2025 progress report: Tech’s role in sustainability
At the start of 2025, forecasts painted an optimistic picture: AI would accelerate climate solutions, electric vehicles (EVs) would become the standard, and mandatory reporting would bring rigour and urgency to corporate sustainability. Progress is underway, but real transformation demands broader uptake and resolve.
Categories:
Sustainability,
Artificial intelligence and machine learning,
Digital transformation
Mandatory climate reporting is now driving real operational change, not just compliance
AI is powering sustainability gains but its environmental cost is under growing scrutiny
Voluntary disclosures are stalling as greenhushing and minimum compliance creep in
Still, the tools for real impact are here and how organisations use them now will define the year
A moment for reflection
At the start of 2025, forecasts painted an optimistic picture: AI would accelerate climate solutions, electric vehicles (EVs) would become the standard, and mandatory reporting would bring rigour and urgency to corporate sustainability. While movement has begun, scaling these shifts remains a major challenge.
We now find ourselves at a turning point. The tools exist, the pressure is mounting, and the first half of this year has shown that how we use technology matters as much as what we deploy.
The good: Momentum on data, reporting & connectivity.
Mandatory climate reporting expands, raising the bar
Regulatory progress has been substantial. The EU’s CSRD, the ISSB’s global uptake, and Asia-Pacific’s fast-tracking of climate reporting frameworks mean that tens of thousands of companies are now navigating emissions disclosure, climate risk, and ESG data transparency1.
This has sparked an industry-wide shift in data operations: companies are finally investing in systems to move from static ESG reports to dynamic, auditable, and real-time sustainability data.
AI helps - but needs direction
AI is increasingly powering climate efforts, especially in emissions tracking and early risk detection. Enterprise leaders are training models on automating assurance steps and improving supply chain visibility2.
But AI’s own footprint is under scrutiny. Without transparent energy and water disclosures from model operators, AI’s role risks becoming part of the climate problem rather than the solution. And while LLMs are making sustainability data more accessible, accuracy, traceability, and ethical data use remain critical challenges3,4.
Telecom innovation is enabling low-carbon infrastructure
Often overlooked, telecommunications infrastructure—particularly 5G networks and intelligent base station management—is enabling low-latency, energy-efficient systems that underpin many sustainability technologies.
From smart energy grids to mobility-as-a-service platforms, the connectivity layer provided by telcos is a foundational enabler. Innovations in network energy management, edge computing, and predictive maintenance reduce energy use while supporting a surge in data traffic driven by IoT, AI, and digital climate platforms.
The challenges: Greenhushing, AI hype, and supply chain stagnation
Greenhushing and minimal compliance
While mandatory disclosures are growing, voluntary sustainability disclosures have plateaued - or in some cases, shrunk. Legal liability fears and reputational risk are pushing some companies into “greenhushing,” revealing less rather than more5.
AI’s energy trade-offs are coming into view
Enterprise deployment of large models has surged, but so too have concerns over their environmental cost. Water-intensive cooling systems, coal-powered data centres, and lack of lifecycle data threaten to undermine the narrative that AI is inherently green6.
There is also a growing market of “AI-for-sustainability” solutions with limited substance. For CIOs and CSOs, separating meaningful tools from marketing fluff is an ongoing challenge.
EVs rise, but sustainability still lags
EV adoption is climbing fast - especially in China, Germany, and Norway - but this doesn’t automatically equate to sustainability. Upstream impacts from mining, geopolitical concerns over critical minerals, and opaque supply chains all require attention. Without end-to-end lifecycle thinking, EVs risk becoming a new form of unsustainable consumption.
Looking ahead: Where to focus now
Mid-2025 isn’t just a checkpoint - it’s a decision point. Tech and sustainability leaders must double down on intentionality. Here’s where to focus:
Build responsible AI use frameworks
Develop internal guardrails on training and deploying large models.
Include environmental costs in procurement decisions.
Prioritise small, fine-tuned models where they suffice.
Elevate double materiality and value chain data
Capture upstream and downstream impacts, along with operations reports.
Engage suppliers now, even if disclosures aren’t yet mandatory.
Use digital twins and scenario tools to simulate material risks and opportunities.
Partner with telcos to optimise infrastructure energy use.
Explore opportunities to connect energy and water metering with predictive analytics.
Consider edge computing for sustainability use cases to reduce cloud dependency.
Prioritise usefulness over novelty
Be clear about whether a tech solution actually tackles a climate problem.
Pilot AI and automation tools on clear use cases: reducing food waste, improving fleet emissions, optimising renewable use.
Moving forward in 2025
We’re halfway through 2025, and the landscape is shifting quickly. The good news? The foundations are being laid: regulatory clarity, AI literacy, sustainability urgency. But the risk of fragmentation is high.
To realise the vision of tech-driven sustainability, enterprise leaders must stay pragmatic, vigilant, and bold. The tools are here - but it’s on us to wield them wisely.
Are you ready for tech-driven sustainability?
References:
S&P Global, June 2025 - Where does the world stand on ISSB adoption? 2025
WSJ x Deloitte, AI + earth observation data cloud catalyze a world's worth of climate progress, 2024
TechRadar, How can we create a sustainable AI future? 2025
UNRIC, Artificial Intelligence: How much energy does AI use? 2025
WSJ, Companies quietly water down climate claims in latest investor reports, 2025
Financial Times, The environmental cost of AI, 2024
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