Our takeaways from a Forrester report: AI requires a rethink in Software Asset Management

If you're in the business of managing software assets, you know that Software Asset Management (SAM) isn't a walk in the park. It's a complex, ever-evolving beast that demands a meticulous approach. According to a recent Forrester report[1] the advent of “generative AI (GenAI) and integrated asset management are forcing a SAM rethink”.

Gone are the days when SAM was just about keeping records in the back office. Today, it's all about managing licenses and contracts, optimizing tech usage, and reducing costs. It's not just a one-time thing for audits or contract renewals. SAM is a continuous process that helps companies keep track of their software assets, understand entitlements, and manage cloud licenses.

Successful SAM implementations can save license costs, improve compliance, and reduce true-ups. They also help in better software utilization, eliminating unused or unfit applications, and improving vendor relationships. But to truly maximize the business value of SAM, firms need to shift their focus. It's no longer just about software audits and license compliance; it's about usage management, security, risk management, cost optimization, and deriving business value.

Embrace GenAI and ML for SAM

“SAM tool deployments turn into disasters when they are implemented in silos, aren’t integrated with other related tools”, the Forrester report says. The report indicates that the future of SAM lies in integrating GenAI and machine learning (ML) technologies. These innovations can transform how you manage contracts, monitor compliance, and make informed asset management decisions.

Forrester identifies the following use cases that will have the potential to boost SAM value:

• GenAI for Contract Lifecycle Management: GenAI can automate various contract lifecycle management steps, from drafting to monitoring. It helps create and modify contracts quickly, ensuring they comply with organizational policies and regulatory requirements. “SAM vendor USU already supports AI-based invoice and end-user license agreement recognition”.

• ML for Compliance Monitoring: ML tools can scrutinize contracts to identify compliance risks, predict license violations, and optimize procurement decisions. By correlating software usage data with entitlements and license terms, ML can help prepare for audits and identify potential gaps.
  
  
• Intelligent Chatbots: GenAI-powered chatbots can offer personalized recommendations for asset management decisions. They understand user queries in natural language and can provide tailored responses based on user preferences, historical interactions, and contextual data.

Conclusion

SAM is a challenging yet vital part of IT asset management. By focusing on well-established SAM disciplines such as vendor management, compliance, optimum utilization, and maintaining a comprehensive technology catalog, you can maximize the business value of your SAM efforts.

With the integration of GenAI and ML, you can supercharge your SAM processes, making them more efficient and effective. So, embrace these technologies and get ready to take your SAM to the next level.

If you’d like to learn more about leveraging USU’s AI-based technologies for your SAM processes, feel free to reach out.

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[1] Forrester (2024): Why You Must Rethink Your Software Asset Management Practices