From hype to clinical translation: A tiered, readiness-based framework for artificial intelligence in gastrointestinal endoscopy

Table 1 Operational criteria used for tier assignment

Domain	Tier 1	Tier 2	Tier 3
Evidence maturity	Multicenter randomized evidence or pooled randomized data with clinically meaningful endpoints and well-described downstream consequences	Prospective multicenter, pooled randomized, or strong external-validation data, but patient-level or pathway consequences remain incomplete	Single-center, retrospective, pilot, or proof-of-concept predominance
Regulatory authorization/health-system pathway	Regulatory authorization for intended use plus either supportive or permissive practice-facing guidance (i.e., recommending in favour of or conditionally allowing the technology) or a structured evidence-generation pathway	Partial regulatory or health-system traction, pilot implementation, or pathway-facing evaluation, but convergence not yet present	No meaningful regulatory traction or practice-facing pathway
Real-world deployment	Use beyond expert development centers, including community or non-academic settings	Limited or early real-world implementation	No meaningful real-world deployment evidence
Workflow actionability	Clear clinical action path with feasible real-time integration into procedural workflow	Action path plausible but not standardized	Action path unclear, procedure-specific, or not yet clinically testable
Governance/monitoring	Explicit oversight with named metrics, update disclosure, override logging, and evidence-generation or post-market monitoring	Published protocol or institutional plan specifies some governance elements, but lifecycle monitoring remains incomplete	Governance largely undefined
Generalizability/resource fit	Evidence across heterogeneous populations, platforms, or settings, with plausible operational fit outside expert centers	Some external validation, but geographic or vendor concentration remains substantial	Narrow setting, platform, or population dependence