AI-powered gains in service, resolution, and efficiency
Part of AI economic impact analysis conducted by SummitAI
This analysis is part of a broader AI economic impact report produced by SummitAI that models the potential business value of AI based on real-world deployments. All figures presented here are directional estimates, derived from documented customer outcomes and calculated using conservative, logic-based scaling.
Summary insight
Enterprise IT teams are deploying AI to improve service delivery, security monitoring, and infrastructure efficiency. The following findings are based on results from deployments in ticket auto-resolution, predictive incident management, resource optimization, and security threat detection. These outcomes are extrapolated to similar IT environments to estimate the potential impact.
The analysis for this report focused on the following use cases:
-
Ticket auto-resolutionAI detects recurring IT issues and applies known fixes without human intervention.
-
Incident predictionModels forecast service disruptions based on performance metrics and system logs.
-
Resource optimizationAI allocates compute, storage, and network resources based on demand patterns.
-
Security monitoringAI correlates threat indicators across systems to detect and prioritize security incidents.
-
User supportVirtual assistants handle routine service requests and escalate complex issues to support teams.
Key modeled findings
Estimated global market-level value
$19.4B annually
based on current deployment outcomes across global mid- and large-sized enterprises.
Impact category breakdown
Modeled value per organization
Organizational impact snapshot
Annual economic value for a tier 1 enterprise.
Assumes global IT operations, 100K+ employees.
A large enterprise applying AI to core IT operations could realize up to $34M in annual business value, primarily from automation, faster resolution, and improved end-user support.
Annual impact estimate
These modeled gains reflect sustained operational benefits from embedded AI systems. In production environments, organizations report resolving up to 42% of tickets automatically, with substantial reductions in average handle time and increased service quality.
Analyst validation: Forrester TEI study
A Total Economic Impact™ (TEI) study conducted by Forrester Consulting examined SummitAI’s IT Service Management platform in a real-world enterprise setting.
Key findings include:
These results support the modeled outcomes in this report, particularly in areas of resolution speed, automation, and IT team efficiency.
Market-level model
Enterprise counts (Global estimates)
Breakdown by category
Total market impact estimate: $19.4B annually