The final edition of the Dive In Festival begins tomorrow, with the insurance sector grappling with a question that has become inseparable from discussions on talent and inclusion: who stands to gain as artificial intelligence becomes integrated into daily operations?
The global festival dedicated to culture and talent runs from September 22 to 24, marking its 12th and final year. With participation expected from over 30 countries, this year’s theme, “The Human gAIn: Powering Culture & Connection,” examines how insurance firms can leverage AI while preserving the creativity, judgment, trust, and human connection that are vital to the industry.
It serves as a fitting final theme for an event that launched in London in 2015 and has since evolved into a worldwide insurance initiative. Last year alone, Dive In drew more than 35,000 participants across 102 events in 31 countries.
For insurance executives heading into this week’s sessions, the conversation has moved past the question of whether AI will be integrated into the workplace managing director at Asta
“We’re done with AI being a future world,” said Barley. “We’ve moved beyond a world where, particularly from a technology itself: Can I implement it well? Can I get the right things out of it? It is going to amplify what we do all day, every day.”
Insurers, brokers, and other industry players are now addressing how work is allocated, which staff members are granted access to new tools and training, and whether AI will ultimately expand opportunities or solidify existing disparities.
The bias leaders may not see coming
Barley anticipates that trust will be a central topic during this week’s discussions, alongside themes of adoption, judgment, guardrails, and the evolving skill sets employees will require as AI capabilities grow.
Among these, she identified bias as a primary concern for insurance leaders as deployment speeds up. Insurance firms utilizing historical data may inadvertently perpetuate patterns—accelerated by AI—that fail to reflect future outcomes or conditions.
“The past doesn’t necessarily represent the future, so to the extent that you’ve got bias in your data and amplify it forward, I don’t think that’s a new thought, particularly inside the insurance industry,” Barley noted. “It’s what you don’t know is being amplified, and what you don’t know in those biases that’s being brought forward,” she said.
This could manifest in ways unrelated to a clearly discriminatory algorithm. Barley pointed to disparities in the speed at which different teams gain access to new AI generations, the caliber of training provided, and the level of opportunity staff have to utilize the <a
