凱捷（Capgemini）：2020年氣候人工智能報告-人工智能如何為氣候行動戰略提供動力（英文版）.pdf

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1、How artifi cial intelligence can power your climate action strategy Executive summary 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, an

2、d 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 t

3、en 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 effi

4、ciency 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 managemen

5、t 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

6、 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 1145% of the Economic Emission Intensity targets of the Paris Agreement, depending on the

7、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

8、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 su

9、ccessfully combining their climate vision with AI capabilities and have driven solutions to scale. We call these high-performing organizations Climate AI 2AI in Climate Change Champions. They represent only 13% of the entire survey sample. A closer look at the challenges that organizations face in s

10、caling 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. IV. How organizations can leverage AIs full climate action potential We believe t

11、hat six action areas are critical: Account for, and take measures to combat, the negative impact of AI on the climate. Educate sustainability teams on how AI can make a real difference and educate AI teams on the criticality of climate change. Lay down the technological foundations for AI-powered cl

12、imate change action. Scale use cases on the basis of impact for your sector and emissions intensity of particular functions. Collaborate with the climate action ecosystem. Harness AI to bring greater focus in reducing scope 3 emissions. The research approach draws on a range of tactics, from using c

13、limate models developed in partnership with right. based on science a climate startup for estimating the impact of AI on greenhouse gas (GHG) emissions to a survey of over 400 sustainability executives and 400 business/tech executives from the automotive, industrial/process manufacturing, energy so

14、while organizations are taking steps, its certainly not at the pace that we need to be consistent with the science.” Investors are now actively shunning companies with low ratings or performance on ESG metrics. One of the largest asset managers in the US, BlackRock, recently put 244 companies “on wa

15、tch” for failing to take sufficient action on climate change. It also took voting action (holding directors accountable or supporting shareholder proposals) against 53 of these.8 As a result, organizations across industries need to adopt radical methods, make adequate investments, and deploy appropr

16、iate tools, technologies, and strategies to achieve this goal. These are challenging goals for the world economy and society, but technology offers an exciting opportunity for organizations to make a real difference. “Our assessment shows that with digitalization, artificial intelligence, big data a

17、nalysis, deep learning, we can realize a green economy much more easily with those technologies than without them,” says Dirk Messner, president, German Environment Agency; Board Member, Stockholm Energy Institute. “However, despite the potential, during the last two decades, these technologies have

18、 not been used enough to really solve the climate and environmental and earth system challenges. We still have non- sustainable growth patterns in most economies and organizations around the world. We need to make the link proactively between climate politics, earth system stabilization strategies o

19、n the one hand side and these modern technologies on the other.” If organizations and countries globally do not take decisive action, our planet is set to warm by almost 30C by the end of the century double the rate needed to constrain the worst impacts of climate change.9 Over the last few decades,

20、 organizations have been taking significant measures such as decommissioning coal plants and directing more funds to renewables and less to fossil fuels. However, using technology levers to contain the effects of climate change is rarely seen as the biggest enabler. Among the technology levers, whil

21、e the spotlight often falls on point solutions that address a specific outcome such as carbon capture technologies to remove CO2 from the atmosphere, 6AI in Climate Change or renewable sources of energy few technologies offer advantages that cut across sectors and value chains. Recent advances in Ar

22、tificial intelligence (AI) for instance, in image recognition powered by deep-learning neural networks is one such fast-emerging field, and points to AIs significant potential that is yet untapped. We believe that AI solutions when deployed sustainably, complementing technological and various other

23、levers to reduce carbon footprint, offer a sizeable and promising opportunity that is worth exploring. AI offers unique opportunities to accelerate organizations climate action Our recent research shows that the adoption of AI across organizations has been on the rise with more than one in two organ

24、izations (53%) moving beyond pilots or proofs-of-concept in a few or more use cases.10 Given that organizations are already beginning to deploy AI at scale, it is an opportunity for organizations to also explore AI-enabled use cases from a climate action perspective and how existing AI deployments o

25、r new innovations could also bring climate- positive outcomes (see section 1 on “AI offers many climate action use cases”). In recent years, several AI use cases have been identified that offer significant value in improving energy efficiency, reducing dependence on fossil fuels, and optimizing proc

26、esses to aid productivity all contributing significantly to climate action.11 For instance, Air France uses Sky Breathe an ML and AI platform to provide a series of recommended actions that can reduce the total fuel consumption by up to 5%. Various airlines have used the solution to save more than 5

27、90,000 tons of CO2 in 2019.12 Getting the focus right can have significant benefits in the long run. As we heard from James McCall, Senior Director Global Climate and Supply Chain Sustainability, Procter for the GHG emissions reduction rates, sector-specific estimates from our survey are used (the d

28、etailed methodology is described in the Appendix). For the automotive sector example, as shown in Figure 6, this scenario represents a total EEI improvement of 8% in 2030 over the Baseline Scenario. This means that by using AI-enabled use cases for emission reduction, automotive organizations can me

29、et more than a fifth of their EEI reduction requirement by 2030. We then compare these two scenarios with the “Beyond 2 Degree Scenario” (B2DS) of the International Energy Agency a scenario that aims to limit global warming to 1.75C,30 in line with the Paris Agreement. Using the XDC Model and the em

30、issions budgets from the B2DS, we compute an EEI target pathway for each sector. This EEI target pathway represents how fast organizations EEI must reduce in this sector to be compliant with the Paris Agreement. For instance, the target pathway for the automotive sector requires an EEI reduction of

