Jonny Phillips, Managing Director at Strive Training discusses the biggest myths about older workers and AI. This is highly relevant for the business support profession as technology plays an ever increasing role in the managing tasks…
While AI’s impact on the workplace has dominated headlines in recent years, much of the public conversation has focused on younger workers. They’re assumed to be in most urgent need of AI skills, those preparing to enter the workforce, adapt to new tools and future-proof their careers.
This narrow perspective neglects a significant portion of the labour market. Experienced employees, who bring decades of expertise in managing teams and navigating organisational change, are expected to embrace AI as rapidly as everyone else, usually without specific guidance. The result is a growing skills and confidence gap that’s rarely acknowledged in discussions about the future of work. At the core of this issue are a series of persistent myths.
Myth 1: Older workers can’t adapt to AI
One of the most common misconceptions is that adaptability declines with age. In reality, evidence suggests that our capacity to learn is far more dependent on opportunity and confidence than on age itself. OECD research shows that adults across all generations can develop new digital skills when training is relevant, practical and delivered in a supportive environment.
Many of the competencies required for effective AI adoption, such as understanding systems, evaluating outputs and managing implementation are already strengths that experienced employees bring to the table. Targeted training allows those strengths to be extended, not replaced.
Myth 2: AI training is mainly for new entrants to the workforce
Several graduate programmes are integrating AI into curricula, but the largest upskilling initiatives are aimed squarely at existing employees. In January 2026, the UK Government relaunched its AI Skills Boost programme with a target of providing AI training to 10 million workers by 2030 across the economy, not just among new starters.
The CIPD has similarly called for “a new reskilling era,” in which lifelong learning becomes a necessity rather than an optional extra. The challenge is ensuring that training is accessible and relevant to people who may have decades of expertise but limited exposure to AI tools in day-to-day roles.
The admin and business support profession has traditionally faced a training gap, as structured training hasn’t been provided by their employers. However, there are excellent training provided for Executive Assistants, Personal Assistants and Office Managers to bridge the gap. This ensures assistants have the confidence and knowledge needed to adapt fast to new technology, including AI.
This is also where organisations have the most to gain. Most companies have treated AI adoption as a technology issue rather than a workforce development matter. Those that offer consistent, targeted support across teams, not just in pockets, will be better positioned to realise its benefits.
Myth 3: Experience matters less in an AI-driven workplace
As AI takes over routine tasks, summarising reports, generating business insights, drafting communications, it can seem as though technical fluency will outshine human judgment. The opposite is true. AI tools require context and interpretation to be useful, and their outputs frequently require scrutiny.
The UK National Cyber Security Centre has repeatedly highlighted the reliability and accuracy limitations of large language models, underscoring the need for human oversight. Experienced workers are well placed to provide exactly that: the sector knowledge, pattern recognition and contextual judgment that distinguish a well-applied AI output from a misleading one. Far from diminishing the value of experience, AI has raised its stakes.
Myth 4: Younger workers automatically have superior AI literacy
There’s a persistent tendency to equate digital nativity with AI fluency. While younger workers may be more comfortable with consumer-facing technology, meaningful AI literacy is a different skill set, one that requires understanding a tool’s limitations, recognising its biases and knowing when not to use it at all.
A McKinsey report from 2025 found that most organisations overestimate their workforce’s AI capabilities, and that age made no meaningful difference to that overestimation. Competence comes from structured exposure and guided practice, neither of which is automatically acquired by growing up with a smartphone.
Myth 5: A single training session is enough
Perhaps the most persistent misconception is that AI upskilling can be handled with a one-off workshop. The technology is evolving rapidly and so are the ways it is applied in professional contexts. A session delivered today may be outdated within a year.
The ICO has highlighted that ongoing training, governance and review processes are essential to responsible AI use. For experienced workers in particular, repeated opportunities and practical, real-world application are what build genuine confidence, not a guidance document or a single afternoon.
What organisations should do instead
Once these myths are set aside, a clearer picture emerges. The challenge facing organisations is evidently not a generational divide in capability; it’s an uneven distribution of practical, confidence-building support.
The workers best placed to get value from AI tools are those who already possess the judgment, sector knowledge and contextual awareness that those tools can’t replicate. The goal, then, is not to replace experience with technology, but to equip experienced people to use technology well. Organisations that invest in doing this consistently, across all levels and career stages, will have a meaningful advantage over those that don’t.
