How can AI and machine learning improve software license management?

1 Automate license discovery and inventory

One of the first steps in software license management is to discover and inventory all the software assets in your organization. This can be challenging, especially if you have a large and diverse IT environment with multiple platforms, devices, and vendors. AI and ML can help you automate this process by scanning your network, identifying your software products, versions, and licenses, and creating a centralized and accurate inventory. This can save you time, resources, and manual effort, as well as ensure that you have a clear visibility of your software assets.

2 Analyze license usage and optimization

Another key aspect of software license management is to analyze how your software assets are being used and whether they are optimized for your business needs. This can help you avoid over-licensing or under-licensing, which can lead to wasted spending or compliance issues. AI and ML can help you analyze your license usage and optimization by collecting and processing data from various sources, such as user activity, performance, configuration, and contracts. AI and ML can then provide you with insights and recommendations on how to improve your license utilization, allocation, and efficiency.

3 Predict license demand and renewal

A proactive and strategic approach to software license management is to predict your future license demand and renewal needs. This can help you plan your budget, negotiate better deals, and avoid surprises or penalties. AI and ML can help you predict your license demand and renewal by using historical data, trends, and patterns to forecast your software consumption, growth, and requirements. AI and ML can also alert you of upcoming license expiration dates, renewal options, and potential savings or risks.

4 Monitor license compliance and audit readiness

One of the major challenges and risks of software license management is to ensure that you are compliant with the terms and conditions of your software contracts and licenses. Non-compliance can result in fines, legal actions, or reputational damage. AI and ML can help you monitor your license compliance and audit readiness by comparing your actual software usage with your entitlements, detecting any discrepancies, violations, or anomalies, and generating reports and evidence. AI and ML can also help you simulate and prepare for audits, as well as respond to audit requests or claims.

5 Enhance license security and governance

Software license management is not only about managing your software assets, but also about protecting them from unauthorized access, misuse, or theft. Software piracy, hacking, or malware can compromise your software security and expose you to cyberattacks or data breaches. AI and ML can help you enhance your license security and governance by enforcing policies, rules, and controls on your software access, distribution, and activation. AI and ML can also help you detect and prevent any suspicious or malicious activities on your software licenses, such as tampering, copying, or sharing.

6 Integrate license management with other systems

Software license management is not an isolated function, but rather a part of a larger IT ecosystem that involves other systems, such as asset management, service management, procurement, finance, and security. Integrating your software license management with these systems can help you streamline your workflows, improve your data quality, and increase your efficiency and effectiveness. AI and ML can help you integrate your license management with other systems by enabling data exchange, automation, synchronization, and collaboration. AI and ML can also help you leverage the capabilities and insights of these systems to enhance your software license management.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?