AI is rapidly transforming working life by automating routine tasks, reshaping job roles, and changing the skills required across industries. From handling customer service to algorithms screening resumes or drafting reports, machine learning and generative AI is altering not just how work gets done, but who does it and how. While AI can boost efficiency, reduce human error, and free up administrative time for more creative or strategic tasks, it also raises concerns about job displacement, digital inequality, and the need for continuous reskilling. Ultimately, AI’s impact on an individual’s working life depends on how thoughtfully it is implemented and whether people at all career stages are supported to adapt and thrive alongside it.
Across many organisations, two powerful assumptions are shaping the future of work. The first is that AI, particularly generative AI and AI agents, will fundamentally reshape how we operate, automate, create, and collaborate. The second is more subtle, but just as impactful: that midcareer, older workers, are less suited to adapt to these technologies.
Moreover, AI in applicant tracking systems (ATS) can actually reinforce age discrimination because it often learns from historical hiring data that favours younger candidates and prioritises linear career paths or recent job history. These factors can lead to midcareer applicants being unfairly filtered out, not due to lack of skill or suitability, but because of algorithmic bias that replicates existing ‘human’ age discrimination.
As organisations embrace automation many are moving quickly to reskill, restructure, and reimagine roles. Yet in doing so, employers risk reinforcing outdated age stereotypes and missing out on a critical cohort of adaptable, experienced talent, the very workers who could help lead and stabilise this transition.
The stereotype that midcareer or older employees are less capable of learning new technologies is persistent, but unfounded. Research clearly shows that:
- Digital adaptability is shaped more by exposure and opportunity than by age
- Older workers are just as likely to succeed in upskilling programs when given equal access
- Experience with problem-solving, communication, and change management gives many mature workers an edge in learning new systems and integrating them meaningfully into their roles
Yet employers continue to assume that younger workers are inherently more digitally native, while sidelining older staff from AI training, pilots, or innovation teams. This creates a self-fulfilling exclusion cycle, where lack of inclusion is mistaken for lack of capability. When organisations exclude midcareer and older employees from digital initiatives, several risks emerge:
- Loss of institutional knowledge during transformation
- Widening skills gaps due to narrow training focus
- Reduced innovation, as AI is applied without the insight of experienced practitioners
- Increased age bias, particularly in AI-assisted hiring systems
- Lower morale and higher turnover among a vital part of the workforce
The better route is to recognise that age diversity is an asset in general terms and very specifically in the age of AI. Don’t assume digital literacy within an age group, build it as a capability within your organisation. Offer AI programs that are inclusive, paced for varied learning styles, and focused on practical, role-relevant use.
Pair digital fluency with experience. Intergenerational teams bring together experimentation and judgment and are a crucial combination for ethical and effective AI integration. Seek to make continuous learning a cultural norm. When midcareer workers see that growth is possible at any stage, they’re more likely to remain engaged.
The age of AI isn’t just a technological shift; it’s a cultural one. If organisations head into transformation assuming older workers can’t adapt, we’ll create systems and workplaces that exclude by design. But if organisations challenge that assumption, if they train inclusively and value all forms of expertise, we build workplaces where everyone moves forward, regardless of when they started their career.
And remember, no generation has had to adapt to more technological change in the workplace than GenX – those employees aged in their late 40s and into their 50s. This cohort is often stereotyped as being averse to change and digitally challenged, yet they started their working lives with typing pools and are now actively working with GenAI – they can adapt!
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