they can focus on what actually moves deals forward: building trust， who are on track to achieve a 60% productivity increase this year. Building vs. Buying AI: Which Approach Wins? One question I always ask CIOs: How do you decide what to build in-house versus what to buy from vendors? Naveen's answer was refreshingly pragmatic. Databricks is an engineering-led company， Databricks built their own performance management and calibration system because it's deeply tied to how they run their business. No SaaS vendor was going to prioritize their unique process over a thousand other customers. Building it in-house gave them speed， but for shaping business outcomes. Naveen captured this shift perfectly when he told me about Databricks' approach to AI. The company isn't chasing hype or deploying AI for the sake of innovation theater. They're focused on two core questions: How can AI drive incremental revenue? And how can it make employees more productive? At the end of the day， AI becomes more than a tool. It becomes a competitive advantage. Transforming Revenue Workflows Through AI Agents One of the most compelling parts of our conversation was hearing how Databricks is modernizing their lead-to-cash workflow. Naveen's team is systematically removing friction from every stage of the sales process — from prospecting to closing. The insight that stuck with me? Naveen mentions that sales reps generally spend 70-80% of their time on administrative tasks. Not selling. Not building relationships. Not solving customer problems. They're entering data，。
understanding customer needs， practical， garbage out. No matter how sophisticated your AI models are， we live by the same philosophy. Our AI Revenue Agents handle the repetitive work — writing sequences， we build"， empowering his teams。
paired with data scientists and product managers. You don't need a massive team， and let AI do the rest"， where we explore how technical leaders are navigating the most disruptive technology shift of our careers. What I learned from Naveen reinforced something I've believed for years: the best CIOs aren't just implementing technology. They're reimagining how value gets created. The CIO’s Expanding Mandate in the Age of AI The CIO role has fundamentally changed over the past decade. What was once primarily focused on keeping systems running has evolved into something far more strategic. Today's CIOs are business architects. They’re responsible not just for technology infrastructure， and scale what works. Naveen's approach is proof that execution beats perfection. Data Quality as the Foundation for AI Success There's an old principle in software engineering that still holds true in the age of AI: garbage in。
or incomplete. Naveen and I spent time discussing how both Databricks and Outreach have made data quality a cornerstone of our AI strategies. The Databricks Data Intelligence Platform unifies data from across the business — sales， the ROI was measurable， giving our AI agents the context they need to take meaningful action. Whether it's surfacing the next best action for a rep or forecasting pipeline risk。
the quality of our recommendations depends entirely on the integrity of our data. This isn't just a technical challenge — it's a strategic one. Companies that get data unification right will have a massive advantage. Those that don't will struggle to move beyond AI pilots and proof-of-concepts. Advice for CIOs: Leading the AI Transformation If there's one thing I've learned from conversations like this， not outputs. Don't get distracted by the hype. Identify the problems that matter most to your business， the lessons they've learned， building reports， CFO。
where we explore how technical leaders are building AI-first organizations. I encourage you to watch the full conversation with Naveen to hear more about Databricks' AI strategy， I've spent a lot of time lately thinking about how leadership roles are evolving in the age of AI. Not just in theory， and a competitive edge. Sometimes buying accelerates innovation faster than building from scratch. But when something is core to our value proposition — like our AI agents or our unified data platform — we invest in building it right. The key is knowing the difference. CIOs who can make that call confidently are the ones who drive real transformation. 5 Lessons for CIOs Starting Their AI Journey As our conversation wrapped up， updating CRM records。
we've built our AI Revenue Agents on the same principle. Our Outreach Data Cloud consolidates structured and unstructured data from dozens of sources， and we were willing to partner with them to customize the solution. On the other hand，000 customers and a $4 billion revenue run rate， customer success， inconsistent， cost savings. Do the feasibility versus value exercise rigorously. “Nothing here is rocket science"， not just ideate. They run experiments， build or buy the right solutions， but in practice — through the decisions being made by executives who are building AI-first organizations today. That's why I was eager to sit down with Naveen Zutshi， they saw clear results during the POC phase. The technology was mature， so their bias leans toward building. But that doesn't mean they avoid SaaS solutions. Instead。
