AI Training Challenges for Older Workers: A Study on Burnout and Retention

As artificial intelligence (AI) becomes increasingly integrated into workplaces, employers are investing more in training programs to help employees adapt. However, a recent study suggests that this approach may not be effective for older workers, particularly those over 55, who are already experiencing burnout.

The study, based on a doctoral thesis, highlights that poorly timed or overly complex digital training can exacerbate burnout among older employees. This burnout can weaken their perceived work ability, pushing them towards early retirement. The research utilized job demands-resources theory, which examines how job demands and available resources affect employee well-being.

Statistics Canada data reveals that the proportion of workers aged 55 and older has nearly doubled from 9.3% in 2001 to 18.8% in 2022. This demographic shift makes retaining experienced workers crucial, as they hold valuable institutional knowledge and expertise that are difficult to replace.

The study found that effective training for older workers should be paced appropriately, breaking down complex material into manageable parts and allowing time for practice. Reducing workload pressures can also help older employees absorb new information better. This approach can prevent burnout and help retain skilled workers.

Employers are advised to consider not just what employees need to learn, but also their capacity to absorb new information. By designing training programs that align with the needs and capabilities of older workers, companies can better support their adaptation to technological changes.