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Accountability · Reviewed 13 August 2026

AI and professional accountability

Using AI does not transfer accountability to the model or supplier. A named person and organisation remain responsible for what is used, shared and decided.

Practice position

AI assists. People decide.

Use approved systems, minimise information, check important output and keep accountable professional judgement human-led.

Ownership must be visible

For each use, define who understands the task, approves the information, checks the output and signs off the final work. ‘The AI said’ is not an accountable rationale.

Review should be meaningful. A hurried glance at fluent text is not effective human oversight, particularly when the reviewer lacks time, evidence or authority to challenge it.

Match oversight to consequence

A spelling suggestion and a service-eligibility decision do not require the same controls. Consequential decisions affecting care, safety, liberty, employment or access to services should remain human-led and use established professional processes.

Keep an adequate record

For significant uses, record the purpose, system, information, AI contribution, verification, changes and responsible person. The record should support learning and transparency without creating unnecessary personal data.

Practical checklist

  • Name the responsible person
  • Define the human-review method
  • Keep consequential decisions human-led
  • Record significant AI assistance
  • Review incidents and model changes
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Written by Tony D’Agostino / TD Consultancy. Reviewed . This page provides general professional education, not legal or clinical advice.