Swati Kirti is the Senior Director of Data Science at Walmart.
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With the sudden rise in artificial intelligence (AI) powered solutions for sustainability, you may wonder if this is just a trend. I’m here to say no: AI can have immensely positive impacts on your sustainability initiatives.
This is especially true for companies trying to streamline their data analytics and unveil hidden opportunities for sustainability. However, proper integration is not about plugging in new technology. AI integration requires alignment with operational changes and a robust change management approach.
Identify New Opportunities
A supply chain professional with years of experience might recognize the need for process changes. These observations are valuable indicators that serve as a starting point. However, AI can add significant depth to these insights with a data-driven approach.
For instance, if you hypothesize that a particular area has significant opportunities and waste, AI can validate this by analyzing vast amounts of operational data and utilize diverse signals, confirming whether this is indeed the case and pinpointing where improvements can be made for an optimized approach. This would take considerable time and effort without the use of AI.
Every business is unique, and sustainability can mean different things depending on your type of business. It could be using more recyclable materials, increasing production efficiency to reduce waste, improving refrigeration processes and more. The key is finding a tailored AI that could pinpoint specific areas to improve your sustainability efforts.
Sizing And Mapping Opportunities
Business are complex and usually have many touchpoints in their operations where waste can occur. Further, waste could be an outcome of process gaps, people challenges or techology gaps. For example, many processes are involved in a supply chain. If your logistics supply chain has some inefficiency, this also means there could be a lot of different pieces to the puzzle.
Once you have identified your opportunities, the next step is understanding their relative size to map your priorities. This is an important step as time and resources are generally limited and hence focusing on narrow but most impactful opportunities becomes key. This is an excellent use case for AI一estimating the size of sustainability improvements一because it requires substantial computation and advanced modeling.
AI can help streamline your sustainability initiative by making recommendations involving optimized shipment routes, improved fuel efficiency or minimizing the handling of perishable goods to minimize waste. With AI, you can sort the relative importance of your goals using a quantitative method that your stakeholders understand.
Aligning Stakeholders
With a clear picture of the relative importance of your goals, it is crucial to sit down with your stakeholders and align them on how AI works for sustainability.
Integrating AI requires strong change management. This means getting everyone on board with new ways of working. Training programs should be in place to help staff learn new processes. For AI-driven sustainability efforts to be effective, operational management must actively implement the changes recommended by AI. This involves translating AI insights into practical steps within the company’s existing processes. Operational management helps ensure that AI-driven strategies lead to real, tangible improvements in sustainability practices. Ongoing support is essential to ensure smooth transitions. A culture that embraces change can help reduce resistance and improve collaboration.
Defining Sustainable AI
According to Goldman Sachs, a single ChatGPT query uses 10 times as much energy as a Google search. This has brought notable concern to the AI space. Paradoxically, AI machine learning and neural networks are being used to unlock new opportunities for sustainability.
In 2016, Google’s DeepMind AI applied machine learning to their data centers, reducing their overall energy consumption by up to 40%. Researchers at the Lincoln Laboratory Supercomputer Center are experimenting with new techniques that reduce the energy required to train new AI models by 80%. While AI technology may increase your energy usage in the short term, AI tools are constantly being developed to identify and change those patterns.
Dr. Sasha Luccioni, a renowned researcher of AI energy usage, said there are a lot of opportunities for sustainability with AI. The problem, she says, is that companies view it as a one-size-fits-all approach.
A better approach is to align AI with your strategic goals for sustainability. You can set internal guidelines on using AI and use pre-trained AI models that reduce overall energy usage across your organization. As with any technology, you should measure costs against the benefits to decide if it is a good investment for your business.
My presentation, comments and opinions are provided in my personal capacity and not as a representative of Walmart. They do not reflect the views of Walmart and are not endorsed by Walmart.
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