AI as a fountain of youth? The case for archiving a graying workforce’s institutional knowledge

Generative AI continues to expand its reach across personal and business scenarios, but we’ve only scratched the surface of its potential to help companies. Businesses are expanding the potential scenarios in which to apply this technology, to both accelerate growth and stabilize their foundation of knowledge. This evolution presents an incredible opportunity to save the invaluable knowledge base of the Baby Boomer generation that is leaving the workforce permanently.

According to data from Forbes, four million Baby Boomers will leave the workforce this year alone – that’s 10,000 Boomers retiring every day in the US. The good news is that this opens incredible advancement opportunities for younger generations; the bad news is that this group of graying workers, who have been in their professions longer than any other generation, possesses boundless knowledge about their field and company. Boomers leaving the workforce represents an unprecedented departure of institutional knowledge that companies may have long taken for granted, and AI can mean a lifeline of hope as Boomers trade corner offices for weekday tee times.

More widely known for its generative capabilities, AI tools like ChatGPT excel at taking unstructured data and consolidating it into a store that can be queried or acted upon in meaningful ways. That is, the aggregation and contextualizing capabilities that can be used with large language models can be equally valuable. Add that to the fact that the language models are only the foundation on which these solutions are built, and we can begin to solve some complex and impactful use cases. Combined with more advanced techniques to ingest, orchestrate, and produce, we now have ways to truly create assets out of our institutional knowledge.

Retirements have almost always meant a loss of institutional knowledge that companies had to try to replace. Through new AI applications, companies can retain much of what a long-tenured employee knows and pass that wisdom along to the rest of the team. And all of that can take place without the older and newer employees ever meeting each other.

Generative AI can be directed to systematically archive employees’ institutional knowledge through dictation, notes, transcripts, emails, and input from primary systems, thus creating a contextualized database. Over time, AI can catalog the organization’s ideas and problem-solving methods from these databases that future employees can search even as team members move out of their current roles, making the organizational knowledge available for years to come. In practice, this approach could be the equivalent of creating the perfect knowledgebase article for the task at hand, via chat or other input.

For younger employees, the departure of experienced coworkers also means a loss of mentorship opportunities when Boomers leave the workforce. And while nothing replicates one-on-one coaching and career development, preserving the institutional knowledge of a long-tenured generation can bridge the knowledge and skills gap for younger workers. When companies invest in innovative ways to capture and share the knowledge and expertise of workers who are now retiring, they also invest in the development of their younger workers.

Young employees are not the only ones benefitting from the larger deployment of AI-based solutions. Much like the data-driven approach has unlocked agility and knowledge from structured data across the organization, generative AI is poised to unlock immense value in unstructured data. Companies building a foundation in generative AI tools and skills today will be poised to deploy the next wave of data-driven solutions more successfully and quickly than ever before.

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