Why AI training can backfire for older workers

A growing body of evidence suggests that efforts to train older workers in artificial intelligence (AI) technologies could inadvertently accelerate their departure from the workforce, particularly if such training is poorly implemented or perceived as burdensome. This insight comes amid a broader trend of increased investment in upskilling programs by employers seeking to adapt to rapid technological changes. However, for workers over 55, the traditional approach of offering more digital training may not yield the intended results and could instead exacerbate feelings of exhaustion and obsolescence. Recent data from Statistics Canada indicates that 36% of Canadian workers have used generative AI tools in their jobs over the past year, with 93% being aware of generative AI. Despite this awareness, a survey revealed that 83% of workers feel they need further training to effectively utilize these tools. Employers appear to be responding, with 78% of Canadian businesses planning to maintain or increase training budgets in 2026, according to the Canadian Federation of Independent Business. However, the effectiveness of such training initiatives may vary significantly depending on the age and experience level of the workforce. Research based on a doctoral thesis highlights that older workers, especially those experiencing burnout, may find additional training requirements overwhelming. Poorly timed, overly complex, or inadequately supported training can add to existing job demands, potentially pushing these workers toward retirement sooner than anticipated. The demographic shift in Canada’s workforce underscores the importance of retaining experienced professionals. According to Statistics Canada, the proportion of workers aged 55 and older within the average organization has nearly doubled since 2001, rising from 9.3% to 18.8%. The number of mature workers in Canada has surged by 184% since 2000, highlighting the critical role these individuals play in maintaining organizational continuity through their accumulated knowledge and expertise. To explore how technological advancements affect older workers, a comprehensive study analyzed 121 existing research papers, identifying 14 key areas where understanding remains limited. A subsequent survey of 361 participants examined how burnout and perceived work ability influence older workers' retirement decisions. The findings indicated that burnout diminishes workers' confidence in their ability to perform their roles, thereby increasing their likelihood of retiring early. The delivery method and timing of technological training played crucial roles in mitigating these effects. Adapting to new technologies requires substantial cognitive effort and time investment, processes that can lead to stress known as "technostress." This phenomenon, described by American psychologist Craig Brod, encompasses the anxiety and fatigue associated with integrating new technology into daily tasks. If training programs amplify rather than alleviate these pressures, they risk contributing to burnout among employees. While technostress affects workers of all ages, its implications differ for those nearing retirement. For older workers, burnout-induced erosion of work capability directly influences the decision to exit the workforce, a choice younger colleagues have yet to confront. A TD Bank survey noted that only 37% of Canadian workers felt their employers provided sufficient training, underscoring the widespread concern regarding inadequate preparation for technological shifts. As industries continue to evolve rapidly, the challenge lies in developing training strategies that genuinely support older workers without adding undue pressure. Employers must consider not just the content of training but also its timing, complexity, and the availability of resources to ensure it enhances rather than detracts from the well-being of their workforce.