Leadership in the AI Age: Why Judgment Still Matters in Healthcare Design

Erica Irvin, MBA, RID, NCIDQ, LEED AP, CQM-C

Artificial intelligence is reshaping how we work, particularly in healthcare design, where tools like Otter, CoPilot and ChatGPT accelerate documentation, analysis, and coordination. These efficiencies are real and increasingly necessary amid growing complexity and accountability. However, as AI becomes embedded in daily workflows, the role of leadership becomes more—not less—critical. AI excels at speed and pattern recognition, not intent, judgment, or accountability. Treating it as an assistive capability rather than a source of certainty keeps design decisions grounded, responsible, and aligned with the realities of patient safety, clinical outcomes, compliance, and long‑term operations. AI can assist the work, but it cannot lead it.

AI excels at clarity, organization, and pattern recognition. Meeting capture tools, for example, can record conversations with completeness, summarize themes, and surface action items quickly. Yet leadership is required to interpret what isn’t explicitly said—the hesitation in a client’s voice, the political nuance of a deferred decision, or the risks that should not yet be documented. AI may draft the record. Leaders ensure it reflects intent, context, and responsibility. AI creates clarity; leaders create meaning.

One example such example at Apogee where this distinction becomes especially important occurs when reviewing construction RFIs and submittals. AI can analyze volume, identify patterns, flag missing information, and even help draft potential responses. That speed reduces cognitive load and helps teams focus. But judgment still belongs to people. Experienced leaders must decide whether a response introduces contractual risk, impacts scope, schedule, or cost, or requires escalation for owner approval. In healthcare environments where a single decision can ripple into patient flow disruptions or operational inefficiencies this judgment is not optional. AI accelerates analysis. Leadership governs risk.

Another example of use of AI is to assist in creating clear, accurate project scope summaries by reviewing and synthesizing the full body of project documentation from drawings and specifications to narratives and working files. By identifying consistent themes, deliverables, and constraints across sources, AI helps distill complex work into marketing‑ready language. This enables teams to communicate with greater speed and alignment, while designers retain oversight to ensure accuracy, intent, and positioning.

AI can help draft clear emails, summarize complex issues for executives, and structure punch lists or risk logs from site observations. These capabilities are valuable, particularly when projects are high‑stakes and timelines are compressed. But AI does not understand relationships, history, or political context. It cannot determine what is truly urgent, what is acceptable, or what must be escalated. Only leaders can prioritize with intention and that prioritization carries real‑world consequences in healthcare environments.

AI is becoming an indispensable accelerator in healthcare design. It helps us move faster, see patterns sooner, and reduce administrative burden. But speed without judgment creates risk.

At Apogee, we see AI as a tool that supports our people, not a substitute for leadership. When integrated thoughtfully, it allows our teams to focus on what matters most: ethical decision‑making, accountability, and patient‑centered outcomes. In the end, AI is a tool. Leadership is the differentiator.

The design firms that will thrive in the AI age will not be those that automate the most but those that lead the best.

Effective leadership ensures AI serves design values, not replaces them, by setting boundaries, maintaining authorship, and prioritizing ethical and experiential outcomes.