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人工智能如何推动你的气候行动策略(英)

# 人工智能 # 气候行动策略 大小:4.13M | 页数:68 | 上架时间:2021-04-22 | 语言:英文

人工智能如何推动你的气候行动策略(英).pdf

人工智能如何推动你的气候行动策略(英).pdf

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类型: 专题

上传者: ZF报告分享

撰写机构: Capgemini

出版日期: 2021-04-15

摘要:

As the COVID-19 pandemic spread across the world, it also highlighted another major collective hazard we face – climate change. Extreme weather events are increasing, lives are being affected and placed in danger, and costs are mounting for governments and industry. Given the urgency of this issue, this report seeks to understand how AI can accelerate our response.

Our research found that: I. AI offers many climate action use cases • We analyzed over 70 AI-enabled use cases for climate action and identified the ten most impactful ones. By that we mean they offer significant benefits for organizations in terms of reduced greenhouse gas (GHG) emissions, improved energy efficiency, and reduced waste.

Examples include: – Tracking GHG emissions and tracing GHG leakages at industrial sites – Improving the energy efficiency of facilities and industrial processes – AI for designing new products that reduce waste and emissions during prototyping, production, and usage – AI for inventory management - improving demand planning and reducing wastage of food products and raw materials – Route optimization and fleet management for retail, automotive, and consumer products firms II. AI-enabled use cases are already reducing GHG emissions and can accelerate climate action • Across sectors, AI-enabled use cases have helped organizations reduce GHG emissions by 13% and improve power efficiency by 11% in the last two years. AI use cases have also helped reduce waste and deadweight assets by improving their utilization by 12%.

• Our modelling estimates that, by 2030, AI-enabled use cases have the potential to help organizations fulfil 11–45% of the ‘Economic Emission Intensity’ targets of the Paris Agreement, depending on the scale of AI adoption across sectors. For instance, for the automotive sector, AI-enabled use cases have the potential to deliver 8 percentage points of the 37% reduction (more than one-fifth) required by 2030.

• In the future, AI is expected to reduce GHG emissions by 16% and improve power efficiency by 15% in the next three to five years.

III. Even though climate action is a strategic priority, most organizations are struggling to support climate action with AI capabilities • 67% have made long-term business decisions to tackle the consequences of climate change.

• However, few organizations are successfully combining their climate vision with AI capabilities and have driven solutions to scale. We call these high-performing organizations – Climate AI Champions. They represent only 13% of the entire survey sample.

• A closer look at the challenges that organizations face in scaling AI for climate action reveals a range of issues: only 42% of the potential AI use cases are being experimented with and more than eight in ten organizations spend less than 5% of climate change investment on AI.

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