Why You Should Put Experienced Talent at the Center of your AI Strategy – Part 2
In Part 1 of our series, we explored why mid-career and older workers are essential to an AI workforce strategy. These professionals bring a mix of deep industry knowledge, problem-solving skills, adaptability and judgment that today’s AI-driven economy urgently needs. Yet despite their apparent value, many employers continue to overlook this talent pool when planning for the future. In Part 2, we dig into what’s holding companies back and offer practical solutions for building an age-inclusive, AI-ready workforce.
Busting the Myth of Older Workers & AI
One of the most persistent and damaging misconceptions in the AI conversation is that mid-career and older workers can’t keep up with technology. The truth? Older workers can and do learn new technologies successfully when training is well-designed and relevant to their needs. The real barrier isn’t age. It’s access.
A survey by CWI Labs found that 92% of workers over the age of 50 are interested in learning new professional skills, including digital tools. But only about half of workers over 55 have been offered job retraining in the past three years, compared to 85% of workers between 18 and 34. When employers do offer training, it often lacks key features for successful adult learning, such as hands-on practice, real-world application or confidence-building design.
A Call to Action: Tapping Experience Talent
To realize the full potential of AI, employers must adopt a skills-first mindset that values what workers can do rather than how old they are or where they last worked. We must also ensure these efforts explicitly include mid-career and older workers, not just new graduates. Below are concrete actions employers can take to place experienced talent at the center of their AI strategy:
- Audit job descriptions for age preferences: There are common phrases that signal a preference for younger workers, such as “tech-savvy,” “energetic,” or “digital native.” These exact phrases can unintentionally discourage experienced candidates from applying, even when they are fully qualified. Conducting a formal review of job postings to identify and remove ageist terms broadens the candidate pool and ensures your organization attracts the best talent, regardless of age.
- Invest in upskilling programs for mid-career and older employees: Providing existing employees with access to AI-related training through online courses, micro-credentials or hands-on labs empowers them to evolve with the company’s needs. Mid-career and older workers who already understand your business are often your most valuable assets; with the right support, they can become AI champions inside your organization.
- Tap into underutilized talent pipelines: Community colleges, nonprofit training providers and workforce boards specialize in preparing mid-career and older workers for in-demand roles, including those requiring AI literacy. By building relationships with these institutions, employers can tap into a highly motivated pool of learners who bring both experience and new skills.
Experienced Workers Are Key to Winning with AI
AI is as much a human innovation as it is a technical one. To unlock its full potential, organizations need the contributions of experienced workers whose ability to solve complex business challenges and integrate AI into everyday workflows delivers real, measurable value.
Now is the time to act. Start building an AI workforce strategy that actively includes mid-career and older talent. It’s a smart investment in performance, innovation, and long-term success.
