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They prioritize employment based on opportunities to further develop data science skills in support of meaningful work. Blindly handing over responsibility to a machine is not just uncomfortable, it’s unadvisable. AI-supported processes must support a transparency that allows people to observe the process and freely take control when necessary.AI algorithms do not match the full awareness and competency of people. The complexity of delivering unbiased and valid financials demands that people remain engaged in the automation loop.
As the chief steward for an organization’s financial health, the CFO must balance the risks and rewards of tools like generative AI. Three distinct conversations across leadership circles will help CFOs establish reasonable expectations and ensure that the use of generative AI creates value without introducing unacceptable risks.
Finance leaders whose functions are not yet using AI cited four primary reasons: other priorities, lack of technical capabilities, low-quality data and insufficient use cases. Across a diverse set of areas, 64% of finance organizations using AI report that its impact has either met or exceeded their expectations. These CFOs can expect this impact to compound as their more complex AI techniques mature and provide greater value in Year 2 or 3.
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