Vertiv Launches AI-Based Predictive Maintenance for Data Centers and AI Factories
Vertiv has introduced Vertiv Next Predict, a managed service that shifts data center maintenance from routine calendars to condition-based decisions. It analyzes asset behavior in near real time, flags risks before they turn into downtime, and prescribes actions your team can execute or hand off to Vertiv Services.
The goal is simple: fewer surprises, tighter control, and better use of field time and spare parts. For operations leaders, that means higher availability, cleaner workflows, and clearer accountability across distributed sites.
How Vertiv Next Predict Works
- Anomaly detection: AI models monitor equipment behavior and surface deviations early.
- Risk scoring: A predictive algorithm estimates operational impact and prioritizes response.
- Root cause analysis: The system isolates likely contributors to speed resolution.
- Prescriptive actions: Based on live data and context, the service recommends and executes corrective steps via Vertiv Services technicians.
"Vertiv Next Predict helps data centers unlock uptime, shifting maintenance from traditional calendar-based routines to a proactive, data-driven strategy," said Ryan Jarvis, vice president of the global services business unit at Vertiv. "We move from assumptions to informed decisions by continuously monitoring equipment condition and enabling risk mitigation before potential impacts to operations."
Where It Fits in Your Stack
The service covers a broad-and growing-set of Vertiv platforms across electrical and thermal infrastructure. That includes battery energy storage systems (BESS) and liquid cooling components.
It's built with scale in mind, aligning to a unified "grid-to-chip" service architecture so new technologies can slot in without a rework of process or data flows.
Why This Matters for Operations
- Reduce unplanned outages by catching degradation early.
- Shift labor from routine rounds to targeted interventions.
- Improve spare parts planning with data-backed forecasts.
- Standardize playbooks across sites for consistent execution.
As AI loads increase compute intensity and heat, tight visibility across electrical, cooling, and IT support systems becomes essential. Predictive maintenance is a proven way to reduce downtime and cost in industrial environments; similar principles now apply at data center scale. For context on outage trends and operational risk, see Uptime Institute's analysis here.
What Ops Leaders Can Do Next
- Map critical assets to failure modes and maintenance tasks you'd want to automate or prioritize.
- Integrate telemetry from UPS, switchgear, BESS, CRAC/CRAH, and liquid cooling to enable complete context.
- Feed work orders to your CMMS/ITSM so prescriptions become tracked actions with SLAs.
- Define KPIs: MTBF/MTTR, maintenance deferrals, spare turns, and outage avoidance value.
- Set governance: change control, access, and data security between your sites and service partners.
- Upskill technicians on interpreting alerts, executing prescriptive steps, and validating fixes.
Execution and Support
Vertiv Services brings global field coverage and AI-backed analytics to handle corrective work when you need extra hands. That combination-continuous monitoring, clear prescriptions, and qualified technicians-shortens the loop from detection to resolution.
If your team is building skills for AI-enabled operations, explore practical training paths by job function here. Focus areas: data literacy for technicians, anomaly interpretation, and workflow automation.
Bottom Line
Vertiv Next Predict gives operations leaders a direct way to move from scheduled maintenance to condition-based decisions across electrical and thermal systems. Fewer blind spots, faster fixes, and a service model that scales with your sites and future tech.
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