GenAI solutions are currently in the early stages of development, despite generating significant excitement. Prior to full implementation, insurers need to carefully assess risks and limitations.
As per Mistry, while Large Language Models (LLMs) excel in general language tasks, they are not yet optimized for the specialized technical language prevalent in insurance, such as legal policy evaluations or claims processing. Mistry emphasizes the necessity for further training and customization of GenAI models to align with the specific speech, information, and procedures inherent in the insurance sector.
Bruch perceives the impact of AI as an evolution rather than a revolution, foreseeing the creation of new roles and gradual transformation of existing career trajectories over the coming years in the insurance industry. Bruch asserts that human emotional intelligence remains irreplaceable in the workplace, emphasizing the emergence of new job roles focused on developing, implementing, and overseeing AI systems. The integration of AI is poised to significantly reshape job profiles, offering substantial opportunities for online upskilling.
Despite the vast potential offered by GenAI, significant risks such as data security, confidentiality, ethical dilemmas, and liability issues accompany its adoption. There is a concern that historical data biases could be perpetuated by AI systems, potentially leading to discriminatory outcomes. The efficacy of these solutions is inherently tied to the quality and integrity of the training data.
Furthermore, GenAI has the capability to generate seemingly convincing yet false information through a phenomenon known as “hallucination.” This poses a new challenge as cybercriminals leverage such capabilities to perpetrate fraud, phishing scams, and the creation of “deep fakes”—digitally altered videos featuring manipulated content of real individuals.
Christopher Rau, Head of Online Law and Data Protection at Allianz Commercial, underscores the importance of ensuring that any AI utilization within the company adheres to principles of compliance, security, responsibility, and strict regulatory frameworks. Allianz is committed to upholding five core principles for ethical AI and data practices. Given its multinational presence, the company must navigate a complex landscape of laws and regulations, including evolving AI legislation like the recent Euro AI Act.
The global consortium of data scientists and AI experts at Allianz recognizes AI as a pivotal strategic consideration and remains vigilant in monitoring and exploring emerging trends. Data analysis and systems play a central role in the operations of insurers, underscoring the increasing significance of data within the industry.
