*The GPT Assistant SwissGPT from AlpineAI was used to create the following texts. The download at the bottom of this page was created exclusively by me (Sophie Hundertmark), without the support of AI.

What is Generative AI?

Generative AI refers to systems that create data models from a collection of information and then generate new content based on these models. In contrast to discriminative models, which are trained on data to make predictions, generative models create new data instances that are similar to the training data. This advanced technology is already being used in a variety of areas, including image and speech generation, text creation and even music composition. In companies, Generative AI has the potential to drive disruptive change by offering new ways to automate and increase efficiency. A well-known example of generative AI applications is ChatGPT, Google Gemini or SwissGPT as used for this article.

Why is Generative AI important for companies?

Generative AI is becoming increasingly important for companies, as it has the ability to automate processes and create new, innovative solutions (such as the GPT chatbot from Jumbo or Helvetia) that were previously not possible. In today’s data-driven world, where companies are constantly looking for ways to work more efficiently and stand out from the competition, Generative AI offers a wealth of opportunities. For example, it can be used to create personalized content for marketing purposes (see LLM-based campaigns), to develop creative designs or to simulate business scenarios. It can also help to save time and resources by automating routine tasks and relieving human workers of repetitive and time-consuming tasks. This enables companies to concentrate on more strategic and value-adding tasks. The importance of generative AI in the corporate world is therefore likely to continue to grow.

What added value does Generative AI bring for companies?

Generative AI offers a wide range of benefits for companies, including increased efficiency, cost savings and improved creativity and innovation.

1. Increasing efficiency: Generative AI can help to automate and accelerate business processes. For example, it can be used to automatically generate reports, analyze data or respond to customer service requests, increasing productivity and saving time. One example of this is Unite’s AI-based customer service.
2. Cost savings: By automating routine tasks, Generative AI can help reduce labor costs. For example, Generative AI used to respond to customer service requests can reduce the need for human customer service representatives and thus save costs.
3. Improving creativity and innovation: Generative AI can be used to develop new and innovative solutions to various business problems. For example, it can be used to create design proposals, which encourages creativity and speeds up the development of new products. The template for the Generative AI Business Case shows an example of this.

A concrete example of the use of Generative AI is the use of GANs (Generative Adversarial Networks) in the fashion industry. Some companies are using this technology to create new fashion designs. The AI analyzes thousands of fashion designs and generates new, unique designs based on this data. This enables companies to quickly and efficiently generate a variety of design options and thus accelerate their product development.

Another example is the use of Generative AI in the marketing industry. Some companies use AI technology to generate personalized marketing content. These can be based on the individual preferences and behavior of customers, which increases the effectiveness of marketing campaigns. You can find an example of this in this blog post about LLM-supported campaigns.

How do companies introduce Generative AI?

Over the last few months, I have had the opportunity to support a number of companies in the planning and introduction of Generative AI applications in their organizations. The participating companies, consultants and technology providers have learned a lot in the process. At the same time, I created a guide to the successful introduction of Generative AI projects in companies.

Typically, a company’s Generative AI journey usually starts with a general“awareness workshop” on the opportunities and risks of Generative AI. A presentation on the topic is also possible. This will be followed by workshops on use cases, data protection and technical possibilities. As soon as the first steps of the implementation have been completed, the test phase begins. During this test phase, further adjustments are made in most projects before the Generative AI solution goes into the productive environment, where it is available to customers and employees.

The entire guide can be downloaded here:

What can I expect in the guide?

The guide is a project plan with all the important work steps and work content for the introduction of Generative AI in the company. The work packages, persons involved and the time required are described in keywords for each work step.

Companies can use this guide to get started directly with Generative AI in their operations.

Who is the guide suitable for?

The guide is primarily aimed at managers and project leaders who want to start a Generative AI project in the company or at least want to evaluate the effort and benefits of such a project.

Further useful tips

Would you like further support with your AI project? Then hopefully these offers are just right for you.

Nothing there?

Then write me a message with your wishes and questions and we will find an offer for you. Just send me a message via WhatsApp or email.

Or come directly to my WhatsApp group – where I regularly post use cases, news, best practices, events and much more about chatbots, ChatGPT and co.