eGain Warns of AI Knowledge Base Decay in Healthcare Contact Centers

eGain Corporation is alerting healthcare organizations to a growing risk within their contact centers: the decay of artificial intelligence knowledge bases, a phenomenon they identify as "AI knowledge drift." This occurs when the information AI systems rely on becomes outdated faster than it can be updated, potentially leading to incorrect responses and regulatory non-compliance.

The healthcare industry is particularly susceptible due to the rapid pace of change in policies and regulations. Continuously shifting factors such as drug formularies, prior authorization requirements, and benefit designs mean that AI systems can confidently provide answers based on information that is no longer accurate.

Unlike "model drift," which refers to a machine learning model's performance degradation, "AI knowledge drift" stems from issues with the content itself. Generative AI models retrieve and process information from their knowledge base without inherently knowing when that information has become obsolete, leading to flawed but confidently delivered answers.

Key healthcare-specific accelerants for AI drift include:

• Annual formulary changes
• Updates to CMS rules and guidance
• State Medicaid regulation shifts
• Payer policy bulletin cycles
• Provider network changes
• Benefit design modifications eGain urges healthcare providers to implement strong governance structures to ensure their AI systems are utilizing current and compliant information, thereby mitigating risks to patient trust and operational integrity.