There is a massive graveyard of enterprise artificial intelligence pilots that looked great in a demo but never made it to actual users.

Why is the transition from the research lab to enterprise production so difficult?

In Episode 4 of Enterprise Decoded, host Anji Maram sits down with Elizabeth Lingg, Director of Applied Research at Thomson Reuters Labs, and Garima Agarwal, Chief Technology Officer at Meeru AI.

Together, they break down the brutal realities of deploying generative models in high stakes business environments.

Listeners will discover why building for the enterprise means building for edge cases rather than average cases. The guests share their deep experience in the field, explaining how engineering discipline determines the floor of your success, while research only determines the ceiling.

You will also learn about the Three Gs framework for enterprise readiness. We discuss how to ensure your data is Grounded, how to keep your outputs Governed and auditable, and how to use a Graduated approach to build deep trust with your most skeptical end users.

Whether you are a Chief Information Officer, a software engineer, or a business leader trying to navigate the hype, this conversation provides a roadmap for building durable and verifiable systems that drive real business growth.

Listen now to learn how to stop building fragile pilots and start building resilient enterprise platforms.

Is your organization genuinely transforming with artificial intelligence, or are you just accumulating technical debt with better branding?

In this episode of Enterprise Decoded, host Anji Maram is joined by semiconductor industry veteran and CIO Steve Nott to challenge the current enterprise AI playbook. Together, they break down why short-sighted tool proliferation leads to organized fragmentation, and how a security-first approach actually unlocks sustainable velocity.

What we discuss in this episode:

• AI-Native vs. AI-Adopted: The critical structural shift organizations must make to compound intelligence over time.

• The Hidden Pitfalls: Why isolated department tools invite severe data exposure, vendor lock-in, and retroactive compliance nightmares.

• The 5-Part CIO Blueprint: Actionable architecture, governance, and talent strategies for decade-long market dominance.

Resources Mentioned:

• McKinsey Global Institute: The State of AI
  

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Welcome to Enterprise Decoded, a podcast about the systems we build and the people those systems are built for. Hosted by Anji Maram, we bypass the buzzwords to explore AI, platforms, and automation through grounded, empathetic leadership.

In Episode 2, we are joined by Raju Reddy to tackle a foundational challenge in an AI-first world: engineering trust. Trust can no longer be relegated to a marketing slogan; it must be a deliberate design, architectural, and product decision.

Listen in as we navigate our signature format to uncover the realities of modern enterprise technology:🔹 The Good: What’s actually working when building trusted systems.🔹 The Bad: The broken processes and blind spots holding us back.🔹 The Ugly: The uncomfortable realities leaders must face head-on.

Produced by CriticalRiver.

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We’re live! Enterprise Decoded Episode 1 is here.

After many conversations, debates, and real-world lessons from the field, I’m excited to kick off this podcast series.

Episode 1: Why Intent Matters in an AI-First World

With the brilliant Dr. Vijay Gurbaxani

In a world rushing to become “AI-first,” we paused to ask a more important question:

Are we building with intent? Or just building fast?

In this episode, we unpack:

• Why AI is not just automation, it’s decision-making at scale What “AI-first” actually means (beyond the buzzword)
• A practical 4-part framework for leaders navigating AI adoption
• Why most AI pilots fail and how to fix it
• And the big one: why how you build matters as much as what you build

One line that stayed with me:“Trust isn’t marketed. It’s engineered.”

This is the first of many honest, structured, and no-hype conversations on AI, platforms, and enterprise transformation.

If you’re a CIO, CTO, product leader, or just someone trying to make sense of AI beyond the noise, this one’s for you.