Artificial intelligence (AI) offers enormous opportunities for all industries and will also revolutionise the insurance industry in many ways, for example through the automation and optimisation of processes, personalised customer contact, more precise risk assessments and more efficient claims processing.
The latest Scale AI Deep Dive Day organised by InsurTech Hub Munich therefore focused on the topic of “The AI-supported customer journey in insurance sales”. In addition to current trends and sales topics, regulatory framework conditions and aspects of how to accompany these changes and jointly develop concrete use cases for the use of AI were also discussed.
The customer at the centre – opportunities through AI
The workshop started with an introduction to AI, highlighting the current state and trends in insurance sales. Cross-industry insights were emphasised in order to provide participants with a broad perspective on the implementation of AI. Digital sales were discussed in particular, with a focus on the opportunities offered by the use of AI and its scaling options. There were also initial assessments of the creation of an AI maturity level in companies.
AI-driven sales: experiences and impulses
Exciting presentations on AI-driven sales were then on the programme. The focus was on conversational AI and personalisation in customer dialogue. ERGO served as an application example for conversational AI in customer service and sales. Current examples were explained and new potentials through Generative AI and Large Language Models (LLMs) were shown. In addition, it was shown how it is possible to combine human advice with digital tools and use customer dialogue with Generative AI as the key to customer loyalty.
In focus: Concrete AI use cases
The morning focussed on the development of two specific AI use cases in the breakout sessions: the AI knowledge manager for sales and the AI mail assistant for preparing quotations. Against the background of their own challenges, the participants jointly developed possible scenarios and goals, assessed opportunities and risks as well as costs and benefits and outlined initial concrete use cases.
After the lunch break, the groups presented their results. These sessions gave the participants the opportunity to present the ideas and concepts they had developed and to receive feedback. Recommendations were also made on AI tools and IT infrastructure to support development and operational processes for AI solutions.
Framework conditions for the use of AI
Another important aspect of the workshop was the necessary framework conditions for the use of AI. This included regulatory frameworks such as laws, regulations and guidelines, as well as recommendations for the use of AI in companies and technological frameworks such as quality, efficiency and data sovereignty with recommendations for the selection of closed vs. open models.
Change & transformation throughout the entire organisation
The afternoon was dedicated to the topic of change support in AI-driven transformations. Employee support is one of the most decisive factors for the successful use of AI in companies. The focus here is not only on empowerment and skills development, but also on the acceptance and subject-specific adoption of AI tools. . The challenges and the path to AI business transformation, role changes in sales and specific recommendations for pilot projects were the subject of lively discussion.
Summary and takeaways
The workshop concluded with a summary and the most important findings of the day. These are briefly summarised:
- Courage and responsibility: It takes courage to take the risk of AI investments and assume responsibility for them.
- Seek reinforcement: Finding fellow campaigners for joint action is crucial – this is how you can achieve more together.
- Framework conditions “willing, allowed, able”: These framework conditions help to create the necessary conditions for a successful AI transformation.
- Customer focus: The customer should be the most important reason and driver for AI use cases.
- Out-of-the-box thinking: It is important to always take time to think outside the box and try things out.
- Keep pivoting and adapting as you go: Flexibility and a willingness to adapt the course are essential.
The participants went home with a clear understanding of the opportunities and challenges that AI offers in insurance sales, as well as concrete strategies and application examples. The Scale AI Deep Dive Day showed that artificial intelligence can revolutionise not only the future of sales, but also the entire insurance industry. The participants are now well equipped to take the next steps towards an AI-driven transformation.
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