Insights on AI augmentation
Practical guides on deploying AI across biotech and scaling companies — from executive education through ongoing operations.
How a 50-Person Biotech Competes at the Scale of a 500-Person Organization
The operating model gap between clinical-stage and large-cap biotech is real — but it's now closeable. Here's what AI augmentation actually changes about how a small team operates.
John T. Garcia · June 4, 2026
The Enrollment Problem: How AI Is Closing the Gap Between Protocol Design and Patient Recruitment
Clinical trial enrollment is the single biggest source of timeline risk for clinical-stage biotech. Here's how AI is changing the math — and what the best-run trials are doing differently.
John T. Garcia · June 4, 2026
What Is AI Augmentation? A Practical Guide for Biotech Leaders
AI augmentation enhances what your existing team can do — increasing throughput, reducing cycle times, and enabling your people to take on more without proportional headcount growth. Here's what it means in practice.
John T. Garcia · June 3, 2026
Why a Fractional AI Partner Beats Building an Internal AI Team
Building an in-house AI team costs $2.5-4M per year, takes months to hire, and carries key-person risk. A fractional AI operating partner delivers faster, cheaper, and with less risk. Here's why.
John T. Garcia · June 1, 2026
AI in Regulatory Affairs: The Strongest Augmentation Story in Biotech
Regulatory affairs and medical writing offer the highest near-term ROI for AI augmentation in biotech. First-draft CSR time drops 56%, medical-writing time falls 30-90%, and submission cycles tighten measurably.
John T. Garcia · May 28, 2026