Iron Mountain says retired IT assets can fund AI projects

Iron Mountain says Australian organisations are using value recovered from retired IT assets to help fund artificial intelligence projects.

Its research found 17% are already doing so.

The findings highlight a funding option for companies trying to expand AI spending while managing tighter technology budgets. Businesses with more than 5,000 employees could recover more than USD $1 million from retired technology assets and redirect that money into AI tools and infrastructure.

The research found 27% of organisations rely on new capital allocation for AI investment, while 24% use departmental funds. By contrast, formal recovery of IT spending is less common, even though industry benchmarks suggest organisations can reclaim 10% to 30% of initial hardware costs when IT asset disposition is treated as a budget recovery programme.

For larger businesses, the report modelled potential reclaimed value of USD $1.2 million. That reflects possible resale, recycling and recovery value from decommissioned technology as businesses replace equipment more frequently to support AI-related workloads.

Refresh cycles

The shift towards AI is changing enterprise technology refresh cycles, with businesses replacing infrastructure sooner to prepare for higher computing demands. In turn, that is increasing attention on what happens to servers, storage equipment and other hardware after they leave active use.

Iron Mountain described asset lifecycle management as a broader process that includes asset tracking, secure data destruction, resale and recycling, rather than disposal alone. It said this approach can give organisations more oversight of retired equipment and a clearer path to recovering financial value.

Erica Hirsch, Senior Vice President, Asset Lifecycle Management, Iron Mountain, said: "The AI investment conversation tends to focus on what businesses need to buy next, but there is another side to the equation. Organisations should also understand what value is sitting in the technology they already own and how that can be recovered as their IT estate evolves."

Sustainability pressure

The research also highlighted concern about the environmental cost of AI expansion. It found 71% of organisations are worried that AI's energy demands could conflict with ESG or broader sustainability targets.

That adds another layer to decisions about technology replacement and disposal. Companies face pressure not only to finance AI projects, but also to show that older equipment is being reused, recycled or retired in ways that support environmental commitments.

In that context, the handling of retired hardware is moving beyond operational housekeeping into mainstream budgeting and sustainability planning. The report suggests some organisations now view end-of-life technology as a source of recoverable value rather than solely a cost centre.

Budget choices

The figures also show that recovered IT spending still trails more traditional sources of AI investment. New capital allocation remains the most widely used source among those surveyed, followed by departmental funding, indicating that most businesses still depend on standard budgeting routes when backing AI projects.

Even so, the use of reclaimed spending suggests some organisations are trying to offset part of the cost of AI adoption through existing assets rather than entirely through fresh budget requests. That may appeal to technology and finance teams under pressure to show returns on AI spending while limiting additional outlay.

Iron Mountain operates in information management and serves more than 240,000 customers across 61 countries. It said the combination of capital recovery, secure disposal and sustainability is becoming more relevant as companies review their infrastructure needs in response to AI.

Hirsch said: "AI is changing the economics of the IT lifecycle. The opportunity is to connect technology refresh with capital recovery, security and sustainability, turning the end of one asset's life into part of the investment case for the next."