The Obelisk: A New AI–Human Efficiency Model

A recent Harvard Business Review article caught my attention for how clearly it articulated a shift I’ve been watching unfold for years: artificial intelligence is not just changing consulting—it’s reshaping the very structure of knowledge-based work.

The conversation around AI often swings between two extremes. On one end is the fear that AI will replace professionals altogether. On the other is the belief that it will simply make us more indispensable. Having observed this evolution firsthand over the past decade—particularly in radiology and healthcare AI—I believe the truth lies somewhere in between. Our roles aren’t disappearing; they are being fundamentally redefined.

For decades, consulting operated on a classic pyramid model: a wide base of junior analysts conducting research, building models, and preparing materials, all in support of a small group of senior leaders who synthesized insights and guided decision-making. This structure worked because human labor was the limiting factor.

AI is now rapidly automating much of that foundational layer. Research, analysis, synthesis, and even presentation development—once the domain of large junior teams—can increasingly be handled by intelligent systems. Tools such as McKinsey’s Lilli, BCG’s Deckster, and Bain’s Sage are enabling firms to complete in days what once took weeks of coordinated effort across multiple teams.

The result is a new organizational structure the article describes as the Obelisk Model: smaller, more senior teams augmented by AI, operating with greater speed, precision, and leverage. Instead of scaling through headcount, organizations scale through intelligence—human and machine working together.

Importantly, this shift is not limited to consulting. In my view, every industry will need to build its own version of an obelisk. This is especially true in digital health and regulated product organizations, where complexity is high and the cost of error is significant. In FDA-regulated environments, AI can help teams navigate dense regulatory landscapes, synthesize vast bodies of predicate and clinical knowledge, and accelerate insight generation—while maintaining rigor, quality, and compliance.

At the same time, AI cannot replace the full spectrum of human intelligence. Complex decision-making—particularly in healthcare—requires judgment, intuition, ethical reasoning, and an understanding of the emotional dimensions that shape patient and clinician choices. AI excels at efficiency: removing repetitive tasks, processing large datasets, and supporting routine decisions. But the most consequential decisions will continue to require human insight and accountability.

What excites me most about the Obelisk Model is not efficiency alone, but elevation. The real opportunity lies in balance. AI is most powerful not when it replaces human intelligence, but when it amplifies it. When optimization is paired with excellence, teams don’t just move faster—they think more clearly, ask better questions, and focus their energy where it matters most.

This is the mindset I’m bringing into my own work and the teams I support: building high-leverage structures that combine human judgment, deep domain expertise, and machine precision to deliver meaningful, real-world impact.

The future isn’t human or AI—it’s human with AI. The organizations that win won’t be the largest, but the most intelligent: lean, experienced teams empowered by technology and guided by human judgment. That is the promise of the Obelisk Model.