THE RETIREMENT WAVE; The Oncoming Threat Few are Talking About
- Miriam Mukasa - Inclusive Leadership & AI
- Jun 16
- 3 min read
Updated: 4 days ago
Everyone seems to be talking about the oncoming AI wave, the threats, the opportunities, the resources required. Yet few are talking about another threat looming across many Western countries; the retirement wave.
Whether we look at the US, UK or EU, the cold reality is this: labour forces across all three regions have been steadily ageing over the last two decades.
According to a UK report titled ‘The State of Ageing 2025’ published by the Centre for Ageing Better, 38% (~22 million), of the population in England is aged 50 or over. This figure is expected to rise to 46% by 2065. Furthermore, many of those aged 50–64 are, just like younger demographics, becoming increasingly more diverse.
In the UK
According to a Department for Work and Pensions (DWP) report dated 30 September 2025, the UK employment rate for people aged 50 to 64 years was 71.6% in 2025.
In terms of exiting the labour force, the average exit age in 2025 was 65.8 years for men and 64.7 years for women. Exit doesn’t always mean retirement; sickness, injury and disability also play a role.
In the US
According to a report by MyPerfect Resume, published on 21 May 2026, and drawing on data from the U.S. Bureau of Labor Statistics (BLS), workers aged 55+ make up 23.2% of the U.S. workforce and that figure is rising
The report goes further, highlighting that not only is the US workforce ageing, in some cases it is close to turning over all at once.
What does this mean for workplaces?
Countries such as the UK and US are currently relying on ageing populations at a time when youth unemployment is increasing and we’re being told that AI will replace many entry-level roles.
Given that many of those aged 50 – 64 are dispersed across a wide range of sectors, including critical infrastructure, what happens to the knowledge lost when older workers exit? Can AI really capture all this judgement, experience and often undocumented, know-how?
Are changing demographics being recognised and treated as critical issues within workforce planning and transformation strategies?
Furthermore, as organisational charts are predicted to look more diamond-shaped than pyramid-shaped, how will this impact succession planning and knowledge transfer?
What about inclusion? Are organisations actively prioritising inclusive culture mindsets to mitigate age-based stereotypes?
Health and wellbeing considerations
Many of those in the 50-64 age group, particularly women, are often juggling full-time work while caring for, or coordinating care, for elderly parents. This frequently coincides with managing their own health challenges.
The question now is whether flexible and/or remote working can continue to be viewed by some organisations as a “nice-to-have”, or whether organisations will wake up to the impending reality and treat flexible working for what it is: a critical component of workforce planning and transformation strategies.
In terms of Diversity and Inclusion
Training and awareness programmes must recognise intersectionality within older demographics, just as they do for younger colleagues. Many older employees also face other forms of discrimination alongside age. These may relate to race, gender, sexual orientation, disability and more.
Going forward
With some occupations nearing large-scale retirement turnover, particularly those requiring certification such as electricians, HGV drivers, plumbers, healthcare workers, pilots and teachers, action is required now.
Workforce planning and transformation strategies must recognise the oncoming realities of an ageing workforce, what this entails and the resources and support required. Retention and knowledge transfer must be prioritised.
Colleagues with deep experience often bring vast, untapped, often undocumented value to organisations and, in the era of AI, can play a critical role in training both humans and machines. The question now for leaders is, are you planning for the retirement wave with the same urgency, rigour and investment that you’re currently applying to AI or, are you allowing decades of experience, judgement and capability to walk out of the door?
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