SmartSuite for the Model Owner

Each model you own sits in the inventory with its use case, status, deployment context and governance requirements, linked to the business processes, applications and datasets it relies on, so nobody has to ask you what it does.

Standardized assessment methodologies apply consistent risk and performance evaluation across drift, bias, security, safety, privacy and data quality, so the assessment you complete is the one the Model Validator expects to see, in the format they review.

Recurring monitoring cycles schedule re-assessments and route them to you with the metrics and thresholds already defined, so ongoing monitoring is a task on your list rather than a question at the next governance meeting.

Performance and risk metrics are tracked against approved indicators and thresholds, so when a model drifts the follow-up action is raised automatically and the AI Governance Lead sees the breach at the same time you do.

Approval, conditional approval, exception and suspend-or-retire decisions run through a workflow with full traceability, so the conditions the Model Validator attaches are recorded against your model, not buried in an email.

Connected model context links your model to the datasets the Data Governance Analyst stewards and the product the Product Manager owns, so a data change or a feature change shows which models it touches before it ships.

Model documentation, testing artifacts, supporting evidence and review logs are stored centrally against the model, so re-validation starts from the file you have been maintaining rather than from a request for everything again.

Audit trails and version history record who changed what, when and why, so the change log the AI Governance Lead asks for before re-validation is the record itself and a re-validation trigger is never missed.

Framework and regulatory alignment links your model and its assessments to the laws, policies and frameworks that apply, so a deployer obligation under the EU AI Act or a CRI AI RMF requirement is visible on the model, not discovered at audit.

A Model Owner is accountable for the AI models assigned to them: registering and maintaining each model in the inventory, completing the required risk and performance assessments, maintaining the documentation, status and change records, tracking and closing issues raised against the model with evidence, monitoring performance and escalating degradation, and preparing the model for periodic review and re-validation. They are the first line for the models their business uses, as the agencies' 2026 model risk guidance (SR 26-2) and the EU AI Act's deployer obligations expect.

AI Governance gives model owners a structured workflow for assessments, documentation and ongoing monitoring through a model registry and assessment templates. Each model has a registry entry, the required assessments are templates rather than blank documents, and the documentation, status and change records sit on the model. CRI AI RMF supplies the assessment structure for organizations following that profile. The Model Validator reviews from the same record, so the owner is not assembling a pack for them.

Issues raised against a model are tracked and closed in Issues Management with evidence and task routing, so a finding from validation or a monitoring alert becomes a task with an owner and a date, and closure requires the evidence that it was fixed. The Model Owner can see every open issue across their models, and the AI Governance Lead and Model Validator see the same list when deciding whether approval conditions have been met.

SmartSuite maintains status, changes and review readiness visible to governance, so the Chief Data and AI Officer and the AI Governance Lead see each model's current status, the changes recorded against it and whether it is ready for its periodic review without asking the owner for an update. The Model Owner keeps the record current as part of operating the model, and that record is the model inventory regulators treat as the evidence of ownership.

Getting started is a matter of registering the assigned models with their intended use, status and documentation, then completing the first assessment from the template. New customers can start with SmartSuite Onboarding, a guided four-week program around one or two priority workflows. The Data Governance Analyst and Product Manager who know the data and the use case contribute to the same record, and once the first review cycle has run the model carries its history, which is what makes the next re-validation a review rather than a reconstruction.