Guest Contributor – Irene Jackman
As artificial intelligence (AI) continues to reshape the modern workplace, much of the narrative focuses on how older professionals need to “catch up” to remain competitive. The assumption is that youth and digital fluency are prerequisites for success in this new age. But what if that premise is backwards? What if the most strategic AI advantage today doesn’t come from being digitally native, but from being deeply experienced?
“AI may be the most powerful anti-ageism technology we’ve ever seen because it rewards what only time can teach.”
At YouAreUNLTD, we champion the idea that age and wisdom is a strength. And experience not seen as a limitation but a critical differentiator. In an era where technology accelerates decision-making and disrupts traditional workflows, those who have spent decades developing expertise, mastering nuance, and learning how systems truly function is more essential than ever. In fact, AI may be the most powerful anti-ageism technology we’ve ever seen because it rewards what only time can teach.
Experience: The Missing Link in the AI Conversation
AI doesn’t replace insight. It depends on it. For all its power, AI is only as valuable as the quality of the human judgment that guides it. It is a tool for pattern recognition and prediction, not for context, ethics, or strategic foresight. These are skills that are earned, not taught.
Seasoned professionals have spent years mastering complex environments, navigating ambiguity, and understanding the ripple effects of decision-making. This context is essential to making AI work in real-world business environments. As AI systems grow more capable, the cost of uninformed use grows, too. That makes insight and judgment, not just technical fluency, the most critical assets in any organization.
Research supports this. A 2023 study in the Journal of Applied Psychology (Ng & Law, 2021) found that older professionals are more likely to anticipate the downstream consequences of AI decisions in high-stakes environments. Their deeper mental models and systems thinking enabled more cautious, ethical, and strategic use of emerging tools.
AI Is Short-Circuiting the Traditional Learning Curve
The traditional workplace once allowed for learning through layers: entry-level staff observed and absorbed before taking on more strategic responsibilities. Today, AI is collapsing those layers. Automation is removing foundational tasks that once served as essential training grounds. As a result, younger professionals may be comfortable with the tools but lack the depth of experience to use them wisely.
A working paper from Harvard Business School (Kellogg et al., 2024) underscores this risk. In a field experiment involving 78 junior consultants using GPT-4 for business problem solving, researchers found that most participants lacked the technical and contextual understanding needed to use generative AI effectively. Their proposed risk mitigation strategies were often misaligned with expert guidance, revealing a gap not in motivation, but in maturity of insight.
Rather than guiding AI adoption, many junior consultants relied on short-term fixes or superficial strategies that failed to address system-level implications. Meanwhile, their senior counterparts, though less tech-native, were better equipped to understand the long-term and ethical risks associated with automation. This study directly challenges the idea that digital fluency alone prepares employees to lead in an AI-powered workplace.
The Shift in Workplace Dynamics
This has created a profound and largely underdiscussed shift in how organizations function. Digital nativity no longer guarantees readiness. In fact, it may be a liability if it’s not matched with strategic oversight.
“AI doesn’t democratize insight. It amplifies it, and in doing so, rewards those who’ve spent years learning how to think, judge, and lead.”
Organizations that assume AI levels the playing field may be in for a rude awakening. Without experience, the ability to guide AI meaningfully, across departments, industries, or human systems, can be dangerously shallow. AI doesn’t democratize insight. It amplifies it, and in doing so, rewards those who’ve spent years learning how to think, judge, and lead.
Rather than being sidelined by AI, older professionals are positioned to lead its integration. Their deep institutional knowledge, pattern recognition, and understanding of context make them the ideal guides for this transformation. And in areas such as governance, policy, ethics, and cross-functional leadership, their value is only increasing.
AI as an Anti-Ageism Technology
If used responsibly, AI could be the most effective tool we’ve ever had to combat ageism in the workplace.
By emphasizing the value of insight and contextual knowledge, AI shifts focus from age to impact. It creates space for late-career professionals to contribute meaningfully, well beyond the artificial limits of retirement timelines.
