RPA, which is expected to impact most jobs, will likely add capacity, reduce staffing costs and reduce human error by automating tasks that are manual, repetitive and rules-based processes. These tasks include billing, claims submission, patient enrollment, insurance verification, patient scheduling, inventory management and contract management. For many, RPA will be a welcome entrant into their workflow, freeing them up to spend more time assisting and caring for patients or other job duties that can’t be performed by technology. However, automation could also result in the elimination of some workers who specialize in these tasks.

Beyond automation, clinicians will see benefits from AI and machine learning when it comes to incorporating data into their decisions. Machine learning models with clinical decision support capabilities are already being worked into the field, with predictive tasks making it easier to diagnose diseases or classify cancers based on images. In order for machine learning to be useful to clinicians, data has to be accurate, meaning more training for the workforce could be coming in the future to ensure the integrity of data.

“In the future, AI will make sense of the overwhelming amount of data created from genomics, biosensors, smartphone apps, the electronic health record (EHR), unstructured notes and data on social determinants of health, and create a broader context for clinicians to deliver high-quality, patient-centered care,” the report reads.

Workers will also have to have new digital skills to use the technology, including digital acumen, AI acumen, data appreciation, an open mind and agility.

“With AI as their new co-worker, staff will need to acquire new skill sets and competencies to take advantage of AI capabilities, and the educational pipeline needs to equip those entering the health care workforce with new skills,” the report reads.

According to the AHA, the emergence of these technologies in the healthcare workplace will put a premium on new positions that facilitate the tech, such as a data scientist; AI engineer; data governance expert; data entry expert; data engineer; or chief AI officer.

For hospitals and health systems thinking about all these changes that go along with implementing AI, it is critical to remember to focus on people skills and the patient relationship, as those aspects of healthcare aren’t likely to change.

“The workforce of the future not only will need people with technical skills, but also soft skills like communication and empathy to take full advantage of what AI gives them to do their jobs,” the report notes.

See the full report here.