Introduction
Depending on the audience, the advancement with Generative AI (GenAI) is either the greatest technological advancement since the Internet or the single biggest threat to ending humanity. Many executive leaders are somewhere in between, having practical concerns and challenges when leveraging GenAI within their organizations. Given that four-fifths of Fortune 500 companies leverage Microsoft/M365 technology (and over 1 million companies in the US), the purpose of this article series is to examine how Microsoft technology addresses top CIO concerns and challenges to GenAI:
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- Potentially poor decision making with limited traceability – ensure generative AI models can produce unbiased and accurate results, but these models are often complex and difficult to interpret which makes it a challenge to trace the source of errors or biases
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- Investment priorities – Decide how much to invest in generative AI technology and how to allocate resources effectively
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- Data security – Ensure that generative AI models are secure and that sensitive data is protected
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- Lack of skills – Find and retain skilled personnel who can develop and maintain generative AI models
Stay tuned for the first installment of this series which will consider how Microsoft is addressing top concerns of GenAI as it relates to potentially poor decision making with limited traceability.
