Optimized next steps: Suggest an independent medical exam or other steps already demonstrated effective for similar claims.
Modified work assignments: Recommend appropriate modified duty assignments, ensuring a smoother transition back to work.
Rehab plans: Suggest tailored rehabilitation or physical therapy programs, expediting recovery and potentially reducing claim duration.
Cost-cutting strategies: Propose cost-effective measures, such as utilizing in-network medical providers.
Communication recommendations: Offer guidance on the best communication practices between the injured worker and healthcare providers, ensuring a smooth flow of information.
A key concern in AI adoption is the singapore whatsapp number data concept of “explainability” or the system’s ability to explain how it makes decisions. Traditional AI models can seem like “black boxes,” leaving professionals perplexed. GenAI addresses this by providing interactive decision support, explaining results in plain language, and even engaging in conversations. For example, if a medical term appears in a claim, insurers can ask open-ended questions and engage with GenAI to obtain a clear, easy-to-understand explanation, enhancing their confidence by clarifying the factors impacting risk predictions. GenAI helps users comprehend the reasoning behind the model’s conclusions, playing an important role in establishing trust and accountability, essential in the insurance industry.
Challenges Adopting AI in Insurance
The collaboration of traditional and GenAI holds immense promise for insurers. However, there are challenges that must be addressed.