As much as 15% of the current healthcare workforce hours will be subject to automation by 2030.
The growing reliance on AI is primarily due to the swelling patient population and a shorter pool of health specialists, according to analysis by Stocklytics.com.
The site’s financial analyst, Edith Reads, comments: “The Covid-19 pandemic’s impact on patient volumes served as a critical wake-up call, underscoring the urgent need to modernize and upgrade the healthcare system.
“The adoption of AI is expected to alleviate the workload on healthcare providers, potentially reducing burnout rates and improving job satisfaction.
“By automating mundane tasks, healthcare professionals can dedicate more time to patient care, research, and specialised medical procedures, thereby enhancing the overall quality of healthcare services,” she adds.
The analysis indicates that almost 90% of healthcare workers, life science companies, and tech vendors use AI in some capacity.
AI implementation in healthcare systems can be categorised into machine learning, natural language processing, computer vision, and context-aware computing,” Reads says. “So far, machine learning has taken the lead in most AI-driven solutions by integrating AI and robotics in diagnosis and treatment.”