Building Environmental Intelligence: How AI can help businesses grow sustainability

Across the globe, environmental sustainability is emerging as a business imperative with several countries facing the impacts of climate change. It is a simple nous — there cannot be successful economies alongside environmental degradation. But developing environmental sustainability also presents risks that can affect the operating models of companies, with a bearing on business prospects in a highly competitive marketplace.

However, the imperatives for sustainability will only intensify. For instance, the rise of purpose-driven customers is clear now. About 93% of global respondents in an IBM Institute for Business Value survey revealed that the Covid-19 pandemic has changed their perspective on environmental sustainability — compared to 2019, 22% more customers now believe that environmental responsibility is highly critical when choosing a brand. Moreover, environmental challenges present increasingly serious risks to supply chains and other operations as outlined in the World Economic Forum’s Global Risk Report 2020. Therefore, companies must heed both factual analyses and consumer voices towards developing environmental sustainability.

To become truly sustainable, companies must adopt measurable goals. These encompass key areas — to foster conservation and biodiversity, companies can set aims to reduce water withdrawals on a year-on-year basis at office locations. They could source paper and wood-based packaging from sustainably managed forests while those planning construction projects could opt for third-party sustainability certifications.

For pollution prevention and waste management, companies should divert non-hazardous waste from landfills and incineration by reusing, recycling, composting and waste-to-energy processes. They could also eliminate non-essential plastic packaging, using fully recyclable or compostable plastic where essential.

Technology can be an aid in key mitigation areas. Green energy consumption and reducing energy-related emissions are critical in climate change mitigation. Companies should begin to obtain a share of their electricity needs from renewable sources now. They can set goals for the next five and ten years to gradually increase renewable energy in the overall consumption mix. Companies owning data centres should also consider improving their average cooling efficiency — the metric for maintaining an ideal temperature that ensures companies can fully harness the power of their processors — over a short-term horizon. Upgrading their servers can also help companies reduce power consumption per unit of delivered work.

Further, businesses can establish reduction targets for carbon intensity with their carriers and shipment suppliers. Carbon intensity — the amount of carbon by weight emitted per unit of energy consumed — is crucial to decarbonisation in the global freight and logistics sector and many corporates are asking their logistics partners to reduce carbon intensity by using renewables in place of oil-based fuels, etc.

In supply and value chains, companies should encourage suppliers to set goals for energy and waste management and greenhouse gas emissions reduction. They should guide suppliers particularly in emissions-intensive sectors like transportation and manufacturing to set reduction goals as per the UN’s Intergovernmental Panel on Climate Change. Companies can also use emerging technologies to curtail their environmental impacts while delivering better business results — they can leverage Artificial Intelligence (AI) and hybrid multi cloud to integrate data across their ecosystem and gain faster insights for building more accurate environmental models. These can help optimise business processes and resource consumption while minimising wastage and pollution.

To illustrate, an AI-infused intelligent fulfilment platform can undertake reverse logistics to enhance the process of return sorting, product re-merchandising and repair lifecycle tracking, reducing the environmental impacts of returned goods. The global fashion industry sees 40% of all online purchases returned — this is both expensive and creates significant additional transportation emissions. Therefore, retailers like the US-based Moosejaw are now supporting their customers in using AI to purchase as per their exact needs, significantly reducing return rates.

Advanced analytics also empowers companies to realign their operations to reduce environmental impacts. In partnership with IBM, Yara, a Norwegian chemical company, unveiled a global digital farming platform that leverages AI, machine learning, weather and field data to drive insights for farmers, so they can sustainably improve crop yields. Analytics can also incentivise stakeholders to innovate by factoring in environmental charges in their costing through methods like imposing a fee on carbon. As these results show, it is possible to combine a sustainable and profitable path with AI-powered solutions and quantum computing. Environmental sustainability is now a business imperative, encouraged by both purpose-driven customers and investors.

The pandemic has further emphasised the importance of protecting our environment — businesses cannot succeed alongside ecological degradation. AI can help develop more sustainable ways forward.

(The author is from IBM. Views expressed are personal.)