New Relic Names ServiceNow Veteran Brian Emerson Chief Product Officer, Doubling Down on AI and Intelligent Observability

New Relic named Brian Emerson Chief Product Officer to lead its observability platform and product strategy. Ex-ServiceNow exec, he'll focus on AI features and deeper integrations.

Categorized in: AI News Product Development
Published on: Oct 22, 2025
New Relic Names ServiceNow Veteran Brian Emerson Chief Product Officer, Doubling Down on AI and Intelligent Observability

New Relic names Brian Emerson Chief Product Officer

New Relic has appointed Brian Emerson as Chief Product Officer, placing him in charge of the Intelligent Observability Platform and the company's product strategy. He will report to CEO Ashan Willy and lead the product management team, with a remit that includes new platform capabilities and partner integrations.

Emerson brings more than 25 years of product leadership across software and cloud platforms. Most recently, he served as Group Vice President and General Manager at ServiceNow, where he helped scale the IT Operations Management business, growing revenue ninefold during his tenure. He has also held senior product roles at VMware, BMC Software, and Remedy.

Platform momentum and product direction

New Relic has shipped more than 25 features to its platform over the past year. The aim: give product and engineering teams a unified view across infrastructure, applications, and AI pipelines so they can move faster with fewer blind spots.

The platform is used by roughly 85,000 customers worldwide and was named a Leader in the 2025 Gartner Magic Quadrant for Observability Platforms for the 13th consecutive time. Gartner highlighted the platform's vision and execution, including support for AI-strengthened workflows. For market context, see Gartner's observability market coverage.

Why this matters for product development

  • AI-first workflows: Expect stronger ties between telemetry, LLM-driven assistance, and proactive issue detection to cut MTTR and reduce toil.
  • Unified data: A clearer path to correlate release events, performance regressions, cost signals, and user impact in one place.
  • Ecosystem depth: More partner integrations can reduce glue code and help standardize instrumentation across teams.
  • Roadmap clarity: Product strategy led directly under the CEO often means tighter alignment of customer needs with delivery.
  • AI pipeline visibility: Monitoring model performance, drift, and dependencies becomes part of standard observability, not an afterthought.

What leadership is saying

Ashan Willy, CEO of New Relic: "Brian joins New Relic at a critical time as we accelerate our mission to empower organisations to thrive in an AI-first world. With his exceptional track record leading product management at successful global IT operations and cloud companies, Brian is the ideal executive to drive our innovation as we stay ahead of customer needs."

Brian Emerson: "New Relic has differentiated itself in the market by making observability intelligent and proactive, saving businesses invaluable time and money. The opportunity to lead a world-class product team and bring new capabilities to the company's renowned platform is incredibly exciting. I look forward to partnering with the executive, product and engineering teams to help our customers move their businesses forward."

Industry context

As companies shift more workloads to cloud and distributed systems-and add AI to the stack-observability has become a baseline capability for product delivery. Emerson's background scaling ServiceNow's IT Operations Management business suggests a playbook focused on measurable outcomes, go-to-market alignment, and product velocity.

Action checklist for product teams

  • Map your critical user journeys to telemetry and alerts; tie them to business KPIs and cost targets.
  • Instrument AI pipelines: data lineage, model versions, latency, quality, and drift.
  • Standardize on shared dashboards for releases, incidents, and customer impact; remove redundant tools.
  • Audit partner integrations you rely on and flag gaps for the vendor roadmap or your own backlog.
  • Set quarterly success metrics: MTTR, change failure rate, release lead time, and cost per transaction.
  • Plan a short POC around a high-noise service to test proactive detection and AI-assisted remediation.

Skills and next steps

If your team is leaning into AI-backed telemetry and experimentation, upskilling helps. Explore practical options by role here: AI courses by job.


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