DataRobot

Data isn’t the new oil. Decoded with Debanjan | Week 4🤖 Stop us if you’ve heard this one before: “Data is the new oil.” This week, our CEO Debanjan Saha explains why this isn’t the case – and exactly where the value lies with data. At DataRobot, we know the gap between the glossy presentation and the day-to-day reality of scaling enterprise AI is massive. That's why every Wednesday, Debanjan is here to decode hype from reality. See you next week😎

🚨 Our new survey with IDC makes one thing clear: enterprises are feeling an AI cost crisis. 96% of organizations deploying GenAI and 92% using agentic AI are facing higher-than-expected costs. Even more alarming? 71% admit they have little to no control over where those costs are coming from. We partnered with IDC to uncover where the money is really going, and why early movers with governance and cost visibility are separating from the pack. 👉 Download the full report: https://bit.ly/4pv0bmD

Japan is showing the world what’s next: AI as a continuity plan. From labor shortages to legacy expertise, the Agent Workforce is becoming a continuity plan, not just an efficiency play. Love this perspective from our CRO on why governance and real control matter as AI gets to work.

Sunday recap edition ☕️ Quick hits from the week at DataRobot: 📍The Verge tapped our own Alex Conway to break down Google’s Gemini 3 — which just posted monster gains on ARC-AGI-2 and SimpleQA while cutting cost per task nearly in half. 📍Most teams think about governance way too late — once costs, complexity, and rework have already piled up. Our latest blog broke down the real moment to stand up a control layer: when you’ve got a few active use cases, real workflows flowing, core components wired together, and clear policies to enforce. 📍CEO Corner | Week 3 🤖 “AI isn’t smart.” Debanjan Saha separated intelligence from pattern recognition — and what that means for scaling AI responsibly. 📍Recap from the road with SAP in Atlanta. One takeaway: every org wants AI ROI, but only the ones who reduce data complexity get there fast. What's next? 🤠: https://bit.ly/41EoVim

⏪ Last month, our team attended the SAP Platform & Data Summit in Atlanta. One theme came through loud and clear: AI is reshaping every job and every industry. But the real question for most organizations is: How do we actually start AI projects that deliver measurable ROI? Key takeaways: 🔹 Every customer is on a different AI journey. Almost everyone in the room is using GenAI for personal productivity—but few have extended it into core business processes where the real impact happens. 🔹 To stay competitive, organizations must reduce complexity. As SAP’s Bob Sakalas put it: For years, data products were provided as “unassembled race cars”—powerful, but difficult to put together. Today, SAP Business Data Cloud + DataRobot together provide customers the fully assembled, high-performance vehicle to help teams move fast and deliver real value. Proud to partner with SAP to help organizations scale AI that’s secure, resilient, and built for real results. Dave Maloney Michael Huang Nathan Crook Lionel Susini SAP Business Technology Platform

AI isn’t smart. Welcome to the CEO Corner | Week 3 🤖 This week, Debanjan Saha explains the difference between intelligence and pattern recognition in AI -- and what this means for deploying AI at scale. Every Wednesday, we’re dropping fresh, sharp insights you can actually use. Follow along and take notes 💼💡

Most teams wait too long to think about an AI gateway. By the time complexity, costs, and governance gaps start to show up, they’re already deep into rework. The real signal is your maturity stage. If you’re running early pilots, building core components, and proving value in production, you’re in the window where a gateway prevents sprawl instead of cleaning it up later. A gateway only works when the basics are in place: a few active use cases, real workflows, core components connected, and clear policies to enforce. If you can answer those pieces with confidence, you’re ready to stand up the control layer that keeps agentic AI scalable and safe as adoption grows. See the full AI gateway framework: https://bit.ly/4pG0B9l

Big developments in the model landscape — and one of our own is helping unpack what they mean. The Verge took a close look at Google’s new Gemini 3 release and tapped DataRobot Principal Software Engineer Alex Conway to break down what the latest benchmark jumps signal for the future of reasoning and research-heavy AI workloads. Alex highlighted Gemini 3’s standout performance on ARC-AGI-2 and SimpleQA — scoring nearly twice as high as competing models while dramatically cutting cost per task. His perspective sheds light on where the industry is heading, especially for complex, niche, and scientific use cases. Great to see thoughtful technical analysis from our team contributing to the broader conversation. Read the full article: https://bit.ly/4rsvHmK

Sunday recap edition☕️ ICYMI, here’s what went down at DataRobot this week: 📍Manish Harsh spent time with AI leaders breaking down the infrastructure shifts making modern, large-scale AI possible — from new compute architectures to the rise of distributed, containerized workloads. 📍Agents in the AM kept us busy across the globe: Dubai wrapped with big energy, and Riyadh delivered smart people, sharp ideas, and a whole lot of “wow, this is where AI is headed” moments. 📍And in CEO Corner | Week 2, Debanjan Saha tackled a big question: why do hyperscalers create so much friction for enterprise AI teams — and what does it actually take to make AI work? Want more DataRobot? Catch us on the road: https://bit.ly/41EoVim