AI in just four sectors could boost global GDP by up to $5.2 trillionChristian Fernsby ▼ | April 30, 2019
Harnessing AI in just four sectors to support better management of the environment could yield productivity benefits, higher GDP, reduced carbon emissions and up to 38 million jobs globally.
World PwC UK’s preliminary assessment was commissioned by Microsoft
How AI can enable a Sustainable Future examines the potential opportunities of AI for economic growth and emissions reduction potential between now and 2030.
AI can be harnessed in a wide range of sectors in the economy to better manage the environment.
AI-infused clean distributed energy grids, precision agriculture, sustainable supply chains, environmental monitoring and enforcement, and enhanced weather and disaster prediction and response are just some of the examples.
The research models scenarios for AI’s use across four sectors - agriculture, transport, energy and water.
It estimates that using environmental applications of AI in these four key sectors could contribute up to $5.2 trillion USD to the global economy in 2030, a 4.4% increase relative to business as usual.
In parallel the application of AI levers could reduce worldwide greenhouse gas (GHG) emissions by 4% in 2030, an amount equivalent to 2.4 Gt CO2e - equivalent to the 2030 annual emissions of Australia, Canada and Japan combined.
At the same time as productivity improvements, AI could create 38.2 million net new jobs across the global economy by 2030, offering more technology based skilled occupations as part of this transition.
Regionally, AI shows the greatest potential to reduce GHGs in North America (-6.1%) and Europe (-4.9%) and the largest economic gains (GDP) in Europe (+5.4%) in 2030.
While Latin America and Sub Saharan Africa stand to gain the least in the analysis, their gains could be higher if more digital transformation can be realised through infrastructure investment, enabling them to leap-frog developed countries.
They also stand to gain the most from avoiding the worst impacts of climate change through mitigating greenhouse gas emissions.
AI applications in energy and transport will have the largest impact on emissions reduction.
AI’s benefits to productivity include optimisation of inputs including reduction in energy, automation of manual and routine tasks, lowering energy emissions per unit of GDP of 6-8% in 2030, relative to business as usual.
The report also finds encouraging signs for AI’s potential to improve health.
More accurate and localised early warning systems for air pollution for example, could save an estimated $2.4bn globally in reduced healthcare costs and health impacts.
Additional environmental benefits can be achieved in water quality, air pollution, deforestation, land degradation, and biodiversity, through greater data, insights, and early warning systems.
For example, using satellite data and ground based sensors to monitor forest conditions in real time and at scale, providing early warning system for investigation of illegal deforestation, with the potential to save 32 million hectares of forest by 2030.
The report warns that for all the potential that AI for environmental systems have, its application and uses could also exacerbate existing threats or create new risks.
Broader AI risks linked to bias, security and control are all potential risks to the environment.
In addition, there are substantial and wide-reaching barriers relating to these sectors that need to be overcome to realise the full potential of AI for environmental applications. ■