughly 30%, allowing the firm to answer customers in under two minutes. Engineers receive contextual information and source references, turning the AI into a real‑time research assistant that accelerates problem solving. Ravin reports that this augmentation makes engineers “better engineers,” improving both accuracy and speed without replacing human expertise.

Despite the gains, Ravin admits Rimini Street is still in a learning phase, experimenting with prompts, governance, and trust in AI outputs. He stresses the importance of skepticism, urging staff to verify source material before acting on AI‑generated conclusions. This cautious stance reflects a wider industry conversation about responsible AI deployment, especially in mission‑critical support functions where errors can damage client relationships. As more firms adopt similar technologies, balancing efficiency with oversight will be key to unlocking AI’s full potential in enterprise support.