adesso Blog

Microsoft has invested in OpenAI to gain access to ChatGPT, and the company is now integrating generative AI into tools such as Microsoft 365. These AI-based copilots improve productivity and efficiency, especially in regulated industries where you find many recurring tasks and large amounts of data. Copilots help optimise workflows as financial or claims management tools. My blog post will take a look at Microsoft Copilot for Microsoft 365, a tool that is used in the banking and insurance sector, as one example of an AI-supported assistant.

Generative AI has been everyone’s mind since ChatGPT came on to the scene. But what exactly does this term mean and how is generative AI different from the well-established concepts of machine and deep learning? This blog post takes a general look at AI technologies and highlights the differences that make generative AI so intriguing and promising in an ever-changing world.

GenAI opens up great opportunities for insurance companies to generate value. Likewise, it is also becoming a key driver of their digital transformation. The rapidly evolving technology can be used to automate and speed up insurance processes and significantly improve the customer experience. From a financial perspective, insurers benefit from GenAI’s ability to more accurately assess risks.

Ethical considerations should be at the forefront of AI development to harness the full potential of AI while minimizing its negative consequences.

The world of artificial intelligence is developing at a breathtaking speed, and large language models (LLMs) are at the forefront of this revolution. LLM operationalisation is an essential part of this development and offers companies the opportunity not only to push the boundaries of technology, but also to set new standards for human–machine interaction. We explain why this is the case in our blog post.

The Artificial Intelligence Act (AI Act) was finalised at the end of 2023 after intensive negotiations between the European Parliament and the European Council. The debates were characterised by talks on the definition of AI and the categorisation of systems into risk classes. Numerous details were clarified, in particular regarding unacceptable risk (highest risk level) AI systems and high-risk AI systems. National interests and the development of certain technologies played an important role, such as the ban on real-time biometric identification in public spaces and the use of foundation models or generative AI. I will show you in this blog post what the EU AI Act looks like in detail.

The ‘Intelligent knowledge database – support during Aleph Alpha integration’ project focuses on the use of Aleph Alpha’s large language models to make the day-to-day work involved in maintaining text documents and editorial processes more intelligent and efficient. adesso implements the work processes for data analysis and clustering in the database as a pro bono service. In my blog post, I will provide a detailed look inside the workshop that accompanies the AI project as well as key aspects of it.

In this blog post, I will take a closer look at traceability tools that show great promise with you and go beyond theory by showing practical applications in AI projects. I will also be presenting a demo to show how these tools not only support the technical side of research, but also how they can be used in practice.

With all the hype currently surrounding generative AI (GenAI), people are divided into two main camps, namely those who support it and those who remain sceptical. This blog post provides a short overview on how GenAI can drive innovation in the insurance sector and why effective change management is important for both its sceptics and proponents.