Shaping change in insurance companies with AI

Will there be a new sales process in the insurance company? Is staff reorganisation imminent? Will new application routes be introduced in the back office? Should the corporate culture change? Or perhaps a new sales system is being rolled out? If so, now is the right time to look at successful change management. No time? Then it's worth reading on once again: artificial intelligence offers innovative solutions for change management and helps insurers to successfully master rapid change. This is followed by practical application examples and valuable tips for implementation in your own insurance company.

Storytime: Change bear Charlie from Nordlicht Lebensversicherungs-AG

Once upon a time there was a polar bear and his name was Charlie. Charlie worked at Nordlicht-Lebensversicherungs-AG. For some time, he and his team had been developing a new sales application for his bear colleagues in the field. On a normal Monday morning at the North Pole, Charlie had just finished his first iced coffee, the time had finally come. They rolled out the application and switched off the old system. Technically, everything was running smoothly. But suddenly... Suddenly the phones were ringing off the hook. The field service bears were confused, annoyed and had a thousand questions. Then the scales fell from Charlie's eyes: they had forgotten about change management. They had developed a great application, but nobody knew it, nobody knew how to use it and everyone was mourning the legacy system. From one day to the next, Charlie had become Charlie the Change Bear, but there was still so much to do for the application that he didn't really have time for it.

Change management: overcoming the iceberg of resistance

What exactly is change management? There are various scientific definitions, but in essence it can be summarised as follows: Change management is how you introduce changes into an organisation and ensure that they are well received.

This can affect individual employees, specific areas or the entire organisation. In addition to new technologies, change management also concerns new structures or processes in the company, a new strategy or a change in the corporate culture. Basically, only the weather can change without change management.

Even though change processes are very diverse in practice, three key activities can be identified:

• 1. communication with all stakeholders: this includes the concept, brand development, and content creation for the various channels, events and feedback opportunities.
• 2. qualification: This can be organised in the form of online training, a mentoring system or training events, for example.
• 3. project controlling: The aim here is to monitor the mood. This is why feedback in the form of interviews, surveys and workshops is primarily used here.

The biggest challenge in change management is the iceberg of resistance. And unfortunately, it's not just Charlie at the North Pole.

Above the surface of the water is the visible part of the resistance, for example direct rejection, critical questions and complaints from employees. This is where the apparent "factual arguments" are presented.

The larger and more complex part of the resistance is hidden beneath the surface of the water. This includes fears, insecurities, a lack of trust in management, the feeling of not being included or even the fear of not being able to cope with the new requirements.

In order to make change management successful, it is crucial to recognise and deal with this hidden resistance. In other words, change management is not something that can be done with a circular email and is becoming increasingly important: technological leap innovations are accelerating change and therefore also the associated change management. One of these new disruptive technologies is artificial intelligence (AI).

GenAI: A brief excursion into the big world of AI

Everyone has been talking about AI for some time now. But why is that? And what exactly does GenAI stand for? We take a brief look at the most important terms:

• According to the broadest definition, artificial intelligence is anything that emulates human intelligent behaviour, even if a human has programmed the algorithm, for example an expert system that analyses claims and decides whether to approve or reject a claim based on predefined rules.
• However, when we talk about AI today, we usually mean machine learning. And that means that computers learn from data and develop the algorithms themselves, for example a system that recognises fraud patterns in claims reports by learning from historical data and can therefore detect insurance fraud more effectively.
• Deep learning is a specialised field within machine learning. It is based on neural networks to recognise complex patterns in large amounts of data. A practical example of this is the automatic recognition and categorisation of damage based on photos of accident vehicles in order to speed up the handling process.
• This article will focus on a specific part of deep learning, Generative Artificial Intelligence - or GenAI for short. This involves the creation of new data that is similar to the trained data sets. And this is the moment when AI enters into dialogue with us, becomes creative and can truly inspire us with its output.

AI will bring about profound changes in every conceivable industry. In retail, AI is revolutionising inventory management, customer analytics and personalised shopping experiences. In healthcare, it enables more precise diagnoses, customised treatment plans and more efficient hospital processes. In the insurance industry, AI optimises claims processing, risk assessment and fraud detection, improves data analysis and decision-making and transforms the customer experience through personalised recommendations and automated interactions. In the manufacturing industry, AI leads to intelligent production lines that anticipate and avoid errors, while in logistics, AI-driven systems optimise supply chains and better predict stock levels. In education, AI provides customised learning paths that meet the individual needs of pupils. And the list goes on and on.

