As artificial intelligence reshapes the future of work, one critical question is emerging: Are our AI systems inclusive of every generation in the workforce?
With automation, algorithms, and AI-driven decision-making increasingly shaping hiring, training, and productivity tools, there’s growing concern that age-related bias may be coded—often unintentionally—into the digital foundations of our workplaces. The consequences are more than theoretical. Without intentional safeguards, AI could reinforce harmful stereotypes and systemic ageism.
But there’s good news: age-proofing AI—designing systems that fairly serve workers of all ages—is not only possible but can lead to more innovative, diverse, and resilient organizations.
The global workforce is aging. According to the International Labour Organization, by 2030, people aged 55+ will make up nearly 25% of the workforce in high-income countries. In the United States alone, the Bureau of Labor Statistics projects that workers aged 65 and older will be the fastest-growing age group in the labor force through 2032.
Yet many AI tools used in recruitment, performance tracking, and learning management systems may not account for age-related inclusion. In some cases, they may inadvertently disadvantage older employees or job candidates through biased training data or flawed design assumptions.
A 2023 AARP report found that nearly 2 in 3 workers aged 50+ believe older employees face age discrimination in the workplace, and AI risks amplifying these challenges if unchecked.
Bias in AI often stems from its training data. If the data reflects a society that undervalues older adults—whether through language, hiring patterns, or workplace feedback—then AI will likely replicate those patterns.
In 2022, the U.S. Equal Employment Opportunity Commission (EEOC) settled a lawsuit against iTutorGroup, an ed-tech company that used AI to automatically reject applicants over the age of 60. This case served as a wake-up call: AI discrimination can and does happen, and accountability is real.
Even beyond hiring, AI-based productivity tools might reward fast-paced keyboard activity (which could penalize those with arthritis or slower typing speeds) or recommend upskilling paths that lean toward younger learning styles.
One persistent myth is that older workers struggle with technology. Yet recent studies contradict this.
- A 2023 survey by Generation found that 89% of hiring managers believe mid-career and older workers perform as well—or better—than younger workers, particularly in terms of reliability, emotional intelligence, and complex problem-solving.
- A 2024 Pew Research study revealed that 71% of workers aged 50–64 use digital learning platforms, including AI-powered tools, to learn new skills, especially in healthcare, finance, and tech-adjacent sectors.
Age, in other words, is not a proxy for tech aversion.
5 Strategies to Age-Proof AI and Foster an Inclusive Workplace
1. Design with Age Diversity in Mind
Co-create AI tools with input from multi-generational user groups. Inclusive design isn’t just about race or gender—it also includes age. Ask: Would a 60-year-old employee find this tool intuitive?
2. Audit for Age Bias
Conduct regular audits of algorithms—particularly those used in hiring, promotions, and performance management—to detect age-based disparities. Tools like IBM’s AI Fairness 360 or Microsoft’s Fairlearn can help assess model fairness.
3. Broaden Training Data
Ensure datasets used to train AI models include examples from a wide age range. This helps prevent models from learning narrow behaviors or assumptions based solely on younger populations.
4. Offer Tailored Upskilling Paths
Design training programs that account for different learning styles. Some older workers may prefer structured, slower-paced modules with more practical examples, while others may thrive in interactive, real-time learning environments.
5. Leverage Reverse Mentorship
Programs that pair younger employees with older ones for mutual learning (e.g., Gen Z shares digital fluency, Boomers share leadership skills) can help bridge generational gaps and humanize AI adoption strategies.
Age-proofing AI isn’t about creating special treatment—it’s about ensuring that AI serves everyone equitably, not just the digital natives.
As organizations strive for greater diversity, age must be part of that conversation. Inclusive AI systems don’t just prevent lawsuits or reputational harm—they unlock the full potential of an age-diverse workforce.
After all, a workplace where experience meets innovation is not just ethical—it’s strategic.
As AI becomes the new colleague in every industry, ensuring that it recognizes the value of experience is a powerful step toward true workplace equity. Let’s not teach our machines the wrong lessons about age. Let’s design a future of work where every generation is invited to the table—and every voice is heard.
