Gartner’s recent AI Technology Sandwich framework (Just Below) offers a useful metaphor for understanding how organizations can build, run, and scale artificial intelligence (Gartner, 2024). At first glance, the model looks deceptively simple: layers of infrastructure, platforms, applications, and governance. But as with any good sandwich, the order and balance of the ingredients matter.
The top and bottom layers are data. “Data everywhere and every kind” on the decentralized end and “Data centralized” on the other represent the dual reality of modern AI: the need for diverse, distributed sources while still requiring structured, governed repositories. Without data—clean, trusted, and available—no AI initiative will scale beyond pilot experiments (McKinsey & Company, 2024).
The middle layers are where execution happens. Gartner divides these into Build (infrastructure, platforms, and built/blended AI models) and Run (embedded AI, bring-your-own AI, and operational integration). This distinction is critical: building AI is not the same as running AI at scale. Too often, organizations conflate the two, pouring resources into proof-of-concept models without establishing the operational backbone to sustain them (MIT Sloan Management Review, 2023).
But perhaps the most important slice of this sandwich is trust. Gartner wisely highlights that trust is not simply a technical safeguard—it spans human governance (committees, communities of practice, oversight teams) and tech-driven security (risk management, safety, compliance). Trust is the ingredient that makes the sandwich edible. Without it, even the best-built AI platforms risk rejection by employees, customers, or regulators (Boston Consulting Group, 2023).
Three Key Takeaways for Executives
- AI Success Starts with Data Discipline
The sandwich reminds us that no AI initiative succeeds without data as the foundation. Executives must invest in both centralized repositories for governance and decentralized pipelines for agility. This dual approach supports compliance while enabling innovation. - Building AI ≠ Running AI
Organizations often underestimate the operational lift required after pilots. Moving from build to run requires embedding AI into products, operations, and decision-making. Executives should demand roadmaps that extend beyond experimentation to full integration. - Trust Is the Non-Negotiable Layer
AI that lacks governance, risk management, and human oversight will not scale. Trust is not a “compliance checkbox”—it’s a strategic differentiator. Leaders who invest in transparent governance and security will see higher adoption and better outcomes.
Final Thought
In short, Gartner’s AI Technology Sandwich isn’t just about technology; it’s about the organizational leadership and the design required to make AI trustworthy, scalable, and impactful. For executives, the message is clear: don’t just focus on tools. Focus on data discipline, operational integration, and trust. Those are the real ingredients of AI success.
References
- Boston Consulting Group. (2023). From Experimentation to Impact: Why Generative AI Pilots Fail.
- Gartner. (2024). AI Technology Sandwich: A Conceptual Framework for Executing AI.
- McKinsey & Company. (2024). The State of AI in 2024: Charting a Path to Value.
- MIT Sloan Management Review. (2023). Implementing AI: From Principles to Practice.