By Venus Mehta, IT Director - Software Asset Management - Cummins Inc., United States
In the ever-evolving landscape of IT management, one thing is clear: the future will be defined by software, data, and AI. While many industries are being transformed by the digital revolution, it’s Software Asset Management (SAM) that stands at the crossroads of this shift. As organizations embrace cloud technologies, AI-driven tools, and data-driven decision-making, the traditional ways of managing software and costs are rapidly becoming obsolete. The time to prepare for these changes is now, and those who fail to adapt will risk being left behind.
The Evolving Landscape of Software and Licensing
Looking into the future, we can expect software to evolve into a far more dynamic and flexible entity than it has been in the past. As we move further into the world of cloud computing and Software-as-a-Service (SaaS), traditional on-premises licensing models are giving way to subscription-based and consumption- based models. This shift is not just a trend; it’s a fundamental change that will influence how organizations manage software costs and compliance.
In the next five to ten years, we can anticipate even more complex and personalized licensing models. Companies will no longer just "buy" software; instead, they will rent and subscribe to software that adjusts in real-time to their usage and needs. AI-powered licensing models will likely become the norm, with systems capable of adjusting costs based on usage patterns, predicted future needs, and even the efficiency of software deployments. Gone will be the days of static, per-user or per-server licenses. The software market will become much more adaptive, and managing these costs will require a new level of precision and agility.
SAM will no longer be a reactive process where organizations simply ensure they are compliant with licensing rules. Instead, AI-enhanced SAM will be a proactive, strategic tool that helps organizations predict software consumption patterns, optimize licensing strategies, and minimize financial risks. The challenge for today’s businesses is to prepare for this transformation—by implementing the right tools, processes, and skills now, they can ensure that they are ready for this dynamic future.
The Role of AI in Software Management
Artificial intelligence (AI) will be the cornerstone of this transformation. As software becomes more complex and data-driven, AI will be the only tool capable of managing the immense scale of information that organizations will generate. AI will take over many of the repetitive, manual tasks traditionally associated with SAM, such as inventory management, license tracking, and compliance monitoring.
However, the impact of AI won’t stop there. Predictive analytics powered by AI will provide organizations with the ability to forecast software needs, optimize renewals, and even predict the financial impact of software-related decisions before they’re made. Machine learning algorithms will analyze historical consumption data and apply this insight to predict future needs, identify cost-saving opportunities, and detect potential compliance risks before they become problems.
Moreover, AI will act as the intelligent interface between software vendors and organizations, enabling businesses to negotiate better contracts, customize licensing plans, and ensure they are getting the best value for their money. With AI-driven negotiation tools, organizations will no longer need to rely on guesswork or outdated models for contract renewal. Instead, they will have real-time data and AI-backed insights to guide them, improving both financial and operational outcomes.
Data as the New Currency
As software and AI continue to reshape the business landscape, data will become the driving force behind all decisions. For SAM, data will be at the heart of optimizing software portfolios and managing software costs. Every interaction, from employee usage to vendor contracts, will generate data that can be leveraged to make smarter, more informed decisions.
The critical data points in SAM will go beyond just tracking software installations or usage. In the future, real- time data feeds will allow SAM teams to monitor usage patterns, assess software performance, and adjust consumption on the fly. As data governance becomes increasingly important, organizations will need to implement comprehensive data management strategies to capture, store, and analyze this data securely and effectively. Data quality will become just as important as the data itself, as companies will rely on this information to inform critical business decisions.
For SAM teams, this data will also play a crucial role in forecasting. AI-powered analytics tools will empower SAM managers to analyze usage trends and forecast future software needs, enabling organizations to be proactive rather than reactive in their purchasing and licensing strategies. Data integration between software tools, vendors, and internal systems will be essential for providing the comprehensive insights needed to manage software assets effectively.
Preparing for the Future: Steps Organizations Must Take Today
While the future of software management may seem far off, the reality is that the changes we’re describing are already happening. To stay ahead of the curve, organizations must take strategic steps now to prepare for this future:
The future of Software Asset Management is one where AI and data intersect to create smarter, more efficient systems for managing software costs and ensuring compliance. As organizations move toward more flexible licensing models and become increasingly reliant on AI-powered tools, the role of SAM will evolve from a reactive process to a proactive, strategic function. Those who begin preparing today—by adopting the right tools, data strategies, and skills—will position themselves for success in the rapidly changing world of software management. The future is fast approaching, and the question is: Will your organization be ready?
