First Contact Resolution (FCR)
A traditional support metric measuring the percentage of customer issues resolved during the first interaction without requiring follow-up. In AI-first support models, FCR's relevance shifts as AI handles straightforward queries and human agents focus on complex, multi-touch issues.
How FCR Changes in AI-First Models
Historically, FCR was a key performance indicator for support teams, with higher rates indicating efficiency and customer satisfaction. However, when AI Agents resolve the majority of simple, one-touch queries, human agents are left handling edge cases, sensitive issues, and complex problems that often require multiple interactions by nature.
As a result, FCR for human agents naturally drops in AI-first organizations—but this reflects increased complexity of work, not decreased performance. When AI is handling the bulk of one-touch resolutions, a lower human FCR is actually a sign that the system is working correctly, with humans focused on issues that genuinely require their expertise.
What to Measure Instead
Rather than using FCR as a primary KPI for human agents in AI-first models, teams should focus on outcome-based metrics like resolution quality, customer satisfaction on complex issues, and the value-add of human involvement. For AI Agents, resolution rate serves as the direct equivalent—measuring whether issues are fully resolved without human intervention.
FCR remains relevant as a system-level metric (measuring whether customers get help without repeat contact), but it should be measured across the entire AI-human collaboration, not used to penalize human agents for taking on inherently complex work.