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Changes in Work – Unions, Demograhics, Trust and Artificial Intelligence (AI)

Manny Teran, Adam Hartung
Justices, Clarence Thomas, Sam Alito, AI, Labor unions, Baby boomers, diversity, labor

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Reflecting on U.S. Labor Day, the work world has been impacted incredibly by the Baby Boom Generation. That large group of workers meant supply of labor exceeded demand for some 4 or 5 decades, which nearly killed unions.  But now that the demographics are upside down, with demand for labor consistently exceeding supply, union activity is up, support for unions is up, and employers have no option other than being flexible.

With many leaders over 60, a trust issue has developed between younger workers and older leaders.  Many younger workers aren’t willing to follow leaders unquestioningly.  They see serious ethical gaffes by people like Justice Clarence Thomas and Sam Alito and question whether leaders are looking out for the good of the organization, the good of the country – heck the good of anyone else other than themselves.  With that trust broken, leaders of big corporations cannot expect to rule by decree any longer.

And AI is finding its way into the workplace, no matter how much leaders or workers fear it.  AI is a tool that can help productivity and achieve better results, but not without careful decision making, good data selection and effective tool utilization.  Doing that is best accomplished by bringing together those with the process and decision-making skills of age and the insights and tool application skills of youth.

Thinking points:

  • Are you carefully assessing the needs of employees and helping them achieve their goals, not just yours?
  • Have your decisions impacted employees and co-workers demonstrating that you can be trusted to think about the good of the group, and not just yourself?
  • Have you considered replacing older leaders with younger leaders, then re-assigning older workers to important roles supporting the new leaders?
  • Are you finding ways to have younger and older people work together, or does bias keep you from making these kinds of demographically diverse teams part of the workplace?