All these innovations should, of course, be accompanied by change management. But that is a challenging task at this pace. But the good news is that AI is not only a cause of faster change, but also provides valuable support for managing this change effectively.

GenAI for Change: The AI toolbox for successful change management

A Company GPT

Back to change bear Charlie. In order to make the new sales system known and popular in his sales team at the North Pole, he first needs a brand as an anchor for all subsequent communication measures. Charlie also wants to write his first newsletter article - basic communication tasks. Normally, Charlie would spend a few working days on this, needing polar bear colleagues for brainstorming and at least one other bear for quality assurance.

Generative AI can support the entire creative process and prepare everything to such an extent that Charlie only needs to take care of quality assurance himself at the end. In a self-experiment, I carried out Charlie's tasks with GenAI and only needed half an hour in total. The result:

Tools such as ChatGPT and Midjourney can provide support in Charlie's scenario and are also good helpers in the private sphere. However, when it comes to protecting customer data and company information in a real insurance company, the solution is better called: Company GPT. This not only brings with it all the advantages in terms of compliance-compliant content creation for change management, but can also be used by other areas of the company. It is a specialised version of a GPT (generative pre-trained transformer) that is adapted and trained for the specific needs and requirements of a company. While a general GPT such as OpenAI's ChatGPT is trained on a wide range of texts from the Internet, a company GPT is fed with company-specific data to support internal processes, communication and decision-making.

A knowledge agent

Another success factor for Charlie's Nordlink Sales system is the continuous and effective qualification of his sales team. Do his employees have questions about the new sales processes or the new application? An intelligent knowledge agent can help here. This knowledge agent is a chatbot that is available around the clock and answers all employee questions.

Imagine a sales representative wants to know how to use a new function in Nordlink Sales or what steps are required to report a claim. Instead of having to wait for an answer from the change team, they can consult the knowledge agent. This chatbot, which is based on an extensive and continuously updated knowledge database, provides precise answers immediately.

The integration of such a knowledge agent not only significantly reduces the workload of the change team, but also ensures that all employees are well informed at all times. The knowledge agent significantly accelerates learning processes by providing immediate feedback and support. For example, when a new sales process is introduced, employees can immediately access the knowledge agent for step-by-step instructions and explanations. As employees receive immediate answers and support, they feel more confident in using Nordlink Sales and are more willing to use and accept the new system.

Sentiment analysis

To effectively utilise the feedback from its sales team on the new Nordlink Sales, Charlie relies on AI-based sentiment analysis. This enables the fast and precise evaluation of feedback from free text fields, such as digital surveys or internal communication platforms.

For example, Charlie can conduct a survey among its employees following the introduction of a new function in Nordlink Sales. A sales representative indicates in a free text field that they have difficulties with the new user interface or miss certain functions. The sentiment analysis records this feedback, analyses the mood and uses it to create meaningful reports.

The AI not only analyses whether the feedback is positive or negative, but also identifies specific topics and common concerns. This enables Charlie to promptly identify which functions of the new system are well received and where there is still room for optimisation. For example, the analysis could show that many employees like the new search function but have problems with the speed of the system.

By analysing the feedback quickly and comprehensively, employees feel that they are being listened to and taken seriously. Charlie and his change team can respond promptly to the large amount of feedback and make targeted improvements to the new system and the associated communication. This not only helps to optimise the sales system, but also increases employee trust and satisfaction.

Another advantage of sentiment analysis is the ability to track trends and changes in feedback over time. Charlie can thus carry out its project controlling and recognise whether the measures to introduce the system are successful and how the mood among the sales force is developing.

How adesso supports

Are you like Charlie? adesso is a reliable partner for digital transformation in the insurance sector. We are not only technological leaders, but also understand how important people are in change management. We analyse the specific requirements and develop an individual strategy for the integration of GenAI into your change management. Your company can benefit from our in-depth industry expertise and methodological competence.

Would you like to find out more about exciting topics from the world of adesso? Then take a look at our previous blog posts.