Databricks Genie One MCP is now generally available! Teams working in ChatGPT, Claude, Cursor, or custom agents can now use one interface to access structured and unstructured data, insights, and answers from Genie One, grounded in governed business context from Genie Ontology. Key highlights: • 𝐂𝐨𝐧𝐬𝐢𝐬𝐭𝐞𝐧𝐭 𝐛𝐮𝐬𝐢𝐧𝐞𝐬𝐬 𝐜𝐨𝐧𝐭𝐞𝐱𝐭 across agents, with shared definitions and domain semantics • 𝐑𝐢𝐜𝐡, 𝐝𝐚𝐭𝐚-𝐬𝐦𝐚𝐫𝐭 𝐞𝐱𝐩𝐞𝐫𝐢𝐞𝐧𝐜𝐞𝐬 including questions, results, visualizations, and Genie Ontology citations • 𝐂𝐞𝐧𝐭𝐫𝐚𝐥𝐢𝐳𝐞𝐝 𝐠𝐨𝐯𝐞𝐫𝐧𝐚𝐧𝐜𝐞 through Unity Gateway, with fine-grained policies and audit logging Genie One MCP brings trusted business context into the tools teams already use.

Databricks Chief Information Officer Naveen Zutshi has been named to TIME's 2026 Executives of the Year: Tech & Data list! @TIME highlights Naveen's mission to make every Databricks employee a builder with Genie, while strengthening the data governance behind how Genie accesses and acts on company data. Congratulations to Naveen and all 50 leaders shaping the future of technology, AI, cybersecurity, and digital innovation. Explore the full list:

Databricks CEO and co-founder @alighodsi joined @bhalligan on Long Strange Trip to share his journey to CEO, how to hire and scale, and where the next unlock in enterprise AI is. "You need to capture the enterprise context - every meeting that's being recorded, every email - then feed it to your AI." That's the missing piece that will allow organizations to move from using AI as a chatbot to having thousands of AI agents that work with each other and autonomously to move work forward. Watch the full episode:

Databricks' @alighodsi on AI risk and adoption: Ali isn't losing sleep over the existential risk debate. He says a number of conditions would all have to be true simultaneously to enable an actual runaway takeoff scenario, and currently several opposite conditions exist. Each frontier training run requires significantly more resources. Power, GPUs, engineers - and some attempts fail, burning up huge piles of money with them. Until that reverses, he doesn't see the self-improving loop happening. Cyber is what he's watching most closely and where he anticipates real impact. Most orgs are not equipped for the coming change in agentic capabilities. The time between a vulnerability being published and being weaponized has collapsed from years to hours. On adoption, he believes most companies don't need a smarter model. The models are already smart enough. The gap is context they don't absorb - the things an employee who's worked at a company for five years learned by osmosis. If the frontier stopped advancing today, he thinks it wouldn't meaningfully change the value most are extracting from AI anyway. In conversation with a16z's Martin Casado and Sarah Wang: 00:00 Intro 00:48 Why Ali places the AI risk near zero 05:05 The word "pacing" was a mistake 10:50 What 10k agents and $100m can do 12:20 What would change his mind on AI risk 14:20 More GPUs, more ways to fail 18:05 US export controls on PlayStations 20:10 The damage everyone expected by now 24:30 Public vulnerabilities weaponized in hours 30:15 Why labs can't grade each other 37:15 Why most of RSI isn't actually RSI 40:05 Why nobody really needs a smarter model 41:50 The AI use cases nobody argues about 47:30 Google Search solved this 25 years ago 50:55 Nobody has privileged knowledge now 55:10 Same model, new harness, 2x cost 58:15 Open source: 5% of spend, 60% of tokens 1:05:30 90% of new databases are created by agents YouTube: @databricks @martin_casado @sarahdingwang

Databricks CEO and co-founder @alighodsi joined @EdLudlow on Bloomberg Tech to discuss the AI pacing debate and why he believes the existential risk to humanity today is close to zero. On where companies should focus their efforts today, Ghodsi shares, “AI models are great at breaking in, and they have all these targets to go through. We have to make huge investments in cybersecurity and protect our software systems." Lakewatch is purpose-built to help defend against those risks. Watch the full segment:

Databricks CEO Ali Ghodsi says people shouldn’t lose sleep over fears of AI taking over humanity, but warns the technology poses a real cybersecurity threat — one that will require “huge investments” to protect software systems around the world. Watch our full interview here:

.@Databricks CRO Ron Gabrisko grew the business from $1M to $7B ARR. Here's what he thinks is the biggest mistake in sales, and the four stages every company grows through: "The biggest mistake I see is salespeople start pitching before they understand anything about you or your challenges. Get to know somebody, build rapport, ask questions first. On the company side, there are four stages. Zero to $10 or $20 million, you're finding product-market fit. $20 to $100 million, you're building a repeatable playbook. $100 million to a billion, you're expanding internationally and into partners. Past a billion, it's about the right leaders, culture, and running fast. Each stage needs different things. You usually need salespeople to push your product, because people don't know about it or how to use it. If people are buying stuff, you want people to sell stuff."

.@databricks CRO on the real reason enterprises still struggle with AI adoption: "Everybody has an FDE model now, but they need help wiring it all together. It's not simple. The biggest challenge is the data. Everybody knows the data is the key to these enterprise use cases. But in a lot of cases, the data isn't in the right place. It's all over the place, in legacy systems, old formats, proprietary formats. Getting your data into a good place to attach AI is a tough, complicated problem that they're using Databricks for."

.@Databricks CRO Ron Gabrisko on why open source users won't just buy from you: "We tried PLG first. We thought customers would just come to us and ask to buy. It wasn't working. Customers in open source don't really want to buy anything. You have to ask them what they're willing to pay for. If I get my support question answered, I'm good to go. PLG is people coming to you. Sales is you going to them. It's the opposite. Salespeople open doors. That said, if you have a great PLG motion like ours, with tons of people coming in the door, you still need salespeople to go sell them the thing you actually monetize."