A perspective on the surprising reality

Think of artificial intelligence (AI) and you’ll think of factories of robots doing manufacturing jobs. You may think of logistics and evoke imagery of robots doing their thing for the likes of Amazon. However, whilst the media often focuses on these radical and wide-reaching applications of AI, there are other forms of adoption which are quietly stirring a revolution. We see this in the way AI is used, and being developed, within the insurance sector.

What’s particularly interesting is that these wide-reaching forms of AI aren’t the headline makers. These are a gradual, systematic replacement of tasks which can easily be enhanced by AI. They are the tasks which are usually overlooked for their impact on effectiveness, productivity and efficiency. However, it’s right here that changes are really having an enormous impact.

Thomas H. Davenport and Rajeev Ronanki in Artificial Intelligence for the Real World published in the Harvard Business Review call these types of AI projects “low hanging fruits”. They are the easy to achieve, lowest cost to implement, yet have a significant effect on improvement. They crucially state that these less ambitious implementations of AI are far more likely to be characterized by success than much more ambitious AI projects.

This is an essential distinction to understand when the Davenport-Ronanki report also explains that three-quarters of their surveyed companies believe that “AI will substantially transform companies within three years”. That substantial transformation is coming in a lower key, but notably impactful, different from the way the headlines would have us believe.

The story of AI

Discussion on AI typically centers on how technology works. To really understand the development of AI, particularly in the insurance industry, we need to flip this on its head. We need to instead consider what can this technology solve? This enables us to see the potential and real-world application of AI rather than a technological history lesson and set of predictions.

In this way AI has three broad ways of meeting business need:

1. Automation behind the scenes: Such as using AI to manage data – inputting, recording, transferring and all the basic use of data going on in back office admin. Using AI here is exceptionally low cost for high return and very easy to implement.
2. Insight through analytics: Here AI is a little more ‘intelligent’ with a greater degree of machine learning. The concept is to mimic the human brain with greater efficiency. AI here is used to do such things as predict customer purchases, use personalization in adverts or do things such as identify insurance fraud.
3. Engagement: Less popular but still of interest, is the use of AI to improve or facilitate customer and employee engagement. This is evidenced in the likes of chatbots or highly customized product recommendations.

How the insurance industry is developing and utilizing AI

Within these three categories, we are seeing exciting development within the insurance industry which is exposing the real tangible use of AI for the future. It is evident in the start-ups which are disrupting the sector. Here Ai is changing how insurance is ‘done’.

Let’s look at current examples of insurance industry solutions in the different business areas:

• Automation: Hyperscience turns documents in to machine readable data. This removes a labor intensive task from admin. It also has the benefit that machines aren’t prone to human error. Blue Prism has created a Digital Workforce Platform using intelligent Robotic Process Automation (RPA). UiPath also uses RPA, this time in claims processing.
• Analytics: Dacadoo  uses dynamic pricing which responds to both customer behavior and market circumstances through app-based lifestyle solutions used in conjunction with Health/Life insurance. Brolly uses insights and behavior analytics through a management app to offer both advice and insurance, thus focusing on AI-based underwriting. RightIndem uses voice analytics to accurately process claims on a 24/7 basis. The aim is to settle claims accurately and quickly, whilst also screening out attempted fraud.
• Engagement: Boundlss uses app technology to actively engage customers in personalized conversations designed to motivate and improve health choices and lifestyles. Spixii is an AI-based chatbot technology. Its success has already been evidenced with Zurich’s chatbot ‘Zara’. Prenetics uses genomics which insurance companies can utilize to gain personalized knowledge of an individual to help them prevent disease.

Humanization versus automation

There is no doubt that AI, particularly used in the arena of ‘low hanging fruits’ is bearing an exceptional harvest. These solutions, in use now and on the horizon, are working and tangible and the real AI revolution.

Bear in mind that this is within the context of prediction by Forrester that by 2025 technology (including AI) will have replaced 7% (22.7m) jobs in the US.

However, we need to be open to the problems and challenges. We also must never lose sight of what we’re aiming for. AI in insurance is very much being used for customization and personalization as expected by Millennials and Generation Z. This means there is a need for humanization too.

A fantastic example of this on-the-ground can be seen with Tesla. Automation was introduced in Tesla’s model 3 production facility which was widely regarded as one of the most advanced car manufacturing plants in the world. Elon Musk took the decision to replace robots in the factories with humans.

What we can learn from this is that AI and humanization need to become intertwined bedfellows if we are to stop just considering how technology works, but actually using it to solve our industry specific problems. Humanization brings some strengths, automation brings others. The human-factor brings creativity and innovation, and the ultimate judgment capability. AI and technology can bring efficiency, speed, accuracy and an ability to handle the complex on an enormous scale.

The future of AI in the insurance sector is looking incredible. It’s changing how we do things and it will continue to do so. We need to pay attention to how we develop and use it, alongside humanization, to remain intensely focused on our goals and not just our capabilities.