Table 3

Action plans tailored to stakeholders for addressing specific issues

Current issuesAction plansStakeholders
Lack of interoperability between hospitals
  •  Engage with medical informatics system vendors to facilitate integration of AI and secure data storage

Healthcare providers
Lack of validation of AI quality/efficacy
  •  Conduct tests using independent external data to validate, optimise and audit AI efficacy

Lack of standardisation in evaluation and validation of AI
  •  Develop and mandate the use of standard oncology terminologies and ontologies

  •  Set the standards required to evaluate the performance of AI-based tools systematically

  •  Establish an up-to-date regulatory and legal frameworks for different AI based on implementation risks

Commissioners and regulators
Lack of integration of implementation science framework
  • Establish consensus regarding trial protocol involving AI to standardise reporting

  • Conduct AI studies that validate patient-centred outcomes and cost/time/resource effectiveness

  • Promote implementation science research to learn optimal methods to AI deployment in cancer care

Academics and healthcare providers
Lack of workforce training
  • Level up on knowledge of AI and basics of medical informatics

  • Prepare for disruption and adapt to changes in nature of work with the integration of AI

Healthcare professionals
  • AI, artificial intelligence.