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Post by account_disabled on Feb 27, 2024 3:09:19 GMT -5
The data used to train AI models is often limited or incomplete Meanwhile AI systems rely on vast amounts of training data to teach the AI to recognize patterns and create predictive models If the available data does not cover a wide range of different customer intentions the system may have difficulty understanding less common or unusual queries As a result some responses generated by AI may be inappropriate or incomplete making effective communication difficult This may lead to frustration among customers who expect precise and adequate answers to their questions or needs The development of advanced machine learning models such as deep neural networks can help improve Azerbaijan Mobile Number List understanding of customer intentions Introducing a greater variety of training data that takes into account different contexts and communication styles may also yield better results Additionally it is essential that AI systems are able to engage with live operators or customer service to obtain additional information or clarification when needed and human intervention can provide a more comprehensive and satisfying customer experience Data security and hacker attacks One of the main threats is the potential violation of customer privacy When communicating with AI customers may reveal sensitive information such as personal data bank account numbers passwords and medical information If this data is not properly secured there is a risk that it may be stolen or used in an undesirable manner This may lead to loss of customer trust and serious legal consequences for the company.
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