Vivek Kompella On Scaling Generative AI With Trusted Data, Governance, And Business Alignment

This episode of TechDogs Discover Dialogues explores how generative AI has rapidly shifted from an experimental capability to a core enterprise function—and why data trust, governance, and leadership alignment now define whether AI initiatives succeed or stall. Nikhil Sonawane speaks with Vivek Kompella, Director of Enterprise Data & AI at Informatica, to unpack what it truly takes to scale AI responsibly while delivering measurable business impact.

Drawing on nearly two decades of experience across data engineering, analytics, and AI leadership, Vivek offers a grounded, execution-first perspective shaped by real enterprise challenges rather than theoretical ambition. The conversation reflects a reality many organizations face today: while AI tools are evolving at unprecedented speed, most enterprises struggle to move beyond pilot projects into sustained, production-grade deployments.  

From Engineering Roots To Business-Driven AI Leadership

The conversation traces Vivek’s professional journey only where it directly informs his leadership philosophy. Beginning with a background in electrical engineering and an early transition into IT at Capgemini, Vivek reflects on how mentorship and continuous learning became foundational to his career. A pivotal piece of advice early on—master data skills regardless of role—set the direction for his long-term focus on data as a strategic enterprise asset.

His move to Informatica marked a shift from purely technical execution to business-facing responsibility. Working closely with senior leadership teams early in his tenure exposed him to how data influences real business decisions, shaping his ability to translate technical outcomes into measurable value. This experience laid the groundwork for his current role, where he operates at the intersection of data, AI, and go-to-market strategy.  

Why Most Generative AI Pilots Fail To Scale

A central theme of the episode is the widespread misconception that experimentation alone leads to AI transformation. Vivek explains that while pilot projects are valuable for learning and upskilling, many never reach production due to a lack of business alignment, unclear problem definition, or insufficient data readiness.

He emphasizes that AI initiatives must begin with a clear understanding of the business decision they are meant to influence. Without alignment on objectives, success metrics, and ownership, even technically strong AI solutions fail to gain adoption. This misalignment often results in fragmented efforts, duplicated experimentation, and stalled momentum across organizations.  

Trusted Data As The Foundation For Enterprise AI

The discussion repeatedly returns to a critical enabler of scalable AI: trusted data. Vivek outlines why cloud modernization efforts that rely solely on lift-and-shift approaches fall short when organizations aim to operationalize AI. Without thoughtful architectural decisions and long-term scalability in mind, data platforms quickly become bottlenecks rather than accelerators.

Vivek strongly advocates for semantic data models as a single source of truth. He explains that centralized definitions, consistent metrics, and governed data access are not legacy concepts but essential requirements for AI-driven decision-making. Without them, organizations face conflicting KPIs, eroded trust, and an inability to scale analytics or AI initiatives across teams.  

Governance, Privacy, And Risk In The Age Of AI

As AI adoption grows, so do concerns around security, compliance, and privacy. Vivek addresses this directly, outlining governance practices that enable innovation without compromising control. Role-based access, data classification, and policy-driven governance frameworks play a critical role in ensuring that AI systems operate within defined risk boundaries.

Rather than viewing governance as a constraint, Vivek positions it as a prerequisite for scale. Enterprises that embed governance early are better equipped to deploy AI confidently, while those that delay often face resistance from legal, security, and compliance stakeholders.  

People, Culture, And The Real Bottleneck To AI Transformation

Beyond technology, the episode highlights that the true bottleneck to AI success often lies with people and organizational readiness. Vivek challenges the narrative that AI will replace jobs, instead framing it as an augmentation tool that enhances productivity and decision-making.

He emphasizes leadership’s role in shaping culture, driving upskilling, and fostering collaboration between technical teams and business stakeholders. Business translators—individuals who bridge technical complexity and business intent—emerge as critical enablers of successful AI initiatives.  

Building Sustainable AI For The Long Term

The conversation concludes with a forward-looking view on AI maturity. Vivek reinforces that sustainable AI success is not defined by model sophistication alone, but by how well data, governance, leadership, and people evolve together. Enterprises that invest in these foundations are far more likely to move beyond hype and build AI systems that deliver lasting value.

As AI continues to reshape enterprise operations, this episode offers a practical blueprint for leaders navigating the transition from experimentation to impact—grounded in experience, discipline, and strategic clarity.  

About Vivek Kompella

Vivek Kompella is the Director of Enterprise Data & AI at Informatica, where he leads the GenAI Center of Excellence and drives enterprise-wide AI and analytics strategy. In this episode, he shares why trusted data, governance, and business alignment are the real drivers of scalable AI success.