Talking AI at Google Cloud Next and Pythian's Role in Making it Happen

First off, the energy at Google Cloud Next 2025 was palpable. I had the opportunity to chat with hundreds of people, present on stage alongside Hitesh Chellani, Head of Partner Strategy and Programs for Databases and Infrastructure at Google Cloud, my dear friend Howard Holton, Chief Operating Officer at GigaOm and Jeff Schnarr, Chief Information Officer for Day & Ross, and interview with SiliconANGLE theCube and The RavIT Show.
What struck me most from the keynote is a significant shift in the AI conversation. Last year, we talked a lot about the potential of agents. This year? Agents are real. They exist. They're built.
We're seeing concrete implementations embedded directly within the applications we use every day—Agentspace for boosting general productivity, Vertex AI for streamlining those core business processes, and intelligent AI features woven into the fabric of BigQuery, our databases and of course, the powerhouse that is Workspace with Gemini.
- Shift from conceptual to real agents: Unlike last year's discussions about potential AI agents, this year's keynote highlighted agents that exist now and are embedded within existing applications.
- People vs. process productivity: Agents are categorized into two types—those enhancing people productivity (like Agentspace for general work) and those boosting process productivity (like Vertex AI).
- Embedded AI everywhere: AI features are increasingly integrated into core Google Cloud services like BigQuery, databases, and especially Workspace with Gemini. Implementing Gemini for workspace is a practical way to drive AI adoption across your entire organization.
- Implementation is key: The focus has shifted from theoretical exploration to actual implementation of AI solutions.
Advice to CIOs: Adopt AI organization-wide with Gemini
Honestly, if I were a CIO right now trying to wrap my head around AI adoption, I'd be looking very closely at implementing Gemini for the app and workspace. It's a tangible way to cut through the philosophical complexities and get real AI power into the hands of your teams. It's what we're hearing from other enterprise leaders too. 2024 and a bit of 2025 have been about understanding the what, and now it's full steam ahead into the how of implementation.
Identify your AI use case and advance your roadmap
First and foremost, a huge chunk of the enterprises we talk to are still in the education and activation phase. They grasp the AI buzzwords, but the practical understanding is still developing. That's where our Field CTO practice comes in—seasoned CIOs, CTOs, and CAIOs who've been through this before.
We come in, cut through the noise, and help organizations identify the real impactful use cases. Trust me, when we hear about 400 potential AI projects, we usually find that only about five are truly AI-driven and strategically valuable. The rest often fall into the analytics bucket.
Pythian provides a practical approach to implementing AI
Many enterprises understand the basic AI language but need help with practical application. Pythian's Field CTOs provide education and activation services. We help narrow down the often large number of perceived use cases to a manageable and impactful few.
- People productivity: Pythian helps implement solutions like Agentspace and enterprise search, which are valuable for finding internal information and getting comprehensive debriefs on various topics.
- Building practical solutions: Instead of large, high-risk projects, Pythian focuses on building smaller, faster-to-implement projects (e.g., 4-week projects with quick ROI).
- Implementing AI features: Pythian provides expertise in enabling and implementing data agents and AI features within analytics tools like BigQuery, databases and Looker, an area where many data engineers may lack specific expertise.
If you're looking to cut through the AI hype and get down to practical implementation, or if you're grappling with modernizing your data infrastructure on Google Cloud, I encourage you to reach out. Either myself, Ernest Solomon, Jeff DeVerter, or Karen Pfeifer will be your primary point of contact in building your data and AI strategy—starting with our AI workshop.
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