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However, Wilson warns of new questions on boundaries between personal and workplace data, spurred by such integrations. Driving sustainability goals With 2030 sustainability targets looming over companies, Kendra DeKeyrel, VP ESG & Asset Management at IBM, highlights how AI can help fill the gap.
Be sure to check out her talk, “ Power trusted AI/ML Outcomes with DataIntegrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.
Take the example of a client who integrated a set of disparate company ESGdata into a new dataset. Their data services were a full dataset download plus an API wrap around the data, which could be queried for ESGdata based on a company ticker symbol.
Organizations are facing ever-increasing requirements for sustainability goals alongside environmental, social, and governance (ESG) practices. This guide can be used as a roadmap for integrating generative AI effectively within sustainability strategies while ensuring alignment with organizational objectives. A Gartner, Inc.
By integrating environmental, social, and governance (ESG) criteria into investment strategies, ML facilitates capital allocation towards sustainable initiatives, renewable energy projects, and climate-resilient infrastructure.
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