3 Real-Life Examples of How AI Makes Businesses Sustainable

Making your business sustainable is a strategic decision for long-term growth and resilience. Embracing sustainable practices lead to cost savings, improved operational efficiency, and enhanced brand reputation. That’s why your company must invest in sustainable software engineering, a crucial aspect of responsible development and environmental impact reduction.

But how to make your business sustainable alreadyalready now? The answer is AI. AI can be truly helpful in making your business sustainable.

In recent years, the rise of AI has transformed technology, presenting new possibilities for businesses worldwide. In order to make businesses sustainable, it can do so much – improve energy efficiency, streamline supply chains, predict maintenance requirements, incorporate renewable energy sources, intelligently manage resources, minimize waste, create eco-friendly products, and monitor and decrease emissions.

According to the most recent data, the Greater China region, including Taiwan and Hong Kong, uses AI for sustainability, with 61% of organizations embracing AI. In contrast, North America lags behind, with only 30% of regional companies using AI in their sustainability initiatives. So, let’s explore 3 real-life examples of how AI makes businesses sustainable.

Energy optimization


AI can analyze data from different smart devices and sensors in a workplace to improve energy efficiency. It identifies where too much energy is used and suggests ways to improve it so the workplace becomes more sustainable and eco-friendly.

For instance, in 2016, Google’s DeepMind AI significantly reduced energy consumption in its data centers by up to 40%. Google and DeepMind created an AI-powered recommendation system and applied machine learning to Google’s data centers. Thus, Google achieved a 15% reduction in overall energy usage. The AI system used historical data from thousands of sensors within the data centers to create a more efficient and adaptive framework, optimizing energy efficiency.

In 2018, DeepMind and Google took their collaboration to the next level. They developed a whole AI-powered control system for data center cooling. The system uses AI to analyze data from thousands of sensors every five minutes, predicting actions to minimize energy consumption while meeting safety constraints. The AI system operates autonomously, directly controlling data center cooling and achieving energy savings of around 30%. Data center operators still have control and can switch to manual mode anytime.

Tesla is one more remarkable example of AI application in energy efficiency. The company’s Autopilot system uses AI to improve the energy efficiency of its electric vehicles. The AI system optimizes energy consumption through speed, route, and battery management adjustments by analyzing data from onboard sensors in real time. As a result, Tesla has extended battery life and achieved reduced energy consumption, establishing itself as a pioneering force in sustainable transportation.

Supply chain optimization


Supply chain optimization means making the process of getting products from suppliers to customers work better and faster. AI helps with this by using smart computer programs to look at important information from various places like suppliers, transportation methods, and raw materials. Then, it uses this information to make the supply chain work more efficiently, meaning things get done quicker and better.

Let’s take a look at Walmart. It uses AI in its supply chain through advanced technologies like Machine Learning and data analytics. By analyzing customer trends, shopping patterns, seasonality, and in-demand items, AI accurately shapes the company’s product catalog to meet customer preferences.

Besides, AI optimizes logistics and fulfillment services, enabling third-party sellers to deliver items promptly to customers. This integration of AI in Walmart’s supply chain operations leads to sustainability in several ways:

  • AI-driven demand forecasting and inventory optimization reduce waste and overstocking;
  • Efficient resource utilization and minimizing environmental impact;
  • The optimization of transportation routes through AI helps decrease fuel consumption and greenhouse gas emissions.

Reduced waste


AI helps companies reduce waste by analyzing where they are not managing things well and where they are wasting materials. It is like having a smart assistant that monitors the production process and ensures they don’t use too much material or produce more than they need. This way, AI helps businesses be more efficient and produce only what is necessary, reducing unnecessary waste and saving resources.

As mentioned earlier, Walmart uses AI to optimize its supply chain and reduce waste in its inventory management, logistics, and transportation operations. Not only Walmart but Amazon uses AI to reduce waste. It uses a combination of deep learning, natural language processing, and computer vision to reduce packaging waste.

By analyzing big data and massive scale, AI helps Amazon find the right amount of packaging for each product. The ML model is trained on millions of examples of successfully delivered products with various packaging types, and customer feedback plays a crucial role in improving predictions. AI analyzes text-based data from the Amazon Store to determine the optimal packaging type for each product, considering keywords and package dimensions. To address visual information, computer vision is deployed using product images captured at fulfillment centers.

This multimodal approach improved the model’s performance by up to 30%. When the model is certain of the best package type, it auto-certifies it, while less certain cases are flagged for human inspection. This AI-driven initiative has significantly reduced Amazon’s packaging weight per shipment by 36% and eliminated over a million tons of packaging, contributing to waste reduction and sustainability. Amazon’s Shipment Zero goal aims to deliver 50% of shipments with net-zero carbon by 2030, further promoting environmental sustainability in its e-commerce supply chain.

Bottom line

AI offers invaluable help when it comes to making businesses more sustainable. Its vast and multifaceted capabilities allow companies to address environmental challenges effectively. By analyzing large volumes of data from various sources, AI can optimize energy usage, streamline supply chains, and predict maintenance requirements, improving energy efficiency and resource management. This saves businesses money and helps them reduce their environmental footprint. AI-driven demand forecasting and inventory optimization are additional benefits that minimize waste and overstocking, contributing to overall sustainability.

Moreover, AI’s ability to monitor and decrease emissions aids businesses in achieving their sustainability goals and aligning with eco-conscious practices. In a rapidly evolving market where environmental responsibility is gaining importance, AI empowers businesses to make informed decisions that foster long-term growth while supporting a greener and more sustainable future.