Can AI Help Fix Our Demographic Time Bomb?

America faces a demographic crisis: our senior population is getting larger, older, sicker, and more expensive.

By 2030, there will be fewer than three American workers supporting each senior citizen – a historic low – while caring for those seniors will cost 3-5x more than their younger counterparts.

In addition to the immense cost burden, there simply aren’t enough healthcare workers to provide the necessary care. By that same year 2030, the U.S. expects shortages of 200,000 nurses and 124,000 physicians. And similar shortages are already being felt in the U.K. and elsewhere.

As a result, both patients and clinicians suffer. Physician burnout from excessive documentation, compliance with numerous regulations, and billing requirements are leading to frustration, reduced productivity, job satisfaction, and turnover. 

Over the years, many have predicted AI would replace a large percentage of a doctor’s job. Yet we must ask: can AI actually bridge the gap in healthcare workers? And if so, how do we prepare the next generation for success?

Rethinking a workforce powered by AI

It’s not just about AI replacing jobs, but enhancing them. To achieve the real goal – which is to do more with less – we need to get practical about specific tasks and jobs.

Tasks not requiring human judgment should be automated, such as scheduling appointments, ordering labs, and even clinical documentation. And with the proliferation of generative AI, we see exciting opportunities to support and enhance clinical decision making. 

For example, new startups are already handling intake for hundreds of thousands of new patients. AI is being used to automate the generation of radiological reports. And now clinical grade physical therapy is available in the ease and comfort of the home.

In these examples, AI allows clinicians to focus on patient care, treating a greater number of patients, and doing so more effectively.

Building a next-generation workforce using AI

Adding new technology here and there isn’t enough, so we must rethink everything from recruitment to education to training.

1. Recruit non-traditional healthcare workers. 

Expand the workforce by hiring people from non-traditional clinical backgrounds like community health workers, home health aides, health technicians, and paid family members. This diversifies the workforce and provides personalized care while addressing unequal healthcare access.

2. Rethink education and curriculum.

Despite spending more than $100 billion globally on medical and nursing education, the curriculum changes slowly, in some cases keeping century-old methods in place. Training programs need to adapt quickly to address workforce shortages and integrate new technologies. For instance, using generative AI in clinical documentation can make medical notes understandable to patients and prevent clinician burnout.

3. Embrace new training methodology.

Traditional medical training is siloed. The future is team-based care, where not just doctors, but an array of health practitioners collaborate. This improves access to care and allows doctors to manage complex cases. Medical and health science education should include ongoing skill assessments and training in new technologies to create a flexible workforce.

To policymakers, healthcare educators, and industry leaders: The future of healthcare depends on change. AI has the potential to make sweeping changes in a constructive and meaningful way to our healthcare system as we know it. 

We must invest in modernizing health science and medical education, embrace innovation and new care models, and expand our parameters for healthcare talent. Together, we can build a resilient healthcare system ready to meet the challenges of tomorrow.

Photo: Juanmonino, Getty Images

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