Insurers must plan to exploit AI of they are to be market leaders and combat disruptive threats from digital giants like Amazon. Yet there are major barriers to progress.

  1. Lack of clear AI strategy
  2. Lack of AI talent
  3. Functional silos constrain multiple AI applications
  4. Lack of leader's ownership & commitment
  5. Lack of technical infrastructure to support AI
  6. Lack of collected data
  7. Limited usefulness of data
  8. Lack of changes to frontline processes after AI's adoption

One  critical enabler of AI is a companies progress on its digitisation journey. Unless you have the digital platform and strategy to complete this you are doomed to fail when it comes to AI.

So get your priorities right, deploy digital processes combined with orchestration of customers, insurers staff and the complete supply chain. Combine the data management, analytics and decision-making processes that are the platform for a viable AI strategy and project.

And remember that AI is only a part of the overall story. Even the manufacturer of the world's most AI enabled vehicles and manufacturing plants, TESLA, is still dependent on technology deployed in 1968 :- 

Programmable Logic Controllers (PLCs). 

These replaced electro-mechanical relays but still operate in a rigid and structured manner. It takes weeks for consultants to reconfigure these in the same way it takes weeks or longer to reconfigure insurer's core legacy systems. Robots are tied to this limitation.

This is one reason why it takes longer and costs more to plan and deploy AI then vendors pretend when hyping the benefits.

Nevertheless insurers need to square the circle and choose insurtech partners that deliver the digitisation journey and provide the digital platform for  effective General Artificial Intelligence.

The McKinsey report below shows the steps to take.

Further Reading:

Building New Data Engines for Insurers

Insurance 2030—The impact of AI on the future of insurance

AI- "Analogue Fools rush in where Digital Angels fear to tread".