Photo By: Alexander Grey
As businesses face rising costs, growing technology complexity and the rapid adoption of AI, asset management is becoming increasingly important to financial performance, cybersecurity and better business decisions.
For many organizations, asset management has traditionally meant keeping track of what they own, from computers and software to machinery and buildings. Today, however, managing these assets is becoming more complex, with information often spread across departments and systems.
Without a clear picture of what they own, how assets are used and what they cost, businesses risk wasting money, overlooking security issues and missing opportunities to improve efficiency.
According to Anusha Das-Fedele, Global Strategist at NewRocket, asset management has evolved from a largely administrative function into a strategic business priority.
With more than 22 years of experience helping organizations improve how work gets done, Das-Fedele works with business and technology leaders to align processes, technology and organizational goals.
“Asset management has moved from siloed record keeping to wider visibility and decision support enterprise-wide,” she explains.
As cloud services, connected devices and software become more central to business operations, asset management increasingly involves IT, finance, procurement, facilities, security and operations.
Why asset management is a business issue
Traditionally, different departments have managed different types of assets. Finance has overseen major purchases, IT has managed computers and software, and facilities teams have looked after buildings and equipment.
But these responsibilities now overlap. Connected operational equipment can introduce cybersecurity risks, while poorly tracked software subscriptions can create unnecessary costs and compliance issues.
Organizations therefore need a joined-up view of their assets, including who owns them, how they are used and whether they remain secure and fit for purpose.
As Das-Fedele puts it, “You cannot optimize what you cannot see, and you cannot trust what you cannot measure.”
Without reliable information, leaders cannot confidently assess whether assets are delivering value or where improvements are needed.
The hidden cost of fragmented data
When asset information is spread across disconnected systems, businesses can end up purchasing equipment they already have, paying for unused software or missing essential maintenance.
Das-Fedele recalls supporting a client that faced software licensing penalties following a vendor audit. Procurement had purchased subscriptions, while IT had provisioned access. However, neither team had end-to-end responsibility for tracking usage and removing unnecessary licenses.
The result was avoidable spending and compliance exposure.
The example demonstrates why clear ownership matters. Managing assets effectively requires organizations to track them throughout their lifecycle, from purchase and use to maintenance and retirement.
How AI is changing asset management
Spreadsheets and manual processes can help businesses get started, but they often struggle to provide accurate, up-to-date information as asset portfolios grow. Outdated records can lead to unexpected repair costs, excess inventory, wasted software spending and inaccurate financial forecasts.
AI offers an opportunity to address these challenges by helping organizations identify patterns, anticipate problems and make better-informed decisions.
For example, AI can help predict equipment failures, identify unused software licenses, improve maintenance planning and bring together information from different departments. These capabilities can reduce waste and help businesses get more value from existing assets.
However, AI is only as reliable as the data it uses. Inaccurate or incomplete records can lead to poor recommendations, making data quality and clear accountability essential.
Das-Fedele also stresses the importance of human oversight. Low-risk tasks may be suitable for automation within defined limits, while decisions affecting cybersecurity, financial reporting, safety or regulatory compliance may require human approval.
Organizations need clear rules, transparent decision-making and accountability for AI-driven actions.
Building a stronger business case
To secure investment in modern asset management, businesses should focus on measurable outcomes rather than technology alone.
Das-Fedele highlights four key areas: reducing unnecessary capital spending, improving operational efficiency, managing security and compliance risks, and making better purchasing and inventory decisions.
By establishing a clear picture of current costs and weaknesses, organizations can identify where value is being lost and estimate how better asset management could improve performance.
This helps position asset management as a business investment rather than simply an IT project.
From tracking assets to creating value
As organizations continue to adopt new technologies and AI, asset management is becoming central to how they control costs, manage risks and plan for the future.
For CIOs, CFOs and operations leaders, the question is no longer simply what the business owns. It is whether those assets are delivering value, creating unnecessary costs or introducing risks.
As Das-Fedele emphasizes, asset management is a strategic discipline that helps leaders make better decisions about investment, security and operational resilience.
With connected data, clear ownership and appropriate governance, organizations can move beyond basic tracking and use asset management to make smarter decisions across the business. Ultimately, organizations that treat asset management as a strategic priority will be better positioned to control costs, reduce risk and turn their assets into a lasting competitive advantage.
