Other parts of this series:
Insurers examining the potential of AI-based solutions need to decide whether to automate or augment. That means determining whether processes and activities rely heavily upon human judgement and interaction or are more objective and rules-based.
As I discussed in my previous blog, artificial intelligence is opening many new doors for insurers. In many cases, insurers looking at AI use cases must decide on one of two approaches. Do they use AI to automate existing processes, or combine it with human intelligence to augment the abilities of the human workforce?
Processes that lend themselves to automation tend to be straightforward and objective in nature. There should be minimal human interface with customers and little need for context. In many cases, such processes are limited to a single channel.
Situations better suited to augmentation are those that require the decision maker to be emotionally aware and sensitive to the customer’s needs. These may be complex or unique, and frequently span multiple channels. Finally, the organization may wish to evolve and/or learn from the experiences related to such situations.
AI technologies have the ability to automate or augment a wide range of work activities that today are largely done by humans, including both manual workers and knowledge workers. Delivering business value from cognitive computing requires understanding the nature of the work being done along two dimensions. The first is data complexity, or the degree to which complex, unstructured, changing data needs to be taken into account. The second is work complexity, or the degree to which individuals need to apply their judgment and interpret a variety of information.
There are many possibilities for automation and augmentation via AI in insurance. In my next post, I will look at some promising areas for exploration and potential investment.