The rapid adoption of GenAI is reshaping cloud computing, offering transformative solutions while accelerating the achievement of sustainability goals. As cloud providers navigate regulatory complexity, escalating costs, and environmental pressures, GenAI is emerging as a critical enabler of innovation and efficiency.
This post explores how GenAI empowers cloud ecosystems to thrive in 2025 and beyond.
Navigating Regulatory Challenges in Cloud Sustainability
Navigating complex and ever-evolving regulatory landscapes remains a challenge for cloud technology vendors. Governments worldwide are implementing stringent regulations to curb carbon emissions and promote sustainable practices.
The EU’s Corporate Sustainability Reporting Directive (CSRD), for example, mandates comprehensive sustainability reporting. The European bloc’s Energy Efficiency Directive (EED) has introduced obligations, especially for datacenter operators, in terms of energy saving and energy efficiency. Noncompliance can lead to hefty fines and damage to a company’s reputation.
GenAI can potentially assist cloud vendors in ensuring compliance with regulations by automating the collection, analysis, and reporting of ESG data. AI can process vast amounts of data from various sources, identify relevant regulatory requirements, and generate accurate and comprehensive sustainability reports.
This not only reduces the administrative burden on cloud vendors but also ensures timely and accurate compliance with regulatory requirements.
Managing Cloud Energy Consumption and Carbon Footprint
According to IDC, global IT datacenter capacity will grow from 180GW in 2024 to 296GW in 2028, and electricity consumption will rise from 397TWh to 915TWh in 2028. Electricity is the largest ongoing expense to run a datacenter.
As the demand for cloud services continues to surge, so does the energy required to power datacenters. This presents a significant challenge for cloud vendors striving to reduce their carbon footprint.
To address this, vendors must invest in energy-efficient technologies and collaborate with energy providers to ensure a steady supply of green energy. An IDC survey found that while 31% of organizations are looking to deploy GenAI workloads in locations able to offer renewable or zero-carbon energy supplies, 31% also say that GenAI workloads are helping the company reduce its overall greenhouse emissions through business-level optimization and efficiency improvements.
AI models can optimize cloud datacenter operations by predicting and managing energy consumption more efficiently. AI-driven energy management solutions can analyze patterns in energy usage, predict peak demand periods, and optimize cooling systems to reduce energy consumption.
