Olivier Subramanian, Head of Cloud Advisory at BJSS, now part of CGI, explores how organisations can optimise their cloud solutions by utilising AI and redesigning applications, for greater efficiencies, lower emissions and ultimately cost savings.
With sustainability now central to business strategy, artificial intelligence (AI) is becoming a crucial enabler of climate-conscious innovation. From minimising energy consumption to optimising supply chains, AI is helping organisations reduce emissions and improve resource efficiency, while continuing to deliver on operational and financial targets.
Government policies, such as the UK's commitment to reach net-zero emissions bt 2050 and its 68 per cent reducion in emissions by 2030, are further establishing the business imperative for organisations to meet stringent environmental goals. As companies respond to these regulatory demands, AI is playing a pivotal role in accelerating their efforts to reduce their carbon footprints and enhance sustainability practices.
However, the environmental benefit of AI depends not only on what the tools are used for, but also on how they are built and deployed. Advanced AI models, particularly those powering large-scale data analytics and generative applications, require significant computing power. If these workloads run on traditional, fossil-fuel-powered infrastructure, the energy consumption can undermine the sustainability gains AI aims to deliver.
To counter this, many organisations are adopting cloud platforms that prioritise energy efficiency and run on renewable power. These platforms are designed to scale AI innovation while keeping emissions in check. They dynamically allocate computing resources, reduce idle capacity (the unused potential or resources within an organisation that aren't currently in use), and optimise workloads, helping to minimise waste and lower carbon impact. By choosing sustainable infrastructure from the outset, businesses can ensure that the tools designed to reduce environmental harm don’t end up contributing to it.
Practical applications with real-world impact
AI is making sustainability more actionable by helping organisations detect inefficiencies, forecast needs and automate improvements. Across a range of sectors, businesses are using AI to analyse patterns in energy usage, uncover resource waste and make real-time adjustments to operations. These insights are enabling smarter, faster decisions that reduce environmental impact while enhancing performance. Indeed, a recent Intel report found that 62 per cent of leaders ae utilising AI to reduce the carbon footprint of their organisation's IT function, and 66 per cent of leaders say that their organisation is using AI as a lever for the whole organisation to reach its net-zero goals.
For example, in manufacturing, AI helps optimise production to avoid overuse of energy and materials. In logistics, it's improving fleet routes to cut fuel use and emissions. In the energy sector, AI enhances the predictability of renewable sources like solar and wind, helping stabilise grids and reduce reliance on fossil fuels. These improvements help align operational processes with sustainability goals, without sacrificing productivity or profitability.
AI is also enhancing environmental monitoring. When integrated with Internet of Things (IoT) devices, it can track carbon emissions across facilities and supply chains in real time. This visibility allows companies to move from reactive to proactive sustainability strategies, detecting problems early and taking corrective action before they escalate.
Building AI with sustainability at the core
While AI offers powerful tools for advancing sustainability, its deployment comes with challenges. Accurate, real-time data is essential for AI to be effective, but many organisations struggle with incomplete or inconsistent environmental data. Gaps in emissions reporting or siloed systems can limit AI’s ability to deliver meaningful insights.
There are also infrastructure concerns. In areas where energy supply is unreliable, maintaining the performance of AI systems can be difficult. Additionally, businesses must ensure that their AI models are built responsibly, with transparency, fairness and compliance in mind. Ethical concerns, such as data privacy and algorithmic bias, must be addressed to ensure long-term trust in these technologies.
Despite these hurdles, businesses are increasingly aligning AI strategies with sustainability principles. This includes designing carbon-efficient models, choosing renewable-powered infrastructure and embedding sustainability metrics into performance dashboards. These practices are helping organisations scale AI responsibly and with purpose.
Accelerating progress through cloud and AI
The combination of AI and sustainable cloud infrastructure is enabling a new wave of climate-aware innovation. Together, these technologies allow businesses to measure and manage their environmental impact more precisely, while continuing to adapt, grow and compete.
AI provides the intelligence to uncover carbon drivers and recommend improvements. Cloud platforms provide the agility and scale needed to act on these insights efficiently. When used together, they enable continuous optimisation, helping businesses reduce waste, improve resiliency and progress toward their climate goals.
Organisations that embrace this dual approach are showing that sustainability and business success don’t have to be in conflict. By embedding environmental responsibility into the core of their digital transformation, they’re laying the groundwork for long-term impact, both economically and ecologically.
The future of sustainable business will be powered by clean, intelligent technologies. And the companies leading the way are proving that responsible innovation is not just possible, it’s essential.
Find out more about CGI and BJSS today.
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