31、37% by 2030 over Baseline levels (see Figure 6). 18AI in Climate Change Figure 7. AI-enabled use cases have the potential to aid organizations to achieve 11-45% of their EEI reduction targets by 2030 14% 42% 17% 38% 4% 38% 8% 37% 7% 36% B2DS pathway reduction (for global warming to 1.75C per IEA and

32、 Paris Agreement) AI-enabled pathway reduction AIs potential in Economic Emissions Intensity reduction by 2030 compared to baseline reduction AIs potential contribution as share of EEI reduction 18% 22% 11% 45% 32% Oil and Gas Automotive Utilities Wholesale retail Consumer retail Source: Capgemini R

33、esearch Institute and right. based on science analysis. We conducted the above analysis for five sectors in our survey and for each sector, and we found that the use of AI-enabled use cases yields a 417% of EEI reduction by 2030 compared to the Baseline Scenario (see Figure 7). In terms of the share

34、 of target EEI reduction, AI-enabled use cases can deliver 1145% of the requirement between 201830. Consumer retail has the greatest potential for AI-driven improvements at 45%, while wholesale retail offers the least at 11%. 19 The COVID-19 crisis has slowed organizations progress on climate goals

35、The COVID-19 crisis has made people more aware of sustainability issues. It has also led to some positive policy initiatives, especially in Europe. The European Parliament has put a “Green Deal” at the core of its economic recovery from COVID and it aims for the EU to be climate neutral by 2050.31 I

36、n October 2020, the European Union parliament voted to cut greenhouse gas emissions by 60% by 2030 compared to 1990 levels.32 However, in the immediate term, we found that over a third of sustainability executives (37%) said that the COVID-19 crisis has decelerated their climate goals (see Figure 8)

37、. The deceleration is at the highest in the energy and utilities industry. As Dr. Faith Barol, executive director of the International Environmental Agency noted, “Despite a record drop in global emissions this year (2020), the world is far from doing enough to put them into decisive decline.” 33 Fi

38、gure 8. Impact of COVID-19 pandemic on progress against climate goals: accelerated vs. decelerated Source: Capgemini Research Institute, AI in climate action survey, JulyAugust 2020, N=400 sustainability executives. It has accelerated our actions towards our climate goals It has decelerated progress

39、 on our climate goals and pushed them further away How has the COVID-19 crisis aff ected your long-term climate goals? 14% 37% Overall 20% 39% Manufacturing/ Process industry 14% 41% Energy and Utilities 11% 36% Automotive 11% 33% Consumer Products and Retail The potential of AIs contribution to rea

40、ch the required goal of IEAs Beyond 20C Scenario for the consumer retail sector. 45% 20AI in Climate Change Looking deeper into potential reasons behind this deceleration, and as Figure 9 shows, we found that: 46% said they had put one or more climate initiatives on hold (this increases to 53% in au

41、tomotive). 38% have put a hold on capital expenditure allocated for climate initiatives (increases to 47% in process manufacturing). Figure 9. One in two organizations have put climate initiatives on hold owing to the COVID-19 crisis Source: Capgemini Research Institute, AI in climate action survey,

42、 JulyAugust 2020, N=400 sustainability executives. Overall 46% 38% 41% Automotive 53% 42% 36% Consumer Products and Retail 49% 32% 50% Energy and Utilities 46% 40% 38% Manufacturing/ Process industry 37% 41% 38% Which of the following is true for your organization owing to the COVID-19 crisis? We ha

43、ve had to put one or more climate change initiatives on hold We have had to put capital expenditure for some or most climate initiatives on hold We expect a loss of capabilities and talent critical for our climate change initiatives Share of organizations that expect a loss of capabilities and talen

44、t critical for climate change initiatives due to Covid-19. 41% 21 3. Even though climate action is a strategic priority, most organizations are struggling to support climate action with AI capabilities Climate action is a top priority for organizations Climate action and controlling emissions are ma

45、jor strategic priorities for organizations and their leaders: 67% have made long-term business decisions to tackle the consequences of climate change. 60% of sustainability executives said that climate change strategy is embedded in their business strategy. 70% of sustainability executives said they

46、 have a governance body to oversee their organizations climate objectives and/or review the progress achieved by the sustainability/climate change team. As Figure 10 shows, the most popular areas of focus are driving carbon-neutral operations, focusing on achieving net- zero greenhouse gas emissions

47、. Figure 10. Top five actions that form a part of organizations climate action Source: Capgemini Research Institute, AI in climate action survey, JulyAugust 2020, N=400 sustainability executives. 1 2 3 4 5 Carbon-neutral operations: Carbon emissions balanced by carbon savings Paris Agreement tempera

48、ture alignment: Contributing to limiting temperature increase RE-100: Shifting to 100% renewable energy for all operations and energy use Emission reduction: Setting goals for science-based overall reduction of GHG emissions from operations Industry benchmark: Benchmarking organizations climate prog

49、ress vis-vis its industry 22AI in Climate Change Share of organizations that have been able to couple strong AI applicabilities with concrete climate action and strategy. 13% As they set their ambition and goals, half (52%) have aligned their chosen approach and actions to the wider United Nations Sustainable Development Goals (SDG) agenda, and 37% plan to do so the future. However, in terms of their long-term strategy, 84% executives said that they would rather compensate for (or offset) their carbon footprint than deploy techno