IDC white paper: The intersection of AI and IT sustainability

As organisations pivot to capitalise on Generative AI (GenAI) technologies, they are investing in the requisite IT infrastructure across the IT estate, from cloud to datacentres and end user devices such as desktops and notebooks. At the same time, organisations are identifying assets for end of use, decommissioning, reuse and cascading to accomplish financial and sustainability goals – bringing IT asset lifecycle management to the forefront of the intersection between AI and sustainability.

IDC research shows that even though a vast majority of organisations include IT recycling and asset disposition within sustainability policy and initiatives, most enterprises are struggling to implement an asset lifecycle management strategy that includes planning, deployment, optimising ongoing operations, and efficient, sustainable disposition practices to manage end of life, including reuse and recycling. In addition, most IT organisations have prioritised data security and governance across the lifecycle as a critical requirement for asset lifecycle management. For help, CIOs, CFOs, and sustainability-leads are increasingly considering third-party service providers that can be more efficient and effective at achieving these multipronged IT asset management goals that can meet both business and sustainability outcomes.

Furthermore, to help open budget to re-invest in GenAI technologies and innovation, IT asset lifecycle management services from hardware asset management (HAM) and IT asset disposition (ITAD) providers present a critical opportunity to understand the residual value of assets at any point in their lifecycle. In addition to the financial value of IT assets, IDC research shows that organisations also evaluate HAM and ITAD providers on their ability to provide sustainability metrics, particularly CO2e reporting for product circularity. To complete the business case, IDC research shows that security services, including certificates of data sanitisation, are critical to address the end of use “danger zone” for data security when managing IT asset lifecycles.

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