From automation and natural language processing (NLP) to robotics and augmented reality (AR), artificial intelligence (AI) can be applied to help organisations tackle a multitude of business challenges.
One thing that unites people and businesses across the globe is climate change and the impact it's having on communities and biodiversity. As well as being key for business prosperity, executives in a number of different industries are now turning to AI technology as a tool to both improve their own internal sustainability strategies and to develop technology that targets key challenges faced as a result of climate change.
Looking at the significance of this technology to sustainability, Prashant Natarajan, Vice President, Strategy and Products at H2O.ai, comments: “AI’s biggest role is using data to create a more engaged and informed global society. From producers of goods and services to governments caring for their citizens, we’ll be much better at grasping opportunities for identifying new sustainability options. These options will both increase environmental protection and set the foundations for truly responsible growth.”
Adding to this, Christina Shim, VP and Head of Strategy and Sustainability at IBM, outlines that sustainability requires much more than measuring emissions within organisations. With supply chains, the life of assets and the impact of environmental conditions on operations also needing to be taken into consideration, AI takes centre stage: “When you can apply data and AI to these areas, companies can make smarter, more sustainable decisions.”
As an asset to sustainability teams by providing a new perspective into sustainability, “AI works at its best when it's used to increase or augment our decision-making capabilities. That’s the sweet spot for climate action,” says Martin Migoya, Co-Founder and CEO of Globant.
AI: improving the energy sector and business practices
Research by PwC models the economic impact of AI’s application to manage the environment across four sectors – agriculture, water, energy and transport. It estimates that using AI for environmental applications could contribute up to US$5.2 tn to the global economy in 2030, a 4.4% increase relative to business as usual.
Looking specifically at the energy sector, Natarajan outlines how it is particularly useful within the industry, which in itself is a significant contributor to climate change.
“Optimising the power grid and increasing its efficiency, not just in production but also reducing the loss that happens in distribution, will mean we can do more with less. With machine learning, you’ll soon know in incredible detail if there is a certain time of the year when more energy gets lost, for example,” he says.
AI can be invaluable to the renewable energy sector, not only because the automation capability of AI can drive operational excellence in many crucial areas but because, with its power predictions, AI will lead to improved demand forecasting and asset management.
“Understanding the impact of decisions from multiple perspectives in the utility space is a place where AI/ML will make a big difference,” adds Natarajan.
The research by PwC also found that AI could create 38.2 million net new jobs across the global economy, offering more skilled occupations as part of this transition towards AI technology.
With the ability to transform how businesses can tackle their sustainability efforts, this multifaceted technology can help companies achieve more efficient, resilient and sustainable operations that have an impact on their bottom line.
“Using AI-driven insights, organisations can extend the life of critical assets such as machinery, buildings, and equipment; create more efficient and resilient supply chains to protect and optimise inventory, reduce waste and added emissions from ineffective shipping and delivery routes,” says Shim.
Additionally, businesses can utilise AI technology to monitor for disruptive environmental conditions, predict potential impacts, and better understand the impact of their own operations on the environment.
“On a cognitive level, AI enables us to assess challenges that are typically complex or costly to quantify and analyse. For example, we can build an AI that estimates the CO2 output of different combinations of hardware, the impact of how we structure code in our programs, or the emissions generated by different activities,” explains Migoya.
Is AI a business imperative?
Nations across the world have signed various agreements, pledged to reduce carbon emissions and agreed to sustainable development goals. With these commitments, businesses are facing increasing pressure from investors, regulators, and consumers to demonstrate more sustainable and socially responsible operations.
It’s no surprise that environmental sustainability is emerging as a top priority for stakeholders across the business and as a result, creating more sustainable operations isn't just good for society - it's also a business imperative.
“According to a recent survey, 80% of consumers indicate sustainability is important to them and 60% are willing to change their shopping habits to reduce environmental impact, a proportion that could very feasibly continue to rise as climate change gets worse. In addition, organisations with successful sustainability programs are able to attract better talent as, according to an IBM survey, 71% of employees and employment seekers surveyed say that environmentally sustainable companies are more attractive employers,” explains Shim.
As Migoya explains, with this drive to create more sustainable businesses, AI provides a solution to this transition to sustainable business operations without disrupting business as usual: “The efficiencies that AI provides enable an escape from the cost/benefit binary, and a focus on the upside. There are still many places where the choice or pursuit of sustainability is a matter of principle, values, and vision. But we are not far away from an era where sustainability is imperative to remain competitive. Having the tools to incorporate these goals without friction enables companies to pivot faster.”
AI, Natarajan explains, will give organisations the ability to understand the impact of a business move from both a sustainability perspective and an economic perspective. “The assumption is you can't separate the two: AI changes that,” he says.
Supporting the UN’s sustainable development goals with AI
Although climate change and its impact is a top priority for businesses, so are many other sustainable development goals, as outlined by the United Nations (UN). The 17 goals, adopted in 2015, are a universal call to action to end poverty, protect the planet, and ensure that by 2030 all people enjoy peace and prosperity.
“The development of these social initiatives are mainly human and they require many aspects, concepts and planning that are not necessarily related to technology. However, technology can contribute to elevating them:AI can help these different aspects to align, and it can also ensure access to relevant forms of knowledge, promoting fundamental skills and critical thinking among the community,” explains Migoya.
With the ability to elevate these initiatives, Shim believes that AI will be revolutionary as the world looks to end poverty.
“A crucial part of this is enabling AI technology the ability to address these issues via public-private partnerships and broader applications of it across business, social, environmental, political and other spheres that are strongly interconnected and have interlocking impacts. In other words, it is impossible to decouple environmental issues from social issues. Climate justice and refugees are an example here, where without the support of AI-enabled technology to mitigate climate change, a significant percentage of the population will lose their homes, their land, and even their countries,” she says.
Migoya, despite celebrating the significance of AI to climate change, stresses the issue of techno-optimism whereby businesses believe that simply integrating AI into sustainability strategies will solve all the problems: “There is no excuse for not appropriately analysing the scope of the objectives and their effects, involving people affected, subject matter experts, and so on. AI needs to be used “from the inside” to improve the way things work; not “from the outside” where there may be a lack of understanding the nuances of the systems involved and how they work.
He concludes: “We need to be humble enough to be consistently measuring and reassessing our actions so that when we learn, we are applying that as soon as possible.”