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[Column] Craig Stephens: Environment impact of AI and analytics in the cloud

[Column] Craig Stephens: Environment impact of AI and analytics in the cloud

Cloud computing's role in today’s digital marketplace is undeniable. It allows for significant advancements through analytics, machine learning, and AI. However, concern over its carbon footprint is growing. The cloud’s greenhouse gas emissions (GGEs) now eclipse that of the global aviation industry.

This highlights the environmental cost of digital expansion, emphasising the need for action as cloud computing now contributes to almost 4% of global carbon emissions. These statistics underline the critical situation we face, with 2023 having been the hottest year on record to date further underscoring the urgency of the climate crisis.

In 2016, the Paris Agreement was signed to limit global warming to 1.5 degrees Celsius by 2100. This would be a level relative to the pre-industrial age from 1850 to 1900. This goal necessitates a 43% reduction in GGEs by 2030 and for the world to reach net zero by 2050. What this means in practical terms is that immediate and concerted efforts across all sectors, including technology, are now non-negotiable.

The need for solutions that align with Environmental, Social, and Governance (ESG) outcomes becomes an important building block in this regard. Gartner's forecast that 25% of CIOs will have their compensation tied to sustainable technology impact by 2027 underscores the increasing importance of ESG considerations in the corporate world.

On-premises better?

The debate about whether on-premises computing solutions are more efficient is a moot one. The IDC highlights that the cloud is a more environmentally friendly choice compared to on-premises computing due to the greater efficiency of aggregating computing resources. Therefore, migrating AI and analytics workloads to the cloud seems like the way to go. This efficiency not only supports the business case for cloud migration but also aligns with environmental sustainability by reducing the carbon footprint associated with IT operations.

For our part, we are committed to leveraging AI and analytics in support of sustainable business practices. Developing solutions that empower companies to reduce emissions and enhance operational efficiency has been an organisational priority. For instance, the SAS Viya platform lies at the heart of these solutions. This embodies our company’s commitment to a data-driven approach to sustainability. By applying analytics to challenges like traffic congestion and energy usage, we are demonstrating the potential of AI and analytics to contribute to a greener future.

Tips to consider

Organisations can also become more aware of the repercussions of ineffective cloud usage especially as it relates to GGEs. One of the things to consider in this regard is for a business to understand its carbon footprint. This can be done by using a combination of tools like sustainability calculators along with technology like the Green Algorithm Calculator to build a comprehensive view of the company and its carbon footprint.

From there, decision-makers need to select the cloud regions they use wisely. Different regions can have a different impact on sustainability. It is vital to find a balance between performance, cost, and sustainability. As part of this, companies must continuously monitor workloads and optimise – and available tools that support continuous monitoring and optimisation become integral to the success of these processes.

Businesses should also consider auto-scaling possibilities. As part of this, they must switch off cloud resources when not needed and only upsize when required. Many companies tend to forget that even idle resources still use power. Wind and solar-based scheduling can help optimise environments, especially in territories that are rich in such natural resources.

Much of optimising efficiencies entails minimising data movement with in-database technologies. Again, this is where our technologies like SAS Vaya become vital business enablers in this regard.

Making it practical

Our work with the Istanbul Metropolitan Municipality serves as an example of how AI and analytics can address sustainability challenges. By optimising traffic management, SAS has helped reduce congestion and emissions, showcasing the practical benefits of AI and data analytics technologies in urban settings.

The journey towards reducing the environmental impact of cloud computing and leveraging technology for sustainability is a complex one. It requires a combination of strategic decision-making, technological innovation, and a commitment to continuous improvement. 

Craig Stephens is the Advisory Business Solutions Manager, SAS in South Africa.






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