This creates opportunities for increased efficiency, higher customer satisfaction, and new business models, while also confronting the industry with important questions related to responsibility, security, and ethics.
So far, players in the insurance industry have primarily focused on exploring AI to improve processes and develop better products, while ensuring that the technology is safe and compliant with existing regulations. However, AI may prove to have far more far‑reaching effects than many initially anticipate. The technology has the potential not only to streamline individual processes but to transform entire value chains and fundamentally influence how insurance is conceptualised. Looking ahead, the Nordic insurance industry will need to navigate a digital transformation in which AI can redefine both the market, the role of insurance companies, and the very content of insurance products.
The use of AI is still at an early stage and requires insurance companies to be even more adaptive and agile than before. This highlights the importance of building a culture and organisation that invests in change capacity and technological understanding. Insurance companies must develop the ability for continuous learning, experimentation, and rapid implementation of new solutions to keep pace with technological developments and changing customer needs. The future winners in the insurance industry will be those actors that manage to combine technological innovation with organisational agility and the ability to explore, test, and adapt in a market characterised by rapid change.
What If AI changes how risk is assessed?
The question “What if AI changes how risk is assessed?” goes deeper than simply making existing workflows in the insurance industry more efficient. If artificial intelligence fundamentally changes how risk is identified, evaluated, and priced, it could lead to entirely new ways of understanding and managing insurance. AI can uncover patterns in large volumes of data that were previously inaccessible, providing the basis for more accurate and dynamic risk assessments. This may challenge traditional models, create a need for new regulation, and change the roles of insurance companies, customers, and other actors across the value chain.
Example 1: Artificial Intelligence in vehicles
The implementation of artificial intelligence in vehicles is expected to lead to increased safety. The use of AI‑based safety systems and predictive maintenance, such as alerts for low tyre tread depth, can reduce the number of damage incidents. This results in a changed risk profile for insurance companies.
When the risk of damage decreases, insurance premiums should also be adjusted downward, as claims risk constitutes the main component of insurance pricing. As a result, insurance companies may experience reduced revenues and must therefore explore new sources of income. These may be found within new product or service areas. This requires insurers to be capable of change and to develop an adaptive mindset and organisational structure.
Example 2: Artificial Intelligence as a decision‑maker
AI is increasingly being used as a decision‑maker. This raises questions about who is responsible for the consequences of such decisions, and how a potential shift in responsibility from the policyholder (user) to AI affects the need for insurance.
It remains uncertain whether this reduces the need for insurance or whether responsibility must instead be placed elsewhere in the value chain. If liability shifts from insurance companies to software developers, this could affect insurance premiums, as the risk component associated with damage may be reduced.
AI requires insurance companies to rethink their organisation, technology, and business models. Those that succeed in building an adaptive culture, understanding how AI can transform the entire value chain, and forming strategic partnerships will be best positioned to succeed in a market where competition is intensifying, and customer expectations are rising. This is not just about digitising existing processes, but about creating entirely new forms of value in response to future technological opportunities.
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