Purpose and necessity
Use AI where it produces a meaningful benefit and define the decision or workflow it supports.
Human authority
Responsible AI is not a disclaimer attached after deployment. It is expressed through choices about purpose, information, models, authority, evaluation, transparency and what intelligent systems are permitted to do.

AFA’s existing responsible-AI principles remain the foundation, now extended to the full intelligence environment.
Use AI where it produces a meaningful benefit and define the decision or workflow it supports.
Assign clear ownership for decisions, approvals, exceptions and escalation.
Match data, knowledge and model access to the sensitivity and purpose of the workload.
Apply stronger controls as the consequences, autonomy and information sensitivity increase.
Describe systems and product maturity accurately; do not imply certainty or availability that does not exist.
Test behaviour before use and monitor material changes in models, sources, prompts and workflows.
Design experiences that can be understood and used by the people they are intended to serve.
Govern the system through design, deployment, operation, change and retirement.
Human oversight is not meaningful when a person is nominally “in the loop” but lacks the time, information or authority to intervene.
For agents and Physical AI, Operational Sovereignty adds a direct question: what is the system permitted to do without approval, and what must remain under human authority?

Document responsibilities that can survive beyond a pilot.
Define the outcome and why AI is appropriate.
Define information, tools, models and actions that are allowed.
Define evaluation, logging, provenance and documentation requirements.
Define approval, escalation, change control and who can stop the system.