What happens when a CTO and a CIO of a global tech company sit down together to talk about AI? That’s the starting point of today’s episode, where I’m joined by Jeremy Ung, CTO at Blackline, and Sumit Johar, the company’s CIO. Rather than chasing the hype, we focus on what AI really means for executive decision making, governance, and business outcomes. Both leaders open up about how their partnership is blurring the traditional lines between product and IT, and why the board is demanding answers on topics that once sat deep in the technology stack.

Jeremy and Sumit explain why AI is not just another SaaS subscription and why expectations have changed so dramatically. For decades, technology was seen as predictable, a rules-based engine that followed instructions without error. AI feels different because it speaks, reasons, and sometimes makes mistakes. That human-like experience is what excites employees, but it is also what unsettles them. This is where education and governance come in, helping teams learn how to question, verify, and trace AI outputs before they make critical decisions. We also explore how AI agents are beginning to work across tools like SharePoint and email, raising new compliance and security questions that CIOs and CTOs must answer together.

The conversation turns to AI sprawl, a problem that mirrors the SaaS explosion of a decade ago. With new AI tools emerging every week, enterprises risk overlapping investments and fragmented initiatives. Sumit shares how Blackline uses two governance councils to keep projects aligned. One is dedicated to risk, pulling in voices from legal, security, and privacy. The other is focused on transformation, evaluating whether requests for new AI capabilities make sense, or whether they duplicate what already exists. The signal that sprawl is taking root, he says, is when requests for tools suddenly jump from a few each month to a dozen.

We also tackle the build versus buy dilemma. Budgets haven’t magically increased just because AI is hot. Jeremy argues that building only makes sense when it reinforces a company’s core advantage. Everything else should be bought, integrated, and kept flexible so that organizations can pivot as the AI landscape changes. Both leaders stress that trust, auditability, and value delivery must sit at the center of every investment decision.