Insights
Ideas for making AI operational.
Field notes on adoption, governance, expert work, operating models, and the realities of building AI inside consequential organizations.
Direct answer
What does it take to make AI operational?
Operational AI connects a useful model to real decisions, governed data, accountable owners, review and escalation paths, adoption, and continuous improvement. HaiPhai Insights examines those operating choices with a biotech-leading perspective and links factual claims to their sources.
Where AI Can Help in Regulatory Affairs—and What Must Stay Human
Regulatory work attracts AI for an obvious reason: it contains large volumes of documents, repeated structures, distributed evidence, and intense
Fractional AI Partner or Internal Team? A Decision Framework
“Should we build an internal AI team?” sounds like a talent question. It is actually an operating-model question. The answer
What Is AI Augmentation? A Practical Guide for Biotech Leaders
“Augmentation” is often used as a polite synonym for automation. That misses the point. AI augmentation is the deliberate redesign
The Enrollment Problem: Where AI Can Improve Clinical Trial Planning
Clinical-trial enrollment is often described as a recruitment problem. By the time recruitment is visibly behind, however, the causes may
How a 50-Person Biotech Builds the Operating Leverage of a Much Larger Company
A small biotech rarely lacks ambition. It lacks slack. The same people who carry the science are also preparing board