• Marjorie Powell, AARP's CHRO, is a member of BI's Workforce Innovation board.
  • Powell says creating a collaborative learning environment is key to helping employees adapt to AI.
  • This article is part of "Workforce Innovation," a series exploring the forces shaping enterprise transformation.

As the chief human resources officer at AARP, Marjorie Powell devotes much of her professional energy to meeting the needs of the multigenerational workforce. These days, much of that involves navigating AI's impact to ensure every employee at the nonprofit is prepared for the technological changes shaping the workplace.

"Our goal in everything we do for our employees is to provide the resources, support, and capabilities they need to make good decisions within the company's guidelines," she said. "We take the same approach with AI."

Powell's mission extends beyond AARP's workforce. As an advocate for the 50-and-over demographic, she champions the adaptability and contributions of older workers in a tech-driven economy.

"There's an assumption that people over a certain age are not comfortable with technology, but what's overlooked is that many older people — particularly those at the end of the baby boomer generation — were at the forefront of this technological revolution," she said.

The following has been edited for length and clarity.

How did AARP handle the introduction of AI in its workforce?

We decided to use Copilot because we're already a Microsoft company. We got enough licenses to set up a working group with key people we thought would be super users. The idea was to experiment with AI tools and see how they fit into our workflows.

We wanted to learn and figure out what works and what doesn't. Then, we could make a decision about how we were going to roll it out to the company, since one, it's costly; and two, we wanted people to feel comfortable with it.

What were some of the outcomes of the working group, and how did those results shape the way AARP approached training and support?

We issued a policy, a generative AI use case approval process, and a mandatory training for all staff to complete to learn how to use gen AI in the workplace. The training focused on internal and external use and the types of information that can be shared, public versus private, and so on.

We encouraged our staff to 'Go out there and play with it.' We then surveyed them and asked, What are you using it for? What are some great use cases you've developed? How's it helping you enhance your productivity? How are you using this tool to further the AARP mission?

We also considered what existing structure we could use to encourage staff to use AI and explore the technology. We already had a structure in place called Communities of Practice — groups where employees learn and share. It's like an employee resource group (ERG), but focused on learning and development within industry, so we used this model to create an AI Community of Practice.

What are some of the 'great use cases' for AI for your HR team specifically?

We get a lot of calls and emails on simple things about AARP benefits and policies. People ask questions like: I'm having knee surgery next month. How do I sign up for FMLA? or Where do I find my W2? or I bought a Peloton. Is that eligible for the fitness credit? So we started building an HR chatbot to provide that kind of information. It's much easier for employees to ask the chatbot instead of overwhelming a team member with those queries.

We're currently piloting the chatbot with 300-400 frequently asked questions and answers preloaded. It directs employees to the right information without them having to dig and helps us understand what additional information we need to include.

Many employers are using AI tools in hiring, but there are concerns about potential bias. What's your perspective on this?

We use AI for sourcing candidates. All AARP recruiters are certified to conduct Boolean searches to increase the accuracy of identifying talent with specific skill sets in the marketplace.

But when it comes to screening and interviewing, we don't use AI. We find that the technology is still very biased, specifically when it comes to age. Until the technology matures enough to minimize bias, I don't believe it's a good idea to use it without that human component of judgement.

Speaking of age, what are your thoughts on ageism in the workplace today, especially from companies hesitant to hire older workers?

Companies don't want to be the kind of organization that isn't welcoming to talent, regardless of age. Due to the economy and the rising cost of healthcare, many people in the 50-plus community are re-entering the workforce.

Many in that age group have valuable skills and experience and are eager to return. They often say, 'I don't need to be in a leadership role. Been there, done that. I just want to help and be of use.' They also naturally take on mentorship roles, as people seek their guidance. By embracing this segment of the workforce, companies can gain huge value.

What do employers misunderstand about older workers and technology?

Baby boomers were at the forefront of the technology era, and they're more comfortable with technology than many people realize. In fact, they are among the largest consumers of technology products. Tech companies really need to pay attention to this demographic.

I look at myself — I'm about to turn 60 — and I was selling Commodore 64s when I was in high school. I've seen everything from floppy disks to CDs, to cassette tapes, to 8-tracks, to digital streaming and everything else. I've experienced all versions of technology, and I've adapted. I'm still willing to adapt, and I'm still learning.

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