The acute shortage of radiologists within the Australian public health system has created
an urgent need for a refinement to their role to increase the speed, accuracy, and
prioritisation of their diagnoses for patient care. A viable and highly advantageous
solution, internationally and in private health services, has been the use of AI to assist
radiologists with the diagnoses of medical images. Yet such large-scale AI
implementation can also produce increased workload, uncertainty, stress, and anxiety
for workers, due to perceived threats to professional identities and work role changes. In
this presentation, we propose that the successful sustainability of AI initiatives directly
depends on understanding the attitudes, perceptions, and acceptance levels of impacted
workers. Our research - the first in an Australian public hospital - provides Australia's
first comprehensive evaluation of the key aspects of AI implementation for medical
imaging diagnostic services. Informed by our digital transformation model, we will
describe the multiple components of the AI implementation. We will also provide the
pre and post comparative results of a longitudinal survey (administered 3 times over 18
months) that traces the workplace psychosocial impacts arising from AI
implementation. The survey includes measures of job demands, support, control,
performance, wellbeing, and technostress. More specifically, in this presentation, we
will also consider management and leadership attitudes to the change and technology
adoption, and how this influences levels of employee change readiness and other
psychosocial outcomes.