83: Using AI to Scale Marketing and Revenue Teams with Patrick Leung

Faro Health is leveraging generative AI to overhaul the most expensive phase of drug development—clinical trial design. By applying large language models at the conception stage, the company can generate protocol drafts in minutes instead of weeks, a speedup that translates into tangible cost reductions. Their collaboration with Merck demonstrated that strategic design tweaks, informed by AI, can shave off up to $100 million from a trial’s downstream budget, directly challenging the upward‑spiraling trend described by Eroom's Law, which predicts drug‑development costs doubling every nine years.

Internally, Faro Health has turned AI into a productivity engine across the organization. Engineers use AI‑assisted coding to prototype features, write unit tests, and integrate new APIs in record time, while QA and DevOps teams automate test generation and infrastructure‑as‑code scripts. Non‑technical staff—UX designers, salespeople, and researchers—benefit from multimodal models that draft presentations, conduct market research, and even create visual assets. This company‑wide adoption illustrates how generative AI can compress cycles, free talent for higher‑value work, and create a competitive edge in a tightly regulated industry.

Beyond pharma, Patrick Leung warns against overhyping AI as imminent AGI. He cites limitations in logical reasoning—such as failing simple puzzles like Towers of Hanoi—and stresses that current models are sophisticated autocomplete systems, not truly creative problem solvers. Hiring AI‑fluent talent remains a bottleneck; resumes alone don’t guarantee competence, so Faro Health relies on rigorous coding assessments. For business leaders, the message is clear: adopt AI now, invest in real skill development, and use the technology to streamline core processes before competitors do.