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Use cases for GenAI in all areas and market roles

Artificial intelligence is advancing inexorably. With Generative Artificial Intelligence (GenAI for short), the topic has reached a new dimension that is bringing about far-reaching changes - including in the energy sector. Tools such as ChatGPT have impressively demonstrated the immense potential of GenAI. However, GenAI can do far more than just generate texts or images. It can also optimise business processes. Those who do without it are consciously accepting competitive disadvantages.

In the energy market, the fields of application extend across all market roles: from energy generation and procurement to the grid and customer service. The focus is always on the benefits, which often manifest themselves in automated processes and an improved customer experience. GenAI is undoubtedly the future - a development that adesso is driving forward with great commitment.

Part 1: Getting started is easy

The rapid spread of GenAI has long since reached the business world. Almost everyone has already come into contact with this technology - be it through chatbots, personalised recommendations or automated processes. The good news is that getting started with GenAI is easier than ever.

Employees are the key to success

In all of the energy companies I was able to talk to about the topic, there are first attempts at using the technology, small pilots and prototypes, as well as employees who have already gained experience with GenAI. They may have developed chatbots themselves, trained machine learning models or carried out data analyses. These internal experts are the key to a successful introduction to the use of GenAI.

Encourage the joy of experimentation

To make it easier to get started, energy companies should promote a culture of experimentation. Employees should be encouraged to experiment with GenAI tools and find new solutions. After all, it is often the small ideas and individual initiatives that lead to big successes.

Part 2: Getting started is simple, but not trivial

The integration of GenAI at energy suppliers and municipal utilities may seem simple at first glance, but the tasks involved should not be underestimated. Energy companies should seek advice in the following areas in particular:

1. Security

GenAI systems must be operated securely. Companies need to implement robust security measures to protect their AI models from unauthorised access, data leaks and malicious attacks. The use of encryption, authentication and access controls is essential.

2. Governance

A clear governance structure is necessary to ensure the responsible use of GenAI. Energy companies should define policies, responsibilities and processes to manage the development, implementation and monitoring of GenAI systems.

3. Data protection

GenAI utilises large amounts of data. Energy companies must ensure that this data can be collected and processed lawfully. Compliance with the General Data Protection Regulation (GDPR) is of central importance and can already be implemented today.

4. Empowerment

As already mentioned, the success of GenAI depends on the expertise of its own employees. Energy companies should continuously train and empower their employees in the use of GenAI technologies. Short one- to two-day workshops are ideal for this, in which the technology is categorised in the overall context and practical exercises are carried out in order to reduce fears of contact.

5 Hallucinations of AI

GenAI systems are not immune to errors. Sometimes they produce misleading or incorrect results - so-called "hallucinations". Energy companies need to be aware of this fact and implement mechanisms to verify and validate their AI models.

Overall, entering the GenAI world opens up many opportunities, but also harbours risks. Energy companies that take these aspects into account and act responsibly will be able to benefit from the advantages of GenAI.

Part 3: Where do we stand today, a brief categorisation

The rapid development of GenAI technologies will open up many new possibilities in the near future. The use cases mentioned are just the beginning. Most of them fall into levels 1 and 2 of the following classification. The good thing is that all the requirements for Level 1 and 2 are met and you can get started right away:

Level 1: Using copilots & GPTs / generating texts

At this entry level, GenAI is mainly used to generate, evaluate or summarise texts. This is often the first step into the world of AI-supported tools, where initial efficiency potential can be realised.

Level 2: Larger use cases with a software engineering component

This level goes beyond simple text generation. GenAI is embedded in larger use cases that require software engineering. Although no business data is yet involved, this level already offers real acceleration.

Level 3: GenAI as a user interface for interacting with business data:

Now it's getting exciting! Imagine that GenAI functions are part of a user interface for interacting with business data. This is where the major providers of standard software come into play: SAP, Salesforce, Microsoft and Co.

