Simone A. Bielsker, CAE, program director of information systems at the American Staffing Association, has a long wish list for how the association’s staff can use AI, including content and analytics. But the list of questions she has is nearly as long. To that end, her priority at ASA is developing a technology adoption survey that clarifies how staff members are using AI tools and where they want to go next.
“We want a better idea of what exactly you are using,” she says. “How often are you using it? What is your appetite for learning new technologies? What AI tools are you using, and why are you using them?”
Bielsker sees the technology adoption survey as a first step in future planning, to make sure that staff has the resources to do their jobs more efficiently in areas where AI can help. But it’s also an intervention of sorts, to ensure that staffers aren’t plugging ASA’s intellectual property into large language models or drawing false conclusions from analytics tools.
“With generative AI, especially around analytics, you need to understand how those analytics handle decision-making,” she says. “The generative AI part of that is not that difficult—we have all of that right now. It gives you an amazing amount of information. But utilizing that information is a different skill set.”