Fisher & Paykel's strategic pivot reveals a fundamental recalibration in how enterprises should think about AI investment. Rather than treating AI as a cost-reduction mechanism confined to support operations, the appliance manufacturer is repositioning it as infrastructure for customer discovery and journey convergence. Chief digital officer Rudi Khoury's framing is deliberate: customer behaviour has already shifted toward using generative AI systems as research interfaces, which means the traditional boundaries between discovery, service and conversion are collapsing. This is not a new deployment pattern—it is a recognition that when customers research products through GPT-style tools before reaching a brand's owned channels, visibility becomes a knowledge problem rather than a media problem. The implication for CX teams is immediate: your service infrastructure may already be functioning as part of the purchase journey, whether your organization has acknowledged it or not. The question becomes whether teams running Agentforce or similar platforms are treating their agents as isolated support systems or as customer-journey infrastructure that marketing, commerce and product teams should actively shape.
The operational consequence is that brand accuracy has become a CX and marketing accountability issue simultaneously. When an AI intermediary assembles answers across multiple systems and sources, inconsistencies between what service, product and marketing teams maintain become visible failures in real time. Fisher & Paykel's approach—monitoring agent performance, identifying knowledge gaps and testing responses—suggests that AI autonomy creates management work rather than eliminating it. This challenges the efficiency-first logic that typically drives AI adoption. Instead, Khoury argues that investment decisions should follow customer behaviour rather than vendor capability roadmaps. For support team leads and CX consultants, this means the strategic tension is no longer between automation and human touch; it is between treating AI as a departmental tool versus treating it as shared infrastructure that requires cross-functional governance. Content governance, product data accuracy and information architecture are now operational CX concerns, not downstream marketing problems.
The practical shift requires organizational alignment that most enterprises have not yet built. A customer asking an agent about product dimensions, compatibility or feature differences may be conducting research, seeking support or moving toward purchase—the interface remains conversational while commercial intent shifts underneath. This creates ownership ambiguity that traditional CX platforms were not designed to resolve. Teams need to ask whether their current systems can surface when a support interaction is actually a discovery moment, and whether marketing, ecommerce and service teams have aligned on what information is authoritative. The brands that adapt well will not succeed through better prompts or additional dashboards; they will succeed by ensuring that marketing, service, commerce and product information are consistent enough that an AI intermediary can represent the business accurately without creating confusion. For CX professionals, this means the role of customer service is expanding beyond issue resolution into brand representation—a shift that demands different metrics, different governance and different cross-functional relationships than most organizations currently maintain.
Fisher & Paykel shifts AI toward brand discovery ContentGrip