One example: In an SAP interface, queries can be formulated in natural language and corresponding reports, analyses and diagrams can be prepared directly. The intelligent and ad-hoc processing of data creates great added value here.

Level 4: GenAI is deeply integrated into existing processes:

At this advanced level, GenAI is deeply integrated into existing processes. Direct user interaction is no longer required. A concrete example: A GenAI-based system automatically restarts a wind turbine after a malfunction. To do this, the system must be trained beforehand, it must understand the turbine and the operating mode, and have read the operating manual and the known error messages. This results in real increases in efficiency and high savings potential.

The future of GenAI is very promising and we can look forward to seeing what further innovations it will bring us!

Part 4: Use cases exist for all areas and market roles

The use of GenAI in the energy industry offers a wide range of benefits and opportunities. It enables a more efficient and effective use of data, improves customer service and optimises decision-making in all market roles.

One example is customer service. Be it automated responses or personalised recommendations: The suggestions are based on sound information from the company systems. The result? Increased efficiency and relief for your customer service team.

GenAI-enhanced virtual assistants take classic chatbots to a new level. They are the perfect companions for your customers. They provide support with enquiries, tariff changes, billing and account management. And the best thing about it? A personalised experience for every user. And while the relevant standard processes are initiated and handled in the background, your employees can concentrate on the essentials.

But that's not all. A corporate GPT is better and faster than the most experienced employee. It answers the most difficult questions, searches thousands of documents, the intranet and SharePoint pages in milliseconds. Searching was yesterday. Finding is today. The time savings are enormous.

GenAI will fundamentally change the way we work. For energy suppliers, municipal utilities and network operators in particular, GenAI opens up a world of opportunities and efficiency gains. Here are a few examples:

  • Personalised learning platforms: GenAI enables the creation of personalised learning content that is tailored to the individual needs of employees. This leads to more effective learning and a better understanding of complex topics, of which there are many in the energy world
  • Let's take a look at the "dear" regulation in the energy industry, which is complicated, extensive and sometimes impenetrable. Many energy suppliers have a large number of people who deal with these issues on a daily basis. With GenAI, they can automatically extract the most important information from the latest publications on market communication, changes to file formats (UTILMD and MSCONS send their regards) and many other documents, contracts and publications. This saves valuable time and minimises human error.
  • Last but not least, let's take a look at sales and marketing: GenAI can work wonders here. Automatically creating advertising texts, text to video, slogans, image material and even pre-structuring entire marketing campaigns - the possibilities are enormous! What has long been used productively in other sectors is still a dream of the future for the energy industry. Energy suppliers can advertise their products and services more effectively and increase their reach. This is becoming an important success factor in the highly competitive commodity and EDL business.


The integration of GenAI into the world of energy suppliers and grid operators is a topic that triggers both enthusiasm and scepticism among companies. But the sceptics are becoming fewer and fewer. The question of whether the technology makes sense has been answered: yes, definitely. The question of application scenarios has also been clearly answered and new ideas are being added every day. I can also clearly answer the question of "When to start?": Now is the right time. The technology works, adesso offers a procedure and a framework for the introduction. As a simple introduction, we offer the GenAI Quick Check, which energy companies can use to quickly determine their own GenAI level. It is up to the players in the industry to seize this opportunity and further digitalise the future of energy supply.

You can find more exciting topics from the world of adesso in our previous blog posts.


Would you like to find out more about GenAI and how we can support you? Then take a look at our website. Podcasts, blog posts, events, studies and much more - we offer you a compact overview of all topics relating to GenAI.

Learn more about GenAI on our website

Picture Jonas Vöhringer

Author Jonas Vöhringer

Jonas Vöhringer is Senior Account Manager in the Utilities business line at adesso. As an experienced Senior Account Manager in the energy sector, he combines his passion for digital innovations with the specific requirements of the energy industry. His focus is on shaping the digital energy transition and translating current trend and technology topics into practical solutions.

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