Quiq appoints Jen Grant as CMO as the enterprise AI agent market shifts from experimentation to scale—and the real competition shifts to trust and execution.
There’s a moment in every enterprise software cycle when the question stops being “does this work?” and starts being “which vendor do we trust?” Quiq, the enterprise AI agent platform, is betting it has reached that moment — and it’s hired accordingly.
The company has appointed Jen Grant as Chief Marketing Officer, a hire that reflects more on building awareness than on winning a market that is rapidly consolidating around a handful of credible platforms. Grant brings executive experience across CEO, COO, and CMO roles at companies including Box, Elastic, Looker, Dialpad, and Google.
The Shift From Experiment to Production
The backdrop to the hire is a genuine inflection in how enterprises are approaching AI agents. The experimentation phase — pilots, proofs of concept, carefully scoped demos — is giving way to something with higher stakes: live, customer-facing deployments at scale, where failures are visible, consequences are real, and the tolerance for unreliability is close to zero.
Quiq’s AI agents are already running in production for global brands including Spirit Airlines, Roku, and Panasonic — handling high volumes of customer interactions in environments where accuracy, compliance, and brand governance are non-negotiable.
“We evaluated over 30 different vendors,” said Matt Feinstein, Director of Product Management at Roku. “Many presented generic solutions and demos. Quiq showed us they could address our needs — and they have.”
That kind of reference is what separates a platform claim from a market position. And the market position is what Grant is being hired to build.
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What the CMO Role Actually Signals
“Most companies are no longer asking whether AI agents work — they’re asking which platforms they can trust in front of customers,” Grant said. “This is the phase where execution and clarity matter more than promise. Quiq is already running AI agents in production at massive scale, and my role is to help the market understand what’s real, what’s different, and how to deploy AI responsibly.”
Mike Myer, Quiq’s chief executive, was direct about the sequencing. “Quiq has moved past experimentation and into real, scaled AI agent deployments, and that shift requires a different kind of leadership,” he said. “Jen is joining because the technology is already proven in production environments.”
That framing — CMO as market-definition hire rather than demand-generation hire — is telling. In maturing enterprise categories, the companies that win are rarely the ones with the best product at the moment of consolidation. They’re the ones with the clearest story about why their approach is the right one.
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The Trust Problem at the Center of It All
The practical challenge Grant is walking into is one that every enterprise AI vendor is grappling with: hallucination risk. When AI agents are operating in customer-facing environments on behalf of regulated industries or brand-sensitive companies, a single confident wrong answer can cause real damage.
Quiq’s platform includes built-in verification and control mechanisms designed to keep agent responses grounded in trusted data — a capability that has become table stakes for any serious enterprise deployment, but one where implementation quality varies significantly across vendors.
Grant’s job, in part, is to make that distinction legible to buyers who are increasingly sophisticated about what questions to ask, but still navigating a market where vendor claims and vendor reality don’t always align.
The enterprise AI agent category is real, it is growing, and it is beginning to sort itself into tiers. Quiq is making a clear statement about which tier it intends to occupy.
