The role of intelligent machines

As real-time, flexible, location- and interest-based targeting for insurance products becomes normalized, it will profoundly change the way risk is assessed. How should a pricing engine model a micro-insurance transaction when a tourist picks up an electric scooter and zips around an unfamiliar city? How should commercial property insurers use smart-buildings data to evolve a workplace policy by monitoring health impacts on employees down to the exact vicinity of their workstation?

The complexity and scale of this work is reflected in our study, which shows that the quantity of work performed by humans vs. intelligent machines will increasingly tip in favor of the latter, particularly in the areas of data management and sifting (see Figure 3). With growing volumes of data, machine-learning systems are needed to prepare the data to ensure it’s accessible, reliable and timely enough to be of business value.

How should commercial property insurers use smart-buildings data to evolve a workplace policy by monitoring health impacts on employees down to the exact vicinity of their workstation?

The march of the machines continues

Respondents were asked to what extent specific activities would be executed by machines vs. humans, now and in 2023. (Mean percent of work done by machines)

Response base: 285 insurance executives Source: Cognizant Center for the Future of Work Figure 3