Clinical use of artificial intelligence requires AI-capable organizations

Artificial intelligence-based algorithms are being widely implemented in health care, even as evidence is emerging of bias in their design, problems with implementation, and potential harm to patients. To achieve the promise of using of AI-based tools to improve health, healthcare organizations will need to be AI-capable, with internal and external systems functioning in tandem to ensure the safe, ethical, and effective use of AI-based tools. Ideas are starting to emerge about the organizational routines, competencies, resources, and infrastructures that will be required for safe and effective deployment of AI in health care, but there has been little empirical research. Infrastructures that provide legal and regulatory guidance for managers, clinician competencies for the safe and effective use of AI-based tools, and learner-centric resources such as clear AI documentation and local health ecosystem impact reviews can help drive continuous improvement. Lay Summary Computer-based tools using artificial intelligence (AI) are being widely implemented in health care, even as evidence is emerging of bias in their design, problems with implementation, and potential harm to patients. To achieve the promise of using of AI-based tools to improve health, healthcare organizations will need to be AI-capable, which means that policies and processes in healthcare organizations reflect and use societal guidance such as professional ethics and regulatory constraints to ensure the safe, ethical, and effective use of AI-based tools. Ideas are starting to emerge about the organizational processes, knowledge, resources, and societal guidance that will be required for safe and effective deployment of AI in health care, but there have been few accounts of organizations wrestling with these issues in real implementation of AI in clinical care. Healthcare organizations need resources for safe and effective implementation and ongoing improvement, including, for example: legal and regulatory guidance for managers, training for healthcare workers in the safe and effective use of AI-based tools, clear software documentation, and methods to enable assessment of the impact of the use of AI tools on socially vulnerable people.