Designing AI workflows with human control built in
A practical framework for placing decision rights, review gates, evidence, and recovery into an AI-assisted workflow.
Read Designing AI workflows with human control built inInsights
Insights across practice and research.
Articles and research are grouped here while remaining clearly identified by type and status.
Practical articles
From a manual process to an AI-assisted system: a practical framework
A practical framework for selecting and validating a bounded first automation opportunity.
Read From a manual process to an AI-assisted system: a practical frameworkActive research themes
Active research theme
Evaluating assisted workflows
How can a team test usefulness, failure handling, and review quality before expanding a workflow?
- evaluation
- realistic scenarios
- controlled iteration
Active research theme
Evidence and review boundaries
How can a system show enough evidence for a person to review an output or proposed action?
- evidence
- review
- traceability
Active research theme
Human-governed workflows
Where should assistance stop, review begin, and decision ownership remain explicit?
- decision rights
- approval gates
- observable actions
Active research theme
Operational context and handoffs
What context must move with work so the next person or system can act without reconstructing the process?
- context
- ownership
- handoffs
Active research theme
Recoverable automation
How should an assisted workflow stop safely, expose failure, and support a controlled next step?
- exceptions
- rollback
- recovery