Our Take
Classic HR advice dressed up as AI strategy, with no actionable framework for the skills gap companies actually face.
Why it matters
HR departments are fielding daily questions about AI job displacement while lacking concrete data on which roles will change and when.
Do this week
HR leaders: Survey your workforce on AI concerns this month so you can replace generic reassurance with targeted skills planning.
MetLife CHRO preaches transparency over AI certainty
MetLife CHRO Shurawl Sibblies argues that HR leaders should stop trying to predict AI's workforce impact and instead double down on traditional HR fundamentals: active listening, transparency about uncertainty, and creating what she calls "learn mode" across the organization.
Speaking to HR Executive, Sibblies acknowledged that surveying MetLife's workforce would likely reveal "a mix of optimism as well as concern" about AI job displacement. Her response centers on transparency about what the company doesn't know: "We have to make it OK to say that we're in learn mode. We don't have all the answers but we're learning with you."
On companies that automate roles and pocket productivity gains without retraining displaced workers, Sibblies offered a diplomatic non-answer: "Every company needs to do what's right for their objectives and according to their values."
Skills planning remains the unaddressed challenge
The interview reveals the gap between HR's comfort zone and the operational questions AI deployment creates. While Sibblies emphasizes "learning agility and adaptability," she provides no framework for identifying which specific skills workers need or how to sequence that development when "the destination keeps moving."
Her focus on "human judgment" and "responsible use guardrails" sidesteps the more pressing question of how HR functions should collaborate with engineering and product teams to map AI capabilities against current job functions.
Active listening beats generic reassurance
Sibblies' core insight holds: transparency about uncertainty beats false confidence about AI's trajectory. But her approach works only if paired with concrete skills assessment.
The emphasis on "learn mode" as a cultural shift makes sense operationally. Workers need permission to experiment with AI tools without fearing their curiosity will accelerate their own displacement. However, this requires more than communication strategy. It demands budget allocation for training programs and clear criteria for measuring learning progress.
Her point about rewarding employees who "try something new" suggests a performance review structure that values AI experimentation, though she doesn't specify how to balance this against traditional productivity metrics.