The conversation reveals that while LLMs are rapidly becoming commoditized, sustainable advantage lies in proprietary data, tailored workflows, and deep integration into business processes. The panel highlights transformative use cases at RBC, Merck, and 7-Eleven, where AI drives efficiency by automating reports, accelerating drug discovery, and streamlining marketing. They stress that AI is not a shortcut—like RPA before it, success requires engineering effort and organizational change. CIOs are advised to experiment with flexible tools, avoid overcommitting to costly infrastructure, and focus on applications that deliver measurable value. The economic model for AI demands significant revenue to justify current CapEx levels, pointing to a shift in value from models to apps and data layers. The future belongs to agentic systems that learn in real time, particularly voice-driven interfaces and personal AI assistants like Glean, which aim to democratize productivity across enterprises. True progress, they argue, isn't about achieving AGI but deploying intelligent systems that create tangible business outcomes.