ServiceNow's latest research exposes a fundamental tension in AI-driven customer service: 53 percent of customers expect AI to improve speed and efficiency, yet 50 percent still cite lack of empathy as their top frustration. This is not a technology problem—it is an operational one. The research reveals that service agents spend only 45 percent of their time actually addressing customer issues, with 80 percent forced to log into three to five systems to resolve a single problem. That fragmentation creates the appearance of indifference. When agents cannot access customer context—whether someone has called three times, is making a high-value purchase, or is dealing with a sensitive life event—they sound detached regardless of intent. AI can address this, but only if it surfaces relevant history, summarizes interactions, and reduces administrative burden. The critical question for CX leaders is whether your current data architecture and workflow integration can support this. If agents remain middleware, manually connecting dots between disconnected systems, adding AI on top simply layers another tool onto an already fractured experience.
The strongest AI strategies will not replace agents; they will liberate them from work that prevents empathy. AI belongs in repetitive, transactional, information-heavy interactions—order tracking, account updates, summaries, routine requests. Humans remain essential for complexity, emotional stress, and high-value moments. Yet many organizations are chasing efficiency metrics without rethinking the experience. A utility provider's experience during a natural disaster illustrates the risk: AI reduced wrap-up time but increased talk time, leaving agents without natural pauses to recover during emotionally demanding calls. The business had to reintroduce space into the process. This reveals how AI can improve one metric while creating pressure elsewhere. For teams already running Agentforce or similar platforms, the implication is clear—measure success not by handling time reduction alone, but by whether agents can spend more time on complex cases, loyalty risks, and commercial opportunities. The shift from cost center to customer value engine depends on redeploying capacity, not simply cutting headcount.
The transition from reactive CRM to proactive, signal-driven service is where AI genuinely makes interactions feel more human. Traditional CRM records what happened; the next phase uses ongoing usage signals—subscription behaviour, device data, engagement patterns—to detect problems before customers escalate them. When a system surfaces context before a customer repeats themselves, the interaction becomes personal without relying on agent memory or manual effort. This requires connected data, integrated workflows, and deliberate choices about where AI assists, where it automates, and where people lead. For CX leaders, the priority is identifying where agents are forced to act as middleware, where customers repeat themselves, and where AI can remove friction without removing accountability. That is the foundation before pursuing autonomous CX at scale.
AI customer service is moving quickly, but customers are not asking brands to replace empathy with efficiency. That is the tension at the heart of ServiceNow’s latest CX research. According to The CX Shift, 53 percent of customers expect AI to improve speed and efficiency, while 50 percent still ci
AI Can Make Service Faster, But Can It Make It Feel More Human? CX Today