Choose an interchangeable model route for each AI workflow
The roadmap choice: design the workflow, not the vendor
Choose a separate, interchangeable model route for every AI workflow. That does not mean every team must run multiple models today. It does mean that prompts, test cases, logging, security checks and acceptance criteria should remain outside a single vendor interface. First define what the workflow must deliver: the minimum quality, permitted data, maximum turnaround time, owner and the threshold at which a human takes over. Only then choose which model performs that task. This sequence aligns with the scope of NIST: the AI RMF Core describes activities for managing AI risks and developing trustworthy systems, organized into govern, map, measure and manage. The source does not prescribe a specific model architecture or fallback. The translation into a model-agnostic roadmap is therefore an editorial recommendation: make the dependency visible and testable for each workflow.
Make model selection a testable acceptance decision
A model is suitable for a workflow only if it meets the predetermined acceptance level. Make that concrete with a small, fixed set of representative tasks and assess, for example, completeness, error type, required human review, processing time and the permitted data route. Repeat the same assessment whenever a model version, price, access condition or interface changes. That way, a release does not become a reason to migrate based on intuition. The European Commission describes proportionate obligations for GPAI models, including documentation and information for downstream providers; for models with systemic risk, it mentions risk management, monitoring of serious incidents and model evaluations, among other things. This is a regulatory framework for the relevant roles and models, not a general obligation for every AI workflow. For product teams, however, it is a useful reason not to treat documentation and evaluation as an afterthought.
Decision register for a single workflow
Use this decision register for one existing workflow: record the workflow, minimum quality, permitted data, selected model route, alternative, owner, evaluation set, log location, security check, acceptance threshold and review date. Decide that a route is production-ready only once the evaluation set and data boundary have been completed; when rejecting it, record which alternative or human step follows. Start with the workflow for which delay, a model change or an unclear data route has the greatest operational impact. This creates a concrete comparison between the primary and alternative route, without assuming that an open-weight or second frontier model is inherently better, cheaper or safer. The European Commission states that providers of GPAI models must make technical documentation available to downstream providers; its practical usefulness depends on the workflow and on what an organization can verify itself.
What this approach does not solve
This approach does not automatically reduce dependency on a supplier: an alternative may also bring different quality, management overhead, contractual terms or security risks. The supplied passages do not support statements about current model access, prices, latency, vendor terms or the performance of open-weight models. Check these points for each specific supplier and workflow before planning a migration. This article does not provide legal, financial or professional advice; assess applicable obligations, contracts and data processing with the designated experts.
