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AI in Regulated Research Readiness

AI Readiness Scorecard for Regulated Research

Score how ready your organization is to adopt AI in a regulated environment without breaking data integrity, 21 CFR Part 11, or GxP.

AI in Regulated Research Readiness - scorecard for adopting AI under FDA and GxP rigor

Walk away with a concrete, actionable implementation plan.

General guidance for educational purposes only — not legal, regulatory, or compliance advice. Review results with qualified professionals.

centrexIT AI in Regulated Research Readiness

In June 2025, the FDA published a paper on embedding cybersecurity into advanced medical-product manufacturing technologies — a signal that adopting AI in regulated research now carries the same scrutiny as the systems around it. This scorecard estimates how ready your organization is to adopt AI without breaking data integrity, 21 CFR Part 11, or GxP.

1. AI Inventory & Shadow AI

0 / 6
You know which AI and LLM tools your staff actually use
Including browser extensions and personal accounts, not just sanctioned platforms
An approved-tool list exists and is communicated to staff
A clear list of which AI tools are permitted for regulated work
Unsanctioned AI use is actively monitored and addressed
Ongoing visibility into shadow AI, not a one-time policy memo

2. Access Control & Data Governance for AI

0 / 4
You control which regulated or research data can be fed into AI tools
Technical restrictions such as DLP, not guidance alone
Sensitive datasets are classified before anyone uses AI on them
IP, genomic, clinical, and PHI data identified and labeled

3. Data Integrity / ALCOA+

0 / 6
AI-assisted records are attributable and contemporaneous
Tied to a person and a time, consistent with ALCOA+
AI-touched records carry a complete audit trail
Every AI contribution is logged and reviewable
You can distinguish AI-generated data from human-generated data
Provenance is recorded, not assumed

4. 21 CFR Part 11

0 / 4
E-record controls extend to AI-touched workflows and outputs
Part 11 record requirements apply wherever AI participates
E-signature controls cover AI-assisted approvals and outputs
Signing meaning and record integrity preserved where AI is involved

5. Validation (CSA / CSV)

0 / 4
AI tools are validated like other GxP systems
CSA or CSV applied to AI based on risk and intended use
AI tools are under formal change control
Model and configuration changes are assessed and approved

6. Human Oversight & Output Review

0 / 4
Review of AI outputs is mandatory before they affect regulated work
A named person is accountable for what AI produces
Reviewers are equipped to detect falsified or fabricated data
Including AI-generated deception such as falsified lab results

7. Vendor & Model Governance

0 / 4
Third-party AI vendors are vetted for security
SOC 2 or ISO 27001 evidence and contractual data terms
AI models and versions are tracked and controlled
You know which model and version produced a given output

Rate all 16 criteria to see your score

Estimates for planning purposes only; not legal, compliance, tax, or financial advice. centrexIT — managed IT and cybersecurity since 2002.

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