Workforce archetypes

Executive summary

This report presents 5 descriptions of workforce archetypes based on the interviews conducted as part of this research.

Interviewees for this research described various roles and responsibilities that relate to how artificial intelligence (AI) technologies are developed, implemented and used in health settings. Following an analysis of these descriptions, this report presents 5 groupings, referred to as archetypes, as detailed in Figure A.

The 5 archetypes include:

  • Shapers
  • Drivers
  • Creators
  • Embedders
  • Users

Individuals acting as each archetype will have different knowledge and skills requirements to confidently develop, implement or use AI technologies, and hence specific educational needs.

The archetypes do not necessarily align with traditional professional groups (for example, doctors, nurses, allied health professionals), specialisms or levels of seniority, but depend solely on an individuals’ role in the development, implementation and use of AI technologies.

Although most healthcare workers will have responsibilities associated with one archetype, the archetypes are not mutually exclusive. For example, a clinician could be involved in co-creating AI technologies (as a Creator), validating AI technologies procured for use within their setting (as an Embedder) and undertaking clinical work using AI technologies (as a User). These responsibilities may involve single or multiple projects.

Figure A: AI workforce archetypes

Shaper
Archetype description Set the direction for AI policy and governance at a national level.
Example responsibilities Decide on AI policies within healthcare at a national level.

Author and enforce regulation for AI technologies, for professionals creating and using AI and for healthcare settings implementing AI.

Create guidelines for the creation, procurement, deployment and use of AI.

Guide training of healthcare professionals.
Driver
Archetype description Champion and lead AI development and deployment at a regional/local level.
Example responsibilities Set the vision for digital and AI transformation at a regional/local level.

Champion AI technologies, by communicating the value and benefits, as a recognised and trusted leader.

Lead strategic decision-making related to AI procurement and deployment at a regional/local level.

Implement local AI governance infrastructure to ensure that AI is being deployed safely.

Promote funding and resource allocation for AI at a regional/local level.

Recruit and lead NHS AI multi-disciplinary teams (MDT).
Creator
Archetype description Create AI technologies for use in healthcare settings.
Example responsibilities Create AI algorithms independently or through collaboration with industry innovators and/or academia.

Test and validate AI algorithms during product development and subsequent releases.

Evaluate AI in terms of performance and clinical impact.

Set up systems for the ongoing monitoring of AI algorithms to assess for any model drift.
Embedder
Archetype description Implement, evaluate and monitor AI technologies deployed within healthcare settings.
Example responsibilities Conduct technical implementation and systems integration.

Ensure that healthcare data used by AI technologies is managed safely and securely.

Establish and manage safety processes for reporting AI technology issues and back-up pathways for when products fail.

Participate in ongoing monitoring of AI technologies assessing for any model drift, including designing and performing algorithmic audits.
User
Archetype description Use AI technologies within healthcare settings.
Example responsibilities Use AI within healthcare settings in accordance with guidelines.

Employ appropriate safety measures related to the use of AI.

Communicate with patients and the public about AI.

Page last reviewed: 17 April 2023
Next review due: 17 April 2024