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Building the AI-Ready Enterprise: Leaders Share Real-World AI Solutions and Practices

Part One of Three: Leading the AI-Ready Enterprise: Insights from our Executive Roundtable

Building the AI-Ready Enterprise: Leaders Share Real-World AI Solutions and Practices

Published: December 4, 2025

Data Leader2 min read

Summary

  • Industry leaders from finance, pharma, media, and CPG share candid insights on moving from AI pilots to production, balancing governance with innovation, and managing cost.
  • Enterprises that are finding success with agentic AI in production are breaking down workflows into clear tasks and laying the foundation for agents to scale responsibly across the business.
  • Focus on outcomes over labels, prioritize measurable impact, align organizations around AI as a product, and act with urgency to scale what works.

AI adoption is progressing at a faster pace than any previous technology cycle, and every executive is under pressure to get it right. Whether you lead in finance, pharma, media, CPG, or tech, the challenges are the same: How do we move beyond AI pilots to production? How do we balance data governance with AI innovation? How do we control costs without slowing adoption? Leaders who solve these challenges today will gain a competitive edge.

Six senior leaders from top global brands, including Danone, Capital One, Warner Bros. Discovery, and Gilead Sciences, joined us for a candid conversation about how AI is reshaping the way they operate, compete, and make decisions

Watch this roundtable to hear these leaders discuss actionable strategies and AI agent use cases you can apply within your own organization. They explore how to break complex workflows into agentic tasks, create a responsible AI Committee, and transform AI pilots into scalable business results.

Their conversation distilled five insights every executive can apply to scale AI responsibly and realize its full business potential.

  1. Move Beyond AI Labels: Build an Outcome-Focused Strategy
    Don’t be distracted by labels like “AI-powered” or “data-driven.” Measure AI by the outcomes it delivers: faster insights, better decisions, and tangible business value.
  2. Prioritize Measurable Impact of AI Projects
    Shift the focus away from academic debates about AGI or “what’s next” and double down on where AI is already driving measurable progress.
  3. Build the Foundation for Agentic AI Now
    Lay the groundwork for agentic AI now by investing in high-quality data orchestration tools and strong governance. Organizations that delay will fall behind as adoption accelerates.
  4. Align Your Organization Around AI as a Product
    Treat AI as something you intentionally build for by aligning data, engineering, and business teams so AI becomes a core driver of strategy, not a side project.
  5. Act with Urgency: Scale What Is Working
    Identify high-performing use cases now and scale them quickly to capture value.

Watch the video to catch the full discussion and learn how today’s leaders are scaling AI agents, building governance frameworks, and driving measurable impact.

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