Enterprise AI Adoption Outpaces ITAM Readiness, New EMA Research Finds

EMA's survey of 203 IT professionals found that 71.9% of respondents reported broad operational AI adoption or beyond, while only 22.2% said their IT asset management function was AI-ready. Among respondents in the AI-ready group, 62.2% used runtime asset data, versus 9.4% in the group reporting optimized ITAM practices. The report identifies statistically significant differences in capabilities and argues that trusted, timely asset data is increasingly important for AI-enabled operations.

Analysis

The investable signal is not near-term AI software demand; it is a potential shift in enterprise spending toward the data plumbing that makes automated operations governable. If asset records cannot capture changing cloud, SaaS, container, model and dependency relationships, AI-driven change and remediation carry greater operational and security risk. That could support incremental demand for IT asset management, configuration management, IT service management, FinOps and observability tools—and implementation work to reconcile fragmented records. The value may accrue to broad platforms such as ServiceNow, IBM and BMC as much as to specialist vendors: buyers may prefer integrated workflows over another point product. This is a conditional mechanism, not evidence of revenue acceleration.

The survey is small, self-reported and sponsored by Virima and Xurrent. Statistical association between reported readiness and other capabilities does not establish that ITAM maturity causes better AI outcomes or budgets. The contrarian risk is that enterprises address the gap with internal data engineering and existing platform modules, limiting standalone vendor upside; budget competition or prolonged data cleanup could also delay purchases. Near term, the November 3 webinar is not a material catalyst. Over 1–3 months, watch for vendor commentary on ITAM/CMDB, FinOps and AI-governance bookings, deal sizes and implementation duration. Over 6–18 months, the structural case strengthens only if customers fund recurring, cross-functional asset-data programs rather than pilots. No immediate sector trade is warranted from this release alone.

Key Decisions for Investors

• No trade on the survey alone. Treat it as a diligence prompt, not evidence of broad enterprise spending or a near-term earnings inflection.
• Put ServiceNow, IBM and BMC on a watchlist for earnings commentary linking AI operations to paid asset/configuration data, FinOps or governance modules. Consider exposure only if disclosed customer adoption and monetization—not product announcements alone—support the thesis.
• For a 1–3 month catalyst check, track ITSM/ITAM vendor bookings, renewal expansion, implementation backlogs and customer references for runtime or dependency-aware asset data. Verify whether spend is incremental or bundled into existing contracts.
• Falsify the bullish vendor thesis if subsequent results show AI-related module attach or cross-sell weakening, implementation cycles lengthening without recurring revenue conversion, or buyers relying on internal tooling and existing platform entitlements.