使用基础模型快速扩展应用的 AI ML并将其应用于现代 AI ML 用例.pdf

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1、Start from scratch valueLeveraging Foundational Models to Rapidly Scale Applied AI OutcomesNick King,Founder/CEO Data K35%of projects miss expectations.90%of S&P 500 companies now publish ESG reports in some form.McKinseyCustomer expectationsInvestor demandRegulatory requirementsCompetitive position

2、ingCorporate reputationOrganizations face mounting pressure to document and improve ESG performance$20BEvery year,Fortune 500 companies devote approximately$20 billion to their CSR efforts.ForbesTwo thirds of an average companys ESG footprint lies with suppliers.For some organizations with tens of t

3、housands of suppliers,its paramount to accurately capture their ESG footprint.Relying on manual processes,questionnaires and investigations is not only highly resource-intensive,but its also extraordinarily inaccurate.Dear Supplier,how ethical are you?A SMARTER ALTERNATIVEAutomate supplier ESG compl

4、iance at scale using LLM and Applied AI/MLHow does Applied AI accelerate this?Risk Identification and AssessmentAI can analyze vast amounts of data to identify potential ESG risks in the supply chain.It can assess the likelihood and potential impact of these risks,helping businesses prioritize their

5、 risk management efforts.Monitoring and ReportingAI can continuously monitor various data sources for new information that might indicate changes in ESG risk levels.It can also automate the generation of detailed ESG compliance reports,saving time and reducing the risk of human error.Predictive Anal

6、yticsAI can use historical data to predict future ESG risks.This can give businesses more time to develop and implement risk mitigation strategies.Decision SupportLarge language models can provide decision-makers with insights and recommendations based on their analysis of ESG data.This can support