An AI roadmap starts with the dependencies around the workflow
Start with the defined application
The useful unit for an AI roadmap is a single workflow, not a list of favourite models. Describe what the workflow does, the context in which it operates and what outcome is acceptable. NIST calls for documenting the intended application scope based on capability, context and categorisation. This supports assessing model tests only after the task, cost of errors and deployment boundary have been established. The passages do not compare models and therefore provide no evidence that one provider or architecture is the best choice. For each AI workflow, document the scope, owner, model and data providers, permitted actions, human oversight, compute, log location, maintenance schedule and fallback.
Make oversight and dependencies part of the design
For every workflow, document which actions a person can review or stop, which external software and data are required, and who maintains those controls. NIST calls for documented processes for human oversight and for mapping risks and benefits for all components, including third-party software and data. For systems that qualify as high risk within the scope of the cited rules, the EU regulation also mentions required computational and hardware resources, maintenance, and the ability to collect, store and interpret logs. Treat compute, logging and providers as design dependencies, not as details to address after choosing a model.
Use a decision register before you commit
Create one row per workflow with: intended application, process owner, model and data providers, permitted actions, human oversight, required compute, log location, maintenance schedule and fallback. This is not a compliance checklist, but a way to make a decision verifiable: if an owner, logging route or fallback route is missing, the production deployment has not yet been fully described. A topic-specific tool is therefore a decision register that documents the scope, owner, component dependencies, oversight, compute, logging and fallback for each AI workflow; reassess it whenever the model, tool or action authority changes.
What this framework does and does not say
The European Commission states that most current AI systems are considered minimal or no risk, while different obligations and roles may apply to high-risk systems. The passages do not classify your application or provide a complete legal assessment. This article is an editorial decision-making framework based on three supplied passages; it does not determine whether a specific workflow falls within a risk category or obligation, and it does not replace legal, technical or professional advice.
