By Deb Dutta
As human activities continue to exacerbate climate change and its impact on our very existence, the importance of sustainable development cannot be understated. The survival of most life on Earth, ours included, depends on adopting sustainable practices that reduce or eliminate these damaging activities while meeting current needs for food production, energy generation, and other necessities.
With its ability to analyse massive amounts of data, recognise patterns, and make decisions or predictions, artificial intelligence (AI) has immense potential in promoting sustainability for businesses and other organisations. AI can also automate mundane, repetitive, and even dangerous tasks for employees. Not only does this make operations more efficient, but it also lessens consumed resources, waste, and unwanted by-products.
But AI is not without its own set of challenges. Data privacy, cyber security, potential algorithmic biases, and the resource-intensive nature of AI training must all be considered by those looking at the power of this technology to achieve their organisation’s sustainability goals. Transparency in AI decision-making, as well as the speed of the technology’s development, which often surpasses regulatory frameworks, are also two issues that decision-makers should consider.
For organisations that can address these issues, though, AI is a game-changer. Here are just five ways AI can contribute to sustainability:
1. AI in Enhancing Energy Efficiency: AI provides an ideal platform for energy monitoring and improved energy generation. For instance, IBM’s AI-powered weather forecasting helps renewable energy companies better manage their plants to maximise production, lessening the need for “dirty” energy. This is critical for India where 70 percent of its generated electricity is derived from coal.
Predictive analytics can also make forecasts based on historical usage data, allowing utilities to make more informed decisions about when and how much power they should generate. In addition, AI-powered automation for tasks such as adjusting heating or air conditioning levels at different times of the day based on the weather can optimise and reduce the energy consumption of households and businesses alike.
2. AI in Realizing Net-Zero Emissions: With India having pledged to achieve net-zero emissions by 2070, both the government and the private sector need the powerful boost new technologies can give to its carbon reduction efforts. One way AI can radically change things is through analytics systems that can go through massive volumes of data to provide insights into energy consumption patterns and sources at the global, national, enterprise, and even individual levels.
For companies, this can raise operational efficiency, lower energy consumption, and decrease both direct and indirect carbon emissions. For governments, these insights can drive national policies and recommendations that are directed toward achieving net-zero goals.
3. AI and Sustainable Supply Chains: AI can also be leveraged to develop sustainable supply chains. Through the analysis of large datasets to identify inefficiencies in suppliers and materials, monitoring of conditions throughout the chain, optimisation of processes for shorter delivery times, and maximised efficiency through automated scheduling, enterprises can optimise fuel use and lower carbon emissions. AI can also predict demand better, allowing businesses to avoid overproduction.
4. Managing Natural Resources with AI: AI can support the management of natural resources by automating the monitoring and analysis of data related to resource availability and providing insights for decision-making and resource conservation efforts.. AI-driven predictions on ecological risks can enable proactive mitigation strategies such as preventive water restoration measures or drought preparedness programmes that protect natural habitats from destruction. Finally, AI-driven simulations can better present how different decisions impact our natural environment in terms of climate change and other phenomena over a longer period.
5. AI in Waste Management: Last but not least, AI can improve waste management by streamlining processes while providing data-driven insights. For example, it can be used to provide predictive analytics for optimising resources in industrial and commercial activities, enabling businesses and organizations to plan their usage of materials better, and reduce waste. AI-driven computer vision techniques such as object recognition can be integrated into the processing of garbage or sorting of recyclables to reduce the amount that goes into landfills. Finally, machine learning models can also drive insights about product lifecycle developments so changes can be made accordingly.
The global situation today requires companies to embrace sustainable practices and commit to achieving sustainability. AI has massive potential when it comes to revolutionising how enterprises deal with environmental, social and governance (ESG) challenges, foster sustainable growth, and contribute towards a better future. Through AI-driven tools, businesses and governments can be more in sync and do what needs to be done to mitigate the climate crisis.
The author is general manager, Asia Pacific and Japan, DataStax
