<?xml version="1.0" encoding="UTF-8"?>
<mods xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns="http://www.loc.gov/mods/v3" version="3.1" xsi:schemaLocation="http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-1.xsd">
  <titleInfo>
    <title>How AI can enable a Sustainable Future</title>
  </titleInfo>
  <name type="corporate">
    <namePart>Microsoft</namePart>
  </name>
  <name type="corporate">
    <namePart>PricewaterhouseCoopers‏</namePart>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="code" authority="marccountry">xxu</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Washington]</placeTerm>
    </place>
    <publisher>Microsoft</publisher>
    <dateIssued>[2019]</dateIssued>
    <dateIssued encoding="marc">2019</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
  </language>
  <physicalDescription>
    <form authority="marcform">electronic</form>
    <internetMediaType>pdf</internetMediaType>
    <extent>51 p. : il. ; 1 documento PDF</extent>
  </physicalDescription>
  <targetAudience authority="marctarget">specialized</targetAudience>
  <note type="statement of responsibility">/ Microsoft in association with PwC</note>
  <note>Artificial Intelligence can be harnessed in a wide range of economic sectors and situations to contribute to managing environmental impacts and climate change.Some examples of application include: AI-infused clean distributed energy grids, precision agriculture, sustainable supply chains, environmental monitoring and enforcement, and enhanced weather and disaster prediction and response. Research by PwC UK, commissioned by Microsoft, 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 $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 offering more skilled occupations as part of this transition.</note>
  <subject authority="lcsh">
    <topic>Tecnologías habilitadoras digitales</topic>
  </subject>
  <subject>
    <topic>IA</topic>
  </subject>
  <subject>
    <topic>environmental impacts</topic>
  </subject>
  <subject>
    <topic>climate change</topic>
  </subject>
  <subject>
    <topic>environmental applications </topic>
  </subject>
  <subject>
    <topic>economy</topic>
  </subject>
  <subject>
    <topic>greenhouse gas</topic>
  </subject>
  <identifier type="uri">https://www.pwc.co.uk/sustainability-climate-change/assets/pdf/how-ai-can-enable-a-sustainable-future.pdf</identifier>
  <identifier type="uri">https://www.pwc.co.uk/services/sustainability-climate-change/insights/how-ai-future-can-enable-sustainable-future.html</identifier>
  <location>
    <url displayLabel="Acceso al documento">https://www.pwc.co.uk/sustainability-climate-change/assets/pdf/how-ai-can-enable-a-sustainable-future.pdf</url>
  </location>
  <location>
    <url displayLabel="Más información">https://www.pwc.co.uk/services/sustainability-climate-change/insights/how-ai-future-can-enable-sustainable-future.html</url>
  </location>
  <recordInfo>
    <recordContentSource authority="marcorg">ES-MaONT</recordContentSource>
    <recordCreationDate encoding="marc">190823</recordCreationDate>
    <recordChangeDate encoding="iso8601">20231116104400.0</recordChangeDate>
    <recordIdentifier source="ES-MaONT">00005558</recordIdentifier>
  </recordInfo>
</mods>
