Human-Centered AI
UX strategy, UX design and user research for digital solutions with integrated AI.
Artificial intelligence is fundamentally changing human-machine interaction. AI is now a feature or integral component of many digital applications – for example, for support, automation, or decision-making. This creates new requirements for usability and user experience. Human-centered AI describes the consistent user-centered design and evaluation of digital applications in which AI plays a role. Human-centered AI complements proven UX principles wherever AI influences the behavior of digital systems and interactions become less predictable.
UX Design for Applications With Generative AI
The integration of generative artificial intelligence into digital products presents companies with new challenges. Proven principles such as understanding contexts of use, involving users, and iterative design and evaluation remain relevant.
At the same time, AI components are changing the behavior of digital applications. System responses and processes are no longer completely predictable. UX design takes these changes into account when designing digital solutions with AI components.
Human-centered AI builds on human-centered design and extends it where system behavior is no longer clearly predictable.
UX Design for Applications With Generative AI
Currently, companies are integrating AI features into their products without having a clear idea of how they can be used effectively. User research helps to identify relevant use cases – ones that are not only technically possible but also offer real added value from the user's perspective.
Human-centered design follows an iterative process: concepts are tested, refined, and optimized until a user-friendly product is created. This process remains fundamental even for applications with AI components.
However, since generative AI does not provide uniform answers but generates dynamic content, new questions arise:
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How can user experience be measured when interactions are changing?
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How can it be ensured that AI delivers trustworthy and user-friendly results?
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When is the right time to incorporate user feedback?
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Which AI use cases offer real added value from the user's perspective?
Identification of Relevant Use Cases
The proven UX toolkit is ideal for identifying useful AI use cases. Co-creation and stakeholder workshops help to align technological possibilities with real user needs. This allows use cases to be evaluated, prioritized, and further developed at an early stage – before extensive development costs arise.
Why Does User Experience Determine the Success of Applications With AI?
While traditional software reacts predictably, AI-based functions behave depending on the situation and generate different results.
For users, this means that results must be interpreted, uncertainties must be understandable, and errors must not lead to a lack of trust. The success of digital applications with AI components therefore depends largely on the user experience.
Typical Questions When Integrating AI Into Digital Projects
- Where does AI create real added value from the user's perspective?
- How can we meaningfully integrate AI into existing applications?
- How do we explain AI results in an understandable way?
- How do we test AI functions that are changing?
- How do we ensure acceptance and trust?
These questions cannot be answered purely from a technological perspective, but require a consistently user-centered approach.
Case Study Intelligent Assistance System
Artificial Intelligence (AI) and smart algorithms enable a completely new approach to information in the diagnostic workflow of radiologists. The goal of this multi-year project was to develop an intelligent software assistant that truly facilitates the work.
View Case StudyOur Services for User-Centered AI Applications
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UX strategy and UX management for applications with AI
Strategic embedding of AI features in products, portfolios, and organizations.
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UX design for AI-powered interactions
Designing understandable, controllable, and usable AI features.
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User research and testing for applications with AI
Evaluation of acceptance, trust, and quality of results in dynamic systems.
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Support for sensitive and regulated AI integration
e.g., in the medical field and other safety-critical contexts.
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Structuring work formats (workshops)
For clarification, prioritization, and decision support within larger projects.
Human-centered AI complements UX design, UX management, user research, testing, and medical UX wherever AI changes human-machine interaction.
The success of digital applications with AI components depends on the user experience. We help make these applications understandable, usable, and trustworthy – throughout the entire UX process, from classification and conception to design and evaluation in realistic context of use.
Structured workshop formats help clarify complex questions and ensure reliable decisions. They are embedded in larger UX design, UX management, and research projects.
