Tower's deployment of AI-enabled contact centre technology has delivered measurable efficiency gains, reducing customer call time by over 796,000 minutes. This outcome reflects a broader industry shift toward agentic AI systems that handle routine interactions autonomously, allowing human agents to focus on complex cases. The scale of time savings—equivalent to roughly 1,300 working days—demonstrates that AI integration in contact centres is moving beyond pilot phases into operational reality. Yet the headline metric masks a critical question for CX leaders: are these time reductions driven by genuine issue resolution, or simply by faster call deflection? The distinction matters because complete issue resolution remains the key to customer acceptance of AI-driven support, and efficiency gains that sacrifice first-contact resolution will ultimately erode customer satisfaction and increase repeat contacts.
Tower's results sit within a wider context of AI adoption reshaping contact centre staffing models. The efficiency gains align with documented job losses in AI-exposed customer service roles, signalling that organisations implementing these systems are fundamentally restructuring their teams rather than simply augmenting existing capacity. For CX professionals managing this transition, the challenge extends beyond technology selection—it requires rethinking agent roles, training pipelines, and performance metrics to reflect a hybrid human-AI operating model. The question facing support leaders is whether their current team structures and KPIs are designed to measure the right outcomes: if call time reduction becomes the primary success metric, organisations risk optimising for speed at the expense of the resolution quality that actually drives customer loyalty and reduces operational cost through fewer repeat contacts.
Tower’s AI-Enabled Contact Centre Cuts Customer Call Time By More Than 796,000 Minutes Scoop - New Zealand News