Francesca Roche sits down with Alex Levin, CEO of Regal to unpack what California’s new AI executive order really means for businesses deploying AI in customer-facing roles.
With nearly six years of experience building in the conversational AI space, Levin has been navigating questions of transparency, bias, and accountability long before regulators made them mandatory. For companies working directly with large enterprises and their end customers, the financial incentive to build safety into AI has always been self-evident. Getting it wrong, even once, has consequences that no compliance framework needs to spell out.
What makes Levin’s perspective particularly interesting is his candor around the growing patchwork of state-by-state AI legislation, and his concern that it’s quietly doing more damage than the problems it’s trying to solve.
He points to France and Italy as real-world examples of where well-intentioned regulatory frameworks have effectively pushed enterprises to pause AI adoption altogether, leaving consumers worse off in the process.
It’s a nuanced position in a debate that rarely makes room for one, and it raises genuinely important questions about whether fragmented regulation is the right tool for protecting people in AI-driven interactions, or whether it’s simply redirecting the risk.
Levin also outlines three industry principles he believes should form the foundation of any credible AI governance standard, covering disclosure, consumer control, and the question of what LLMs should and shouldn’t be allowed to retain about individual customers.
His distinction between personalisation built within a compliant customer profile versus personalisation baked into the underlying model itself is one of the more technically precise ideas to surface in this space right now.
With headlines about advanced LLMs gaining access to sensitive systems becoming increasingly common, it’s a line of thinking that deserves serious attention from anyone building or buying AI for customer experience.
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