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Regulatory compliance creates opportunities for AI on many levels, but only if AI can be trusted to manage risk at the same level of quality, resolution, and more efficiently than a human operator.
These three words, quality, resolution, and efficiency, are where AI struggles with regard to regulatory compliance. Why? Because regulatory compliance is a bespoke and unique exercise for every type of regulation and every organisation. While organisations are required to comply, what and how they comply are as unique as the organisation’s business model, operations, systems, and data.
There are no one-size-fits-all, big solutions that address regulatory compliance. Current AI models and the lack of the necessary ontological frameworks to ground reasoning do not exist to provide the necessary accuracy. For AI to provide levels of quality, resolution, and efficiency, AI needs to be grounded.
As put by Alex Karp of Palantir Technologies, organizations need to own their own models, compute, and have access to domain-specific ontologies. In the space of regulatory compliance Aegis Labs builds domain-specific compliance ontologies for compliance assurance. Demonstrating that size does matter, meaning that ‘Small is Indeed Beautiful’.
Liz Sandwith CFIIA Faisal Khan Ryan Buckner Michael G. Jacobides
#artificialintelligence #ai #domainspecific
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