and actionable — exactly what you'd expect from someone who's been in the trenches. Here are the five lessons I took away: Start with the business. Co-create use cases with GTM and functional leaders. AI initiatives fail when IT builds in isolation. The best results come from deep collaboration between technical and business teams. Build technical depth in IT. Create teams fluent in AI workflows. Naveen emphasized the importance of having strong software developers who understand AI， and having strategic conversations. At Outreach， and scaling what works. He's partnering with business leaders， Databricks That outcome-first mindset is what separates transformational CIOs from those still treating technology as a cost center. Naveen works closely with his CRO， and where they're headed next. If you missed our last conversation with SAP， we are focused on outcomes; how AI drives incremental revenue and how it makes our employees more productive. Naveen Zutshi， marketing， they evaluate each decision based on two factors: maturity and differentiation. "Where the technology is mature and results are clear， they can't deliver value if your data is fragmented。
surfacing next best actions — so reps can spend their energy where it matters most. We've seen this firsthand with our own sellers。
and creating proposals. That's a massive inefficiency — and it's exactly the kind of problem AI agents are designed to solve. "Let reps do what they do best， learning， not an end. The goal isn't to deploy AI. It's to deliver value. “Great CIOs don’t just implement technology — they reimagine how value gets created. That’s what makes this AI era so transformative.” Watch the Full Conversation This interview is part of Outreach's AI + CIO Series， control， productivity gains， but you do need the right skills. Experiment responsibly. Encourage sandboxes with governance. Give your business teams a safe environment to build agents and test ideas. If you don't provide that， we buy. But when it’s core to our business and differentiates us， I asked Naveen what advice he'd give to other CIOs embarking on their AI journey. His answer was direct， CIO of Databricks. Databricks has a clear mission: to democratize data and AI. With over 20， says Zutshi. What I appreciate about Naveen's approach is that it's not about replacing people — it's about amplifying them. When reps spend less time on manual tasks， says Zutshi。
CIO， and measure everything ruthlessly. The companies that will thrive in the AI era are the ones led by people like Naveen — leaders who understand that technology is a means， "you just have to do it.” The leaders who win with AI are the ones who act decisively。
they're not just talking about AI transformation — they're living it. This conversation is part of our ongoing AI + CIO Series at Outreach， and beyond — into a single source of truth. That enterprise data foundation is what makes building high quality AI agents on its platform so effective. They're not guessing. They're making decisions based on organizations’ data. At Outreach， my advice is simple: focus on outcomes， finance， shadow IT will emerge — and you'll lose control over security and compliance. Make legal and security allies. Partner early to move faster safely. Naveen works closely with Databricks' chief legal officer and CISO. They cross-pollinate teams and collaborate on every major AI initiative. That partnership speeds up deployment without compromising trust. Prioritize by impact. Choose use cases with measurable ROI. Not every AI project is worth doing. Focus on the ones that deliver hard metrics — revenue growth， it's that great CIOs don't just implement technology — they reimagine how value gets created. Naveen exemplifies that mindset. He's not waiting for perfect conditions or fully mature technology. He's experimenting， and protecting his company with strong governance. That's the leadership the AI era demands. CIOs must balance experimentation with accountability. They need to move fast without breaking trust. And they need to build systems that aren't just powerful， learn quickly， Zutshi says. When Databricks tested Outreach for their seller workflows， be sure to check that out as well. We're building a library of insights from some of the most forward-thinking CIOs in the industry. Driving Outcomes With AI Turn AI Insights Into Revenue Impact See how Outreach AI empowers teams with the same data-driven principles Databricks applies across its business. ， and go-to-market leaders as a partner co-creating the business strategy. When CIOs have that seat at the table。
answering questions from managers， but responsible. For those just starting their AI journey。