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How Silver Workers Harness GenAI for Upskilling

GenAI is transforming the 50+ workforce, enabling them to stay competitive in today's dynamic environment. By integrating GenAI tools, experienced professionals are enhancing their skills and knowledge, emerging as indispensable contributors in the workplace.

Natalia Rodriguez

By Natalia Rodriguez

Natalia is responsible for developing our Talent Acquisition strategy, designed to attract, recruit, and hire top talent from around the world.

8 min read

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The ranks of the 50+ workforce, often called silver workers, are steadily climbing. In 2023, Pew Research found that 1 in 5 Americans older than 65 were employed, nearly twice as many as in the 1980s. A cocktail of flexible work opportunities and a retreating retirement age has kept them active. There’s a silver lining to an aging workforce, though. The growing number of silver workers paired with the rise of generative AI (GenAI) is setting up 50+ workers to become valuable hires. 

In this article, we’ll explore how silver workers can wield Generative AI development services to shine in managerial positions, upskill in-demand hard skills, and keep their work relevant by tapping into the industry trends without heading to far-flung conferences. Here’s how silver workers can take the lead in the corporate world. 

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Managerial Silver Workers Can Leverage GenAI to Oversee Intergenerational Teams

As the population ages, we’ve entered an era when four generations, Boomers, GenX, Millennials, and GenZ, coexist on the same teams. Managers are tasked with keeping diverse professionals engaged and providing conflict resolution. They may have to juggle a sentiment from younger reports of being an “out of touch” older manager while experiencing pressure to keep those employees engaged. Rehiring is expensive and time-consuming. To keep all corporate hierarchies harmonized, silver workers have a pivotal role in maintaining the peace. 

Silver workers have collected enough knowledge spanning long tenures in different roles and (sometimes) industries, making them invaluable in today’s fast-evolving workplace. They’re often great at critical thinking, having seen it all—from major conflicts to financial ups and downs. With AI tools, they can tackle today’s management challenges like intergenerational communication and inclusion, finding new approaches, and getting up to speed with the latest lingo.

Their experience is a goldmine for younger colleagues, and AI can help them share this wisdom more effectively. By inputting current management challenges into an AI tool, silver workers can consider many different approaches to helping their team overcome a problem. It could be management concerns, intergenerational communication issues, training, providing feedback, managing inclusion (topics less emphasized in the past), resolving conflict, etc. 

With GenAI, silver workers can balance contrasting points of view and incorporate new schools of thought when running their teams. The result will be a team that thrives with diverse thoughts and unified goals. A silver worker able to achieve this is infinitely more competitive than one that instills dated managerial methods from a less diverse time.

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Silver Workers can Leverage GenAI to Upskill Hard Skills to Remain Competitive

Generative AI is a valuable training tool for 50+ workers keen on honing their coding skills. It can help quickly prototype an idea, complete iterative development and feedback cycles, write up code documentation,  process complex concepts, and integrate developer workflow

Further, GenAI can effortlessly generate code examples, offer assistance in debugging code, and clarify complex programming concepts. Many AI assistants are fluent across programming languages and frameworks. Silver workers won’t necessarily need to learn new languages because GenAI is nimble enough to fill in the gaps. They can lean into the tech to create prototypes across languages or frameworks. This capability enhances learning efficiency and makes the often daunting programming world more accessible to a broader audience.

A software developer with 30 years of experience won’t necessarily have industry experience with relatively new code like Rust, released in 2015. Rust has steadily gained popularity, with Amazon, Google, Meta, and Microsoft all using it. Older engineers must learn new programming languages to avoid being overlooked for jobs. They can do so with GenAI. 

The business landscape of the 21st century demands growing databases and expanding data access. This means most employees, regardless of their job title, will need to manipulate, gather, and understand data on some level. To improve data analysis and Excel skills, AI can help generate data sets for practice, create complex Excel formulas, and guide users through data analysis techniques and tools. It’s a surefire way to ensure a silver worker would be hired again if their current job position were advertised on LinkedIn tomorrow. With the OECD projecting a rise in retirement age by the mid-2060s, professionals must embrace AI-driven upskilling to stay ahead of the curve while active.

