To help you begin to navigate this complex reality, I will briefly explain the four major types of AI application, describe some positive impacts, and then discuss the risks to those less able to adapt.

The 4 Types of Applied Artificial Intelligence

We need to start with pointing out that there are four commonly used types of applied artificial intelligence, and we will look at them one by one. AI for Insight is the technology that can help you examine enormous amounts of data to find trends patterns, and points of inflection. It can help you ask some extraordinarily big questions such as “Have my customers’ needs changed?”. AI for Decision Making automates relatively straight-forward decisions such as whether an insurance claim should be approved. AI for Operations is about the software robot. Such a robot can observe staff copying data manually from one system to another, and then replicate the task with a high degree of accuracy. Finally, there is AI for Engagement which takes the place of a human in engaging with your customers; we are moving to a time when an AI for engagement program can answer simple super related questions in real time.

The Benefits of AI Applications

Now, there is certainly plenty of good news to glean from the emergence of these technologies. Firstly, many of the AI applications are for activities that we could not cost-effectively do beforehand. For example, we can now use deep historical information to run models for unique customer portfolios across hundreds of different economic scenarios. Yet what is really different is that these models can now automatically get smarter the more information we feed them. This takes the applications of portfolio modelling out of the general and expensive, to the very specific and the eminently affordable.

Secondly, AI applications can ensure that many superannuation operational functions can be dramatically faster and more efficient. AI for operations, which mostly involves software programs which have been called robots, can massively reduce errors and costs in superannuation processing. For example, such robots can scan contributions data to ensure that accounts are updated instantly. Furthermore, robots can reduce much of the irritating and frustrating use of forms. Some robots can pre-fill forms whilst others can rekey data from one system to another.

Risk & Adaptation

Yet AI and robotics introduce two types of highly probable risk. Firstly, there is the risk of falling behind, either on the insights that AI can yield, or on the efficiencies it can bring. Businesses falling behind the application of these technologies will find themselves at an information, service or efficiency disadvantage. Secondly, there are people in the super industry who are performing automatable tasks but have little capacity to reinvent themselves. These are the people who can be genuinely said to be at employment risk.

One particularly important take-away from the above discussion is that there is no part of the superannuation industry that is immune from these changes. Whether you are in asset allocation, investment selection, product management, advice, compliance, operations or any other part of the industry, your role or function could be subject to change. So, what’s the best way to cope with this change? Well get to know what is going on in your industry and plan to adapt. The earlier you experiment with how to use these technologies in your business the more you will find these technologies a boon rather than a burden.

By Roger Perry – CEO Bevington Group