Best of LinkedIn: Sustainability & Green ICT CW 50 - 01

AI is treated as both sustainability risk and enabler, making efficiency and emissions reduction part of core model and infrastructure design

Green coding practices move into the mainstream, promoting energy-efficient algorithms, carbon-aware design and clean refactoring as standard engineering discipline

Developers begin using AI assistants more consciously, from collaborative refactoring to green coding agents that target performance, cost and climate impact together

Green software is repositioned as everyday responsibility, linking each line of code to long-term emissions, reliability and total cost of ownership

Cloud and data center players tighten their focus on energy efficiency, cooling innovation, water use and full transparency of underlying power consumption

New infrastructure concepts, including more efficient edge technologies and wooden data centers, blend sustainability engineering with distinctive physical design

Location choices for AI data centers face scrutiny as water stress and climate conditions expose the risk of placing high-density compute in unsuitable regions

Urban sustainability models gain attention, using excess data center heat and AI-enabled microgrids to support district heating and more resilient local energy systems

New AI-specific standards, such as SCI for AI and Carbon per Token, offer practical ways to track emissions from models and workloads

Integrated metrics like the One Token Model aim to combine cost and sustainability indicators, enabling clearer trade-offs in technology and architecture decisions

Independent software evaluations and buyers guides increase pressure on vendors to prove sustainability impact, not just offer generic ESG claims

Next-generation metrics move beyond energy alone, pushing data centers and IT leaders to capture Scope 3 effects and resource efficiency across value chains

New climate tech solutions emerge for infrastructure, including physical edge platforms and water treatment programmes that optimise data center cooling and resource use

AI is applied directly to sustainability operations, from customer support agents optimising journeys to green AI models tailored for the solar and energy industries

Space-based compute experiments and high-performance satellites signal fresh avenues for distributing workloads and rethinking where sustainable compute can sit

Regional stories, from China’s strong green tech export performance to Latin America’s climate innovation, underline climate tech as a maturing, globally competitive sector

A high-level UN AI resolution is criticised for lacking focus on energy, water, lifecycle analysis and enforceable mechanisms, exposing gaps between policy and practice

Structural tension between rapid AI growth and decarbonisation targets drives calls for better data transparency, scenario modelling and aligned corporate governance

Infrastructure deals relying on fossil power and carbon capture are challenged against public climate commitments, raising questions about credible transition pathways

International cooperation, such as UAE-EU collaboration on energy and AI, frames sustainability as growth driver, while local regulators push harder for disclosure and accountability

CIOs and digital leaders are urged to manage AI’s environmental footprint proactively, using green IT as a lever for risk reduction, compliance and operational advantage

Sustainability is positioned as part of every job in tech, linking individual developer choices and everyday tooling to enterprise-wide climate outcomes

Communities and meetups, from ClimateAction.tech to regional Green Software Foundation events, create practitioner networks that accelerate learning and shared standards

Public and employee pressure grows, as youth leaders, local communities and critical commentators question optimistic AI narratives and demand tangible, measurable emission reductions