IT Knowledge in a Nutshell
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While the EU aims to ensure safety and transparency for its citizens through the AI Act, companies are increasingly uncertain about the legal obligations the AI Act imposes on them. One thing is certain: AI has long since become part of everyday business life. We’ll explain how you can use AI in your company in a legally compliant manner, in accordance with the EU AI Act!
An employee asks the internal AI assistant about the current vacation policy. The answer sounds convincing—but it’s still wrong. The language model isn’t familiar with the actual company policy; instead, it generates a plausible-sounding response based on its training data. You may be familiar with this exact problem from your own experience.
AI governance establishes a binding framework for the secure, transparent, and legally compliant use of artificial intelligence. It integrates corporate governance, risk management, data protection, IT security, and technical development. As a result, governance becomes a central component of any viable AI strategy.
Within just a few minutes, the balance between generation and consumption shifts—and the power grid comes under strain. For many energy providers, scenes like these have long been part of everyday life. But what does this mean, specifically, for managing an increasingly complex energy system? This is exactly where artificial intelligence comes in.
Companies are constantly storing vast amounts of data. Sensors, ERP systems, CRM solutions, cloud applications, and IoT devices deliver new information every second. Real value is only created when this data is accurately consolidated, processed, and made available for later analysis.
The open standard makes it possible to connect AI applications to enterprise systems, data sources, APIs, and external tools in a standardized way. This gives language models access to up-to-date information and enables them not only to retrieve data but also to perform actions in various applications.
Just a few years ago, the path to information almost always went through traditional search engines like Google. Users would enter a search term, click on various websites, and compare the information provided there on their own. This search behavior is currently undergoing a fundamental change...
Security in software development is not an optional feature - it is a basic requirement. Nevertheless, practice shows time and again that security vulnerabilities are often only discovered late in the development process or even during operation, which is precisely where Static Application Security Testing - SAST for short - comes in.
In this article, you will find out in which areas AI is already being used in HR today, what advantages it offers and what challenges you should consider when introducing it. We also use specific examples to show how companies are successfully using AI in HR.
In this article, you will find out what AI means in the office, what advantages it offers and in which areas it can already be used today. We also show you what you should look out for when using AI and how you can get started working with AI-supported tools step by step.
Agentic AI is considered to be one of the most important developments in the field of artificial intelligence to date. Unlike traditional AI systems, which primarily respond to individual requests, agentic AI systems can plan tasks independently, make decisions and execute processes automatically.
Do you want to know whether Scrum or Kanban is the right choice for you? Both agile methods are among the best-known project management methods - and both can help you to deal with complex requirements more clearly.
For a long time, medical image data was regarded as a reliable "source of truth". X-rays, MRIs and CT scans provided seemingly unambiguous evidence for diagnoses and formed the basis for benefit decisions in the insurance industry. However, this status is increasingly being shaken.
When you run AI locally, models and applications run directly on your own infrastructure - be it on a server in the company or even on powerful hardware at your workplace. This not only gives you more control over your data, but also over costs, performance and individual customizations.
Applications such as ChatGPT, Gemini or other AI-supported systems deliver texts, evaluations, concepts or code within a few seconds. But in practice, it quickly becomes clear that the quality of the results is no coincidence. It largely depends on how precise and structured you formulate your query.
Artificial intelligence has long since arrived in everyday business life. Whether automated processes, intelligent analyses or generative AI - the potential applications are growing rapidly. At the same time, however, the requirements for data protection, transparency and legal security are also increasing. This is precisely where the topic of AI compliance comes into play.
Artificial intelligence is changing the way companies work. AI systems support the analysis of large amounts of data, automate recurring tasks and enable new digital business models. However, the use of AI not only brings efficiency gains, but also new security-related challenges.
Have you ever wondered why smartphones now recognize faces, why cars can drive themselves or why chatbots seem more and more natural? Behind many of these small technical wonders is deep learning - a kind of "brain" for modern AI systems.