Integrating large language models (LLMs) into business workflows boosts efficiency and enhances customer engagement. In regulated sectors like healthcare and finance, LLMs face challenges in data privacy, compliance, and security. Off-the-shelf models often fall short of meeting strict regulations, leading organizations to seek customized solutions. Generic models present risks such as unclear data storage, lack of auditability, potential for generating incorrect responses, and insufficient domain knowledge. Businesses must prioritize bespoke LLMs to ensure security and compliance while effectively leveraging AI technology.
Data privacy is a crucial concern for regulated industries, where public LLMs' storage methods raise significant risks under regulations like HIPAA and GDPR.
Generic LLMs often lack auditability, failing to log queries or provide necessary traceability in sectors like finance and law, where justification is essential.
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