Managing IT infrastructure is increasingly complex, making IT Asset Management (ITAM) crucial for overseeing assets from acquisition to disposal. ITAM ensures optimal utilization and alignment with business objectives. AI in the asset management market, valued at USD 3.4 billion in 2024, is projected to grow significantly. AI’s role in ITAM includes tracking, procurement, utilization, and disposal, impacting cost control, compliance, risk management, productivity, and strategic planning. Accurate record-keeping enhances efficiency and reduces costs and risks.
Modern IT’s complexity, with diverse environments and assets like hardware, cloud services, and IoT, renders traditional ITAM inadequate. This leads to inefficiencies, security vulnerabilities, and higher costs, with millions lost due to underutilized software. AI offers a transformative solution by automating and optimizing ITAM processes, enhancing efficiency, reducing costs, and improving compliance. AI provides automation, better visibility, predictive capabilities, and improved decision-making. The shift to remote work accelerated the adoption of sophisticated ITAM software.
Recent data indicates a significant rise in AI and ML adoption in ITAM. By February 2025, 77% of organizations had embraced these technologies. However, a Deloitte survey shows that less than a third of AI experiments reach production. This highlights a growing recognition of AI’s potential, but full-scale implementation and talent development are still evolving.
Quantifiable benefits: Why is AI important for IT asset management
AI integration in ITAM offers significant benefits in cost optimization, efficiency, and security.
Cost optimization: AI enhances visibility into resource use and recommends optimization, potentially reducing operational costs by 30%, as reported by Gartner. AI analyzes usage to identify underutilized licenses and cloud resources, suggesting cost-saving alternatives and optimizing hardware upgrades. It also automates recycling and tracks environmental impact.
Boosting efficiency: AI-enabled ITAM automates tasks like inventory tracking, license management, and compliance reporting, freeing up IT teams. AI accelerates asset tracking, eliminates manual errors, and identifies underutilized resources for optimal allocation. Real-time asset discovery across diverse environments provides comprehensive visibility.
Strengthening security: AI proactively identifies vulnerabilities, detects threats, and ensures continuous compliance monitoring. It helps pinpoint weaknesses and recommends security patches. AI-driven anomaly detection identifies unauthorized access and monitors adherence to security protocols. Predictive capabilities help anticipate risks from outdated software.
Additional Read: Reducing Your Organization’s Carbon Footprint with Smart SAM
Key AI capabilities in ITAM
AI integration brings powerful capabilities to ITAM.
Predictive analytics: AI algorithms monitor asset performance in real-time, flagging potential issues and allowing for proactive problem-solving. By analyzing historical data, AI forecasts future asset needs and anticipates hardware failures or software vulnerabilities, enabling proactive servicing and cost reduction. Generative AI can also analyze support ticket trends for optimized procurement.
Anomaly detection: AI algorithms continuously monitor asset performance and usage, flagging unusual patterns that could indicate malware or security threats. AI-based systems provide context around anomalies, such as unusual connection requests or network traffic. In cybersecurity, AI-powered Intrusion Detection Systems analyze network traffic for suspicious activities.
Automated asset discovery: AI-powered tools automatically scan networks to identify and catalog all connected devices and software, ensuring a complete inventory with detailed specifications. This enhanced visibility supports informed decisions on resource allocation and security. Agentic GenAI proactively scans networks and cloud environments for real-time asset identification, including shadow IT.
The partnership between OpenLM and ServiceNow exemplifies AI-driven asset discovery, improving asset visibility and optimizing license usage.
Additional Read: Managing Software in the Multisite and Hybrid IT Environments of 2025
Challenges and opportunities: What are the future trends in AI and asset management
While AI in ITAM offers crucial benefits, it also comes with certain challenges. Data privacy is a primary concern, requiring compliance with regulations. A shortage of skilled personnel necessitates investment in training. Integrating AI with existing infrastructure can be tricky as it requires careful planning. Initial costs can be a barrier, especially for SMEs. Finally, data quality is critical for reliable AI outcomes.
AI integration offers substantial opportunities for innovation and IT management improvements, including enhanced automation and business intelligence. AI solutions can be customized for specific needs and are designed for seamless integration. AI’s analytical power provides valuable insights, and automation frees up IT teams for strategic initiatives.
Experts agree that AI will increasingly shape ITAM’s evolution, augmenting ITAM professionals’ capabilities. AI will handle routine tasks, allowing experts to focus on strategic planning and governance. Key areas like data reconciliation and compliance reporting will be significantly enhanced. New roles like “orchestrator of AI ITAM agents” are anticipated. ITAM professionals will need to develop new skills to leverage AI effectively.
Conclusion
AI integration into ITAM is no longer the future. It is here already, and it presets the asset management landscape for the next decade. Starting our GenAI journey with co-pilot models, now we are at the age of AI agents augmenting the ITAM and ITSM landscape. Furthermore, the strong market outlook reinforces the growing importance of AI in enabling more effective, strategic, and secure asset management.
