How AWS AI Enhances Sustainability and Operations at Amazon

Artificial Intelligence (AI) is increasingly recognised for its capability to support sustainability efforts.

By enhancing processes, improving efficiency and driving innovative solutions, AI addresses environmental challenges effectively.

In the realm of building efficiency, AI is transforming the landscape by optimising energy usage, forecasting equipment malfunctions and elevating building automation systems.

These advancements are significantly reducing energy consumption and operational costs in both new and existing structures.

Amazon stands out as a frontrunner of the growing trend of corporations harnessing AI to dramatically decrease its environmental footprint while simultaneously improving operational efficiency.

The e-commerce giant is deploying AI across a variety of applications, from streamlining packaging processes to accelerating carbon footprint calculations for its vast product range.

The AI-driven revolution in Amazon's building efficiency

Among the many applications of AI is its potential to radically improve building efficiency.

AI systems can optimise energy use, foresee equipment failures, and upgrade building automation. These capabilities are transforming how buildings operate, making them more energy-efficient and less impactful on the environment.

By integrating AI, Amazon is diminishing its environmental footprint while boosting operational efficiency.

Specifically, the tech giant focuses on workplace sustainability, reinforcing its commitment to the Climate Pledge through strategic utilisation of AI.

“At Amazon, our culture is rooted in innovation and speed,” Amazon’s CSO Kara Hurst says.

“AI can enable both and we’re using it in ways big and small to make progress.”

Some examples Kara gives include:

• The Package Decision Engine: An AI model that ensures safe delivery of Amazon parcels in the most efficient packaging possible, the Package Decision Engine makes decisions using deep ML, NLP and computer vision.
  “What does this mean for sustainability?” Kara poses. “So far, along with other packaging innovations, the Package Decision Engine has helped us avoid over two million tons of packaging material worldwide.”
• FlowMS: Just one of many Amazon AI tools for buildings, FlowMS is able to detect leaks, with one instance saving nine million gallons of water annually.
  Amazon focuses on solutions for buildings as the built environment — along with their construction —  accounts for 40% of the world’s greenhouse gas emissions.
  Kara says: “We’re using a suite of AI tools to help manage energy and water use in more than 100 of our buildings. Other AI tools help us monitor our HVAC systems, refrigeration units and dock doors.
  “These seemingly simple solutions add up and we’re making meaningful progress in saving energy.”
• Maximo: One of the “coolest-looking” examples, according to Kara, Maximo is an AI-powered robot developed by The AES Corporation that assists with building solar farms thanks to computer vision. This helps lift heavy panels, makes decisions with real-time construction intelligence and helps construction crews avoid dangerous heat. “Maximo can reduce solar construction timelines and costs by as much as 50%,” Kara shares.

She adds: “This is just the beginning and I’m excited about all the ways AI can help us reach our goals.”

Amazon and AI: The results

As well as the above examples, Amazon’s AI has optimised its operations in other parts of the business.

Energy efficiency

​​​​​​​Amazon’s Base Building Advanced Monitoring (BBAM) tool leverages ML to monitor HVAC systems, analyse operational data and identify anomalies in energy consumption. 

By comparing real-time data with expected performance based on factors like weather conditions, BBAM can detect issues such as clogged filters or malfunctioning air conditioning units. 

This not only saves energy but also improves overall system reliability.

Dock door management

By alerting employees when doors are accidentally left open at fulfilment centres and delivery sites, AI tools help reduce energy loss. 

This leads to substantial energy savings when implemented at scale.

“At Amazon, we’re innovating with AI to help us find new ways to decarbonise even faster, including inventing new solutions that continue to make our buildings more energy- and water-efficient,” Kara continues. 

“This is just one example of how Amazon is leveraging our decades of experience in AI development and sustainability to think big about decarbonising our business and operating more efficiently.”

Refrigeration optimisation

Amazon's Advanced Refrigeration Monitoring (ARM) tool analyses complex data patterns from refrigeration units in real-time. 

This allows Amazon to maintain optimal temperatures for perishable goods, as well as predict potential operational issues and flag malfunctioning equipment, preventing food waste and reducing energy consumption. 

For example, in Spain, ARM detected a change in the defrost cycle pattern at a site, preventing an estimated 1,000 hours of downtime.

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