IT Sustainability Think Tank: How IT Sustainability Entered the Mandate Era in 2025 | Computerweekly

The conversation evolves from ambitious to responsible

The most profound shift of the past year has been the forced shift of sustainability dialogue directly into the executive committee’s core risk portfolio. This movement is not voluntary; it is driven by impending regulation and the sobering realization that environmental failure now carries direct, verifiable financial sanctions and accountability at the board level.
Just a year ago, the discussions were about unquantifiable reputational benefits. Today, the lexicon is dominated by acronyms indicating mandatory compliance: CSDDD, CSRDand the tightening of the SBTi Net-Zero Standard V2. These frameworks force executives to move beyond narratives and confront the detailed, auditable data associated with every asset, supplier and cloud use.
For the CIO, this manifests itself in two crucial areas. First, energy efficiency is being firmly redefined as a cost of doing business, critical to managing operational expenses amid volatile global energy markets. Second, the sudden demand for energy from generative AI has led to a rapid internal debate about responsible computer architecture.
Leaders are increasingly forced to justify AI investments not just on traditional ROI, but through an emerging “return on compute” model that necessarily integrates and accounts for carbon spend. This makes the environmental costs of IT an integrated input into the total cost of ownership calculation, rather than a polite footnote.
Despite this high-level commitment, progress remains complicated. The IT function often lacks the authority to enforce change across complex internal silos, and the necessary budget and risk tolerance for truly transformative change remains stubbornly limited.

Real progress where the green shoots gain a foothold

Despite systemic inertia, 2025 has delivered solid, tangible progress in certain operational areas, and provided a partial blueprint for future net-zero efforts. Our confidence is reinforced by three examples, although it is critical to understand that large-scale adoption within the average enterprise is still in its infancy and often limited to pilot programs:
1. Decoupling cloud growth from carbon: Hyperscale cloud providers have largely won the battle for renewable energy procurement. The next frontier – optimizing physical operations – concerns enterprise involvement. We saw accelerated adoption of advanced liquid cooling technologies (still mainly concentrated in hyperscale environments, but critical for future AI scaling). Companies that optimized workloads for low-carbon regions and used serverless architectures successfully decoupled the rapid expansion of the cloud from a proportional increase in emissions. This success belongs mainly to the hyperscalers, and business optimization remains an ongoing campaign.
2. Maturating the circular IT model (As-a-Service): In 2025, the Managed Device-as-a-Service (MDaaS) model transformed into a critical environmental enabler. By outsourcing the entire device lifecycle, companies virtually commit to renovation and robust reverse logistics. Successful companies use these contracts to guarantee the return of assets into the value chain through certified renovation, dramatically reducing e-waste. The caveats are twofold: MDaaS adoption is far from universal, and the verification of these circular chains still lacks the necessary, robust third-party oversight.
3. The Burgeoning Rise of Green Software Engineering: The formal emergence of green software engineering (GSE) is perhaps the most encouraging development. For too long, the environmental focus was solely on hardware. This year, organizations began measuring code energy consumption by optimizing algorithms and refactoring applications to reduce reliance on resource-intensive computing.
An important development this year was the publication of the W3C Web Sustainability Guidelines (WSG) Concept note. Developed through a global, collaborative effort – in which I was pleased to participate – the Guidelines provide a structured and internationally relevant set of best practices for reducing the environmental footprint of web products and services. While the scope focuses specifically on the Internet and not the full breadth of enterprise IT, the concept note nonetheless represents an important step forward for the industry.

The persistent gaps undermining net-zero momentum

For all the real acceleration, 2025 has been equally defined by two persistent, critical gaps that threaten to derail the trajectory of a net-zero crisis and require urgent attention.
1. The Scope 3 emissions gap: The most widespread and frustrating gap remains measuring and meaningfully reducing Scope 3 emissions, particularly from purchased goods and at the end of asset life.
Despite the regulatory urgency, the vast majority of companies still rely on highly aggregated, industry-average supplier data (by spend or activity), which is neither verifiable nor sufficient for mandatory disclosure. The necessary mechanism – detailed, granular carbon footprints (PCF) of products provided by each supplier – is simply not available at scale or with sufficient reliability.
The problem persists because it requires collaboration across complex, often proprietary global supply chains. Suppliers are reluctant to disclose detailed data due to competitive concerns, while buyers do not have the power to mandate this. The result is a ‘Scope 3 plateau’: targets are set, but underlying emissions remain stubbornly high, creating significant credibility risk. We are still largely measuring a reflection, not reality.
2. The Generative AI Energy Debt: While AI is a powerful tool for sustainability optimization, the immediate, unmanaged energy demands of Large Language Models (LLMs) represent a deep and growing gap. The speed of AI adoption, combined with the inherently expensive High-Performance Computing (HPC) required, creates an “energy debt” that offsets hard-won gains elsewhere.
The challenge is governance. Companies are deploying AI solutions without robust, mandatory policies around model selection, inference efficiency, or resource decommissioning. Crucially, most organizations remain focused on achieving initial ROI numbers, relegating energy efficiency to an optional performance adjustment. Without enforcing a “responsible computing” framework, AI’s transformative power risks being offset by its growing impact on the environment. This is the biggest risk to the IT sector’s net-zero trajectory.

Strategic priorities for 2026 and beyond

As the IT Sustainability Think Tank looks to 2026, the focus must shift from identifying the problem to tackling it systematically close the remaining gaps with institutional discipline. We must treat these priorities as non-negotiable elements of future business resilience:

1. Granularity of mandate data for Scope 3: Use purchasing influence to enforce supplier compliance with verifiable Product Carbon Footprints (PCF). The mandate should be non-negotiable and enforced with clear supplier scorecards and contractual requirements.
2. Institutionalize green software engineering: Invest heavily in training and tools to integrate energy efficiency into the software development lifecycle (SDLC). Software architecture must be treated with the same environmental scrutiny as data center cooling, making efficiency a controlled requirement.
3. Control AI energy costs: Implement a responsible AI framework that includes mandatory energy consumption metrics and resource allocation policies for all generative AI deployments.

The year 2025 was the year in which IT sustainability entered the board’s audit file. Next year must be the year when we finally collect the detailed data, impose the necessary discipline, and control the rapidly growing energy demands of our own invention. The time for ambitious statements is definitely over; the urgent task now is to translate these emerging efforts into full, verifiable accountability.