Research Administrator
Coordinate IRB, IACUC, and other research compliance reviews
What You Do Today
Support researchers through institutional compliance review processes — human subjects (IRB), animal care (IACUC), biosafety, and export controls. Ensure protocols are approved before research begins.
AI That Applies
AI pre-screens protocols against common deficiencies, suggests standard language for routine procedures, and tracks protocol approval timelines and renewal deadlines.
Technologies
How It Works
The system ingests protocol approval timelines and renewal deadlines as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The results integrate into the practitioner's existing workflow — presenting recommendations, flags, or automated outputs alongside their normal working context.
What Changes
Protocol preparation becomes faster with fewer rounds of revision. AI catches common issues before reviewers see them.
What Stays
Helping researchers understand why compliance matters — not just jumping through hoops — and navigating truly complex ethical questions requires human expertise and sensitivity.
What To Do Next
This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.
Establish Your Baseline
Know where you are before you move
Before adopting AI tools for coordinate irb, iacuc, and other research compliance reviews, understand your current state.
Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.
Define Your Measures
What to track and how to calculate it
Time per cycle
How to calculate
Measure how long coordinate irb, iacuc, and other research compliance reviews takes end-to-end today, then after AI adoption.
Why it matters
The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.
Quality of output
How to calculate
Track error rates, rework frequency, or stakeholder satisfaction scores before and after.
Why it matters
Speed without quality is just faster mistakes. Measure both.
Start These Conversations
Who to talk to and what to ask
your VP Operations or COO
“What's the risk if we DON'T adopt AI for coordinate irb, iacuc, and other research compliance reviews — are competitors already doing this?”
They're prioritizing which operational processes to automate
your process improvement or lean lead
“What would a pilot look like for AI in coordinate irb, iacuc, and other research compliance reviews — smallest possible test that would tell us something?”
They understand the workflow dependencies that AI tools need to respect
Check Your Prerequisites
Confirm readiness before you invest
Check items as you confirm them.