Generative AI providers and their partners must commit to responsible development and deployment.
In another example, insurance companies face a multitude of motor accident claims. Contextualized GenAI cognitive data extraction platforms can effectively integrate various elements of unstructured information from insurers, such as call center transcripts and bot conversations, to efficiently handle these claims. Furthermore, contextualized GenAI can identify subrogation opportunities and calculate relevant amounts.
Sector contextualization and domain expertise can significantly improve features like content generation, content extraction, summarization, translation and knowledge management for LLMs.Moving away from the traditional seller-client model, contextualization calls for a partnership approach between businesses and gen AI providers. By closely collaborating—actively engaging in GenAI pilots, proofs-of-concept and cross-functional R&D projects—they can unlock the full potential of GenAI.
As the technology evolves, businesses and their business process management partners must work together to upskill their teams on GenAI usage, create new roles and opportunities and augment capabilities and responsibilities for operations.Considering the concerns surrounding AI expressed by governments, academicians and industry experts, GenAI providers and their partners must commit to responsible development and deployment.
To capitalize on the immense potential of gen AI, companies and their BPaaS providers should foster ecosystems where data scientists and AI specialists work hand-in-hand with domain experts to contextualize gen AI across various industries. A mature, ethical and innovative approach will make GenAI accessible to all.
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