What the hype promises 

You’ve probably heard the claims: AI in ITAM will transform everything from license management to compliance, making your job faster, smarter, and fully automated. In theory, that includes:

• Automated license optimization
• Zero-touch software usage tracking
• Contracts analyzed in seconds
• Forecasts that eliminate overspend
• Proactive compliance alerts

It sounds impressive. But the reality for most ITAM teams is still grounded in manual processes, spreadsheets, and rule-based tools. So what’s real today and what’s not?

Where AI in ITAM adds value today

Some capabilities are already delivering results, especially when built into modern ITAM tools:

Usage trend analysis
AI highlights underused software and flags optimization opportunities

Anomaly detection
It spots unusual asset behavior, such as sudden usage spikes or installs that don’t match user profiles

Data normalization
AI helps clean and categorize asset data, removing duplicates and fixing naming inconsistencies

Forecasting
Some tools predict future license needs based on historical patterns and renewal cycles

What’s still emerging

Some of the more advanced use cases are promising but not yet fully realized:

Natural language reporting
Early tools let you ask basic questions like “What licenses are unused?” but results vary

Contract analysis
AI can scan documents, but it still struggles with complex licensing terms or exceptions

Full end-to-end automation
Some tasks can be automated, but full lifecycle AI-driven ITAM? Not quite there yet

What you can do right now 

Even without deploying AI, there are practical steps you can take to future-proof your ITAM practice.

Start by improving data quality, ensuring asset records are clean, complete, and standardized so they can support smarter insights later. Look for opportunities to automate repeatable tasks, such as renewals and usage tracking, to reduce manual effort. Documenting your workflows is also essential, as clear and consistent processes are much easier to enhance with advanced technologies. At the same time, investing in flexible tools with strong integration capabilities will prepare your organization for future innovations. Finally, focus on upskilling your team, since a strong understanding of data and insights is critical to working effectively with AI rather than against it.

It’s real, but it’s evolving

AI in ITAM isn’t hype but it’s not a full revolution yet either. It’s a set of emerging tools that support what you already do: track, optimize, and protect your IT estate.