Verification, Validation & Evidence for AI
What does “validated” actually mean?
AI has brought engineering, software assurance, clinical science, human factors, regulation, healthcare operations, cybersecurity, and institutional governance into the same decision environment. These disciplines do not always mean the same thing when they use words such as verification, validation, and evidence.
“Validated” is not a complete claim.
A trustworthy validation claim identifies what was evaluated, against what requirements or evidence, for which intended use and context, by whom, and whether that determination remains applicable after material change.
What does “validated” mean for AI?
One word decomposes into at least six distinct questions, each with its own evidence and its own accountable authority.
Independent verification is an additional layer of confidence, separate from the six questions above. See TTIC’s work on behavioral verification.
These are not six TTIC programs. They are different questions, and most of them belong to other professional authorities.
What is the difference between verification and validation?
Verification asks whether a system was built and configured correctly. Validation asks whether it performs, and produces the intended benefit, for its intended use.
Verification and validation emerged from multiple professional traditions with different objectives, evidence standards, and authorities. Engineering asks whether systems meet requirements. Clinical science asks whether evidence supports safe and effective use for particular purposes and populations. Human factors examines interaction between people and technology. Regulators evaluate requirements within their jurisdiction. Healthcare institutions must determine whether a technology should be used within their own environment and under what conditions.
AI increasingly causes these questions to collide.
TTIC grew from a synthesis of a Taylor & Francis book series with a spinout of the IEEE/UL 2933 working group, which gave it a strong technical foundation.
It is not only a strong technical foundation. TTIC is also informed by continuous clinical oversight, including a cutting-edge editorial policy based on the ACCME model and reviewed by R1 research institutions, built to bridge the divide between technology and medicine for the age of AI.
As healthcare AI has evolved, it has become increasingly important to identify where technical assurance ends and clinical, scientific, regulatory, operational, and institutional authority begins.
TTIC’s response is not to assume all of these authorities. It is to make their boundaries and relationships understandable.
Different questions. Different authorities.
Three territories, held at equal weight. TTIC does not sit above the other two.
- Technical verification
- Technical validation
- Technical assurance
- TIPPSS security assurance
- Privacy technical controls
- Safety technical assurance
- Reliability / resilience
- AI / agent behavioral verification
- Technical monitoring and reassessment
- Clinical validation
- Human factors / usability (conditional)
- Analytical validation
- Operational / workflow validation
- Local / institutional validation
- Clinical science
- Clinical trials
- Regulatory determinations
- Legal determinations
- Conformity assessment
- Deployment authorization
- Specialty professional standards
TTIC may develop substantive resources in its core scope. In boundary areas, TTIC provides definition, distinction, and routing, not methodology. Outside TTIC scope, TTIC references the appropriate authority rather than recreating its work.
Who is responsible for clinical validation of AI?
Appropriately qualified clinical, research, regulatory, and institutional authorities, not TTIC.
Technical and TIPPSS assurance can be mistaken for evidence of clinical validity. They are not. Clinical validation belongs to qualified clinical, research, regulatory, and institutional authorities.
Where the interface sits.
One or two sentences each. Not a methodology, a routing statement.
Where a specific human-technology interaction affects a TIPPSS property, TTIC identifies the interface. Human factors and usability validation belong to qualified human factors professionals and, for regulated products, the applicable regulator.
TTIC technical assurance does not establish analytical validity. That belongs to the relevant scientific discipline and, for regulated products, the applicable regulator.
TTIC technical assurance does not establish that a technology works within a particular organization’s workflow. That determination belongs to the organization accountable for the workflow.
TIPPSS and technical assurance are not deployment authorization. The deploying institution owns that determination.
TIPPSS and TTIC technical assurance are not regulatory approval or legally recognized conformity assessment. Those belong to applicable regulators and recognized conformity-assessment bodies.
What is the difference between technical and clinical validation?
Technical validation confirms a system performs to specification. Clinical validation confirms adequate evidence exists for a specific clinical use. Neither substitutes for the other.
- Requirements
- Performance
- Reliability
- Security
- System behavior
- Intended use
- Population
- Clinical setting
- Clinical performance
- Safety
- Human interaction
- Clinical utility / outcomes where applicable
Evidence does not authorize itself.
Evidence can inform a determination. Someone with appropriate authority remains accountable for the determination.
Authority remains accountable.
Evidence can inform a determination. Someone with appropriate authority remains accountable for the determination.
Validated does not automatically mean deployed. The step from determination to deployment is a separate decision, made under conditions, monitored, and subject to reassessment. It is not an automatic progression.
Does validation expire when an AI system changes?
A validation conclusion may depend on assumptions that can change. Material change may require reassessment, but not every change requires complete revalidation.
Material change may require reassessment. The appropriate response depends on the change, the risk, applicable requirements, and the accountable authority. Not every change requires complete revalidation.
“Validated” is not a complete claim.
What should healthcare leaders ask when an AI system is described as validated?
Ten questions, in order, that turn “is it validated?” into a question with a real answer.
- What exactly was validated?
- Against which requirements, comparator, or evidence standard?
- What version of the system was evaluated?
- What was the intended use?
- Which population and environment were represented?
- Who generated the evidence?
- Who independently verified relevant claims, if applicable?
- Who had authority to make the resulting determination?
- What limitations or conditions accompanied it?
- What changes would require reassessment?
What TTIC does. And what it does not.
TTIC does not provide clinical validation, clinical trials, regulatory approval, clinical implementation, workforce training, or organizational change management. TTIC’s certification pathway, currently in early access, combines behavioral verification with TIPPSS governance screening; certification is issued through TTIC’s governance review. It is not a determination of clinical validity or clinical effectiveness for any clinical use.
TTIC does not perform or certify clinical validation. It clarifies how clinical validation relates to technical assurance, governance, and institutional accountability and directs practitioners to appropriate clinical, scientific, and regulatory authorities.
With thanks
This page reflects a prior conversation within the IEEE/UL 2933 working group. Sherri Douville developed it together with Dr. Art Douville, Dr. Apurv Gupta, and Mitch Parker, Vice Chair, IEEE/UL 2933. TTIC also recognizes Dr. Douville and Dr. Gupta for their continued commitment to clinical validation and patient safety.
Related TTIC resources
- FDA / IMDRF Good Machine Learning PracticeExternal
- FDA: AI-Enabled Medical DevicesExternal
- DECIDE-AIExternal
- SPIRIT-AIExternal
- CONSORT-AIExternal
- TRIPOD+AIExternal
- AMIAExternal
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- Published by
- Trustworthy Technology & Innovation Consortium (TTIC)
- Author
- By Sherri Douville, Founder & Chair, Trustworthy Technology & Innovation Consortium (TTIC)
- Originally published
- Last updated
Provenance: This resource is an original practitioner architecture from the Trustworthy Technology & Innovation Consortium (TTIC), developed to operationalize healthcare AI governance standards into institutional practice. External standards and source materials are cited separately.
Cite this resource
Sherri Douville. “Verification, Validation & Evidence for AI.” Trustworthy Technology & Innovation Consortium (TTIC), 2026. https://trustworthytechnologyinnovation.com/verification-validation-evidence/.