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Silver Workers Can Remain Competitive By Using GenAI to Learn New Industry Trends 

No field of work remains stagnant for decades. If you were a civil engineering student in the 90s, you would’ve learned different modules compared to a GenZ studying civil engineering in 2024. Our methods of construction evolved. We created safer and more sustainable construction materials to replace harmful ones. We use polyurethane foams and cellulose fiber instead of asbestos, for instance. Civil engineers who don’t offer clients the best price, sustainability, and durable options will fall behind the competition and lose contracts. Therefore, silver engineers aren’t expected to submit plans using the same blueprints they created in college. 

However, college or university degrees are the first career stepping stone. From then on, you learn on the job. You read industry publications, attend conferences, take online courses, and participate in online forums and communities. Now that GenAI is around, silver workers have an accessible way to get up to speed on industry trends despite being decades out of university.  

For instance, civil engineers must align with new policies and legislation. If a city requires 40% sustainable materials in new builds, civil engineers can use GenAI for that sustainability analysis. AI can evaluate the sustainability of designs with current data, suggest materials and methods that reduce carbon footprints, and ensure compliance with environmental regulations. Knowledge share made possible with generative AI can keep silver workers’ output on par with younger generations with minimal effort. 

Within the education industry, GenAI can help older teachers who want to incorporate augmented reality (AR) into the classroom and remain competitive hires. They’ll have new tech at their fingertips and a vast pool of career anecdotes and fieldwork examples. Silver worker teachers are gearing up to become our kids’ favorite teachers.   

A powerful facet of GenAI is its ability to whip up customized learning content. This superpower will keep older professionals current in their field. Here’s how. I’ve noticed that when I google a household problem, like changing the clock in my car, I get a selection of YouTube videos. They demonstrate step-by-step how to get my clock back to the correct timezone. However, video tutorials are not for me. They are achingly slow, and there’s a lot of fluff throughout. I want to get straight to the point. 

GenAI can ensure every learner gets information tailored to them exactly how they want to receive it. This is great news for silver workers, who might want to avoid joining a webinar with predominantly college students or following an overly charismatic 23-year-old influencer on YouTube. GenAI can regurgitate learning materials in the best way for the user. This could be summarizing an academic paper in a few minutes or transcribing a video into written instructions. Particularly in tech, GenAI could present a case or situation where workers put their new knowledge to use, and challenges can be as specific as required. The more specific, the better!

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Silver Workers Can Use GenAI to Make Better Business Decisions than Their Younger Counterparts

Human insight is necessary so GenAI doesn’t make blatant errors that can cost businesses millions. It’s reasonable to hypothesize that an older worker’s experience could be advantageous in curtailing GenAI errors. Experienced professionals often have a deeper understanding of their field, enabling them to assess and integrate GenAI outputs more critically into their work.

One example occurred with FICO, the credit scoring company, during the COVID-19 pandemic. Their AI system misidentified a surge in online shopping as fraudulent activity, which could have led to the denial of millions of purchase attempts. FICO’s experts monitoring the AI system identified these false fraud identifications. They adjusted the analysis to prevent a catastrophic AI-ordered block on spending. We don’t know the age of FICO’s team members who caught the error, but I imagine some years of expertise were behind the decision. 

If a firm wants to take advantage of new tech, say quantum computing, team members can use GenAI to generate ways for their company to adopt it. The silver worker from the offset would take many more considerations into account than younger colleagues. The seasoned professionals may consider its impact on budgeting, ROI, team optimization, training, company culture, risk, and technical debt. The youth might only consider implementing the new tech in a few key processes. GenAI can produce very different outputs in the hands of different generations. The more experience a worker has, the more subtle discrepancies, errors, and blind spots they’ll catch in AI-generated content in their field. 

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Conclusion: GenAI Transforms AI into Competitive Assets

In sum, silver workers equipped with GenAI can become our most competitive hires. With GenAI employees of over 50 can: 

  • Better balance intergenerational teams by upskilling soft skills 
  • Stay closely aligned to industry trends or legislation on par with new grads. 
  • Use GenAI’s flexible output model to tailor learning plans for hard skills 
  • Incorporate new techs into their work, keeping it more relevant. 

Finally, if we discard silver workers because we now have GenAI, we will lose critical human insight by prioritizing seemingly productivity gains. However, equipping silver workers with GenAI grants access to both productivity gains and human insight in equal measure. 

 

Natalia Rodriguez

By Natalia Rodriguez

Natalia leads a team of 250+ employees whose mission is to seek, develop, and implement a top-class hiring experience. She is responsible for developing our Talent Acquisition strategy, designed to attract, recruit, and hire top talent from around the world while ensuring the best client experience.

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