Recent reports by McKinsey and AARP found that organizations with age-diverse teams report stronger risk mitigation, better cross-functional leadership, and higher retention among mid-to-late-career professionals. Yet hiring practices often remain biased toward younger applicants for AI-driven roles, creating a disconnect between intent and outcome.
A related study published in OBM Geriatrics showed that when late-career professionals receive targeted AI literacy training, they quickly become powerful contributors. Rather than needing to learn technology from scratch, they simply learn how to apply existing judgment through a new lens. Their career experience becomes the very thing that gives AI its strategic edge.
From Retirement to Reinvention: How Institutions Are Reframing Late-Career Leadership
Forward-thinking institutions are already taking steps to redefine what it means to lead later in life, especially in an AI-driven economy. Yale School of Management’s Experienced Leaders Initiative (ELI) is a prime example. Designed for seasoned professionals navigating late-career transitions, ELI helps participants identify new ways to apply their expertise in service of greater societal and organizational impact.
Rather than viewing retirement as a wind-down, Yale reframes it as a launchpad for renewed purpose. The program supports leaders in identifying how their accumulated wisdom, strategic insight, and ethical sensibilities can be leveraged in areas like innovation, mentorship, and governance, precisely where AI disruption is most acute. It also fosters community among experienced leaders, encouraging peer collaboration and intergenerational exchange.
Programs like ELI reinforce the idea that the future of work will not be driven by who can adopt AI fastest, but by who can guide it most responsibly. And the capacity to guide, with judgment, foresight, and human-centered thinking, is most often found in those who’ve led through complexity before.
Building a Future That Learns from Experience
Organizations that will thrive in the AI age are those that build multigenerational teams, not to tick diversity boxes, but to reflect the reality that technology is not neutral. It is shaped by the minds that direct it.
This means creating structured learning opportunities for younger professionals and providing seasoned employees with the tools to lead transformation efforts. It means dismantling the assumption that digital is always better or that older workers are always behind.
AI is not a great equalizer. It is a great amplifier. It will magnify gaps in experience and strategic thinking just as quickly as it magnifies operational efficiency. The companies that recognize this and respond accordingly will build stronger, more resilient teams.
In this light, the future of work belongs not to the young or the old, but to the wise. And in the age of intelligence, wisdom is the most powerful currency we have.
Guest Contributor to YouAreUNLTD.
Irene Jackman is a faculty member at Durham College, a career transition coach with Verity International, and an HR consultant with over 20 years of corporate experience. She supports future HR professionals through teaching and mentorship, while helping individuals navigate change, challenge ageism, and rethink what meaningful work can look like. Her work explores how AI, equity, and lived experience are reshaping the future of work. A huge believer in continuous learning, she is currently pursuing a Master of Education with a focus on Digital Technology at Ontario Tech University.
References:
- Kellogg, K. C., Lifshitz-Assaf, H., Randazzo, S., Mollick, E., Dell’Acqua, F., McFowland III, E., Candelon, F., & Lakhani, K. R. (2024). Don’t expect juniors to teach senior professionals to use generative AI: Emerging technology risks and novice AI risk mitigation tactics (Working Paper No. 24-074). Harvard Business School. https://www.hbs.edu/ris/Publication%20Files/24-074_b72b0d90-42ab-41b1-8507-1475bfa3d1c8.pdf
- Chetty, K. (2023). AI Literacy for an Ageing Workforce: Leveraging the Experience of Older Workers. OBM Geriatrics, 7(3), Article 243. https://www.lidsen.com/journals/geriatrics/geriatrics-07-03-243
- McKinsey & Company. (2023). Inclusive growth. In 2022 ESG report (pp. 33–55). https://www.mckinsey.com/spContent/bespoke/esg-2023-sean/pdfs/06202023-inclusive-growth_esgreport2022_final.pdf
- AARP. (2023). The value of experience: A business case for age diversity in the workplace. https://employerportal.aarp.org/resource/the-value-of-experience-2023-report/
- Yale School of Management. (2024). Experienced Leaders Initiative. https://som.yale.edu/executive-education/for-individuals/experienced-leaders-initiative
