In recent years, the way in which we design digital experiences has undergone a profound transformation. What used to be a combination of aesthetics and usability now also needs to account for something bigger: interpreting data in real time, learning from user behavior, and continuously adapting to new demands.

In this new scenario, the intersection between artificial intelligence and UX is no longer a trending topic. It has become mandatory practice for those who are building relevant digital products.
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Interfaces that learn from the user
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Instead of static and linear flows, we are designing adaptive systems.

Virtual assistants, intelligent search engines, suggestion engines, the challenge now is to combine data, algorithms, and interaction design in a natural way.

When Netflix recommends a movie you wanted to see or Duolingo adapts the learning journey, it's not magic: it's AI well aligned with good UX practices.

Without design, AI can't sustain itself.

Without AI, design doesn't scale.
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Has the role of design changed?

No.

But it became more complex.
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We continue to work with clarity, hierarchy, contrast, rhythm, and intention.

However, now the designer also needs to dialogue with data, understand behavior, orchestrate intelligent flows, and translate predictive models into understandable interactions.

AI doesn't replace design. It broadens the field of design practice.
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Hand in the dough: 4 ways to apply AI to your product's UX today
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1. Content personalization
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Display content, products, or offers based on the behavior and interest of each user.

Tools:
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Segment, Amplitude, Mixpanel (data collection)

Recombee, Algolia Recommend (recommendations)

Firebase Predictions (mobile apps)

2. AI-powered assistants and chatbots
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Guide the user through tasks or questions through intelligent conversations.
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Tools:
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OpenAI GPT-4 API, Anthropic Claude (AI engines)

Rasa (open-source)

Voiceflow (building conversational flows)
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3. Smart product search
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Improve the internal search experience with semantic relevance.
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Tools:
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Algolia

ElasticSearch with embeddings

Pinecone (vector search)
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4. A/B testing and optimization with AI
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Accelerate experimentation and interface optimization.

Tools:
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VWO, Optimizely

Adobe Target
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How Baux can help in practice
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At Baux, AI is not a tool resource.

It is part of the product architecture.
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Our job isn't simply to use AI to generate screens, but to design products that:
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• They combine data and behavior: we structure how the data will be collected, organized, and used within the product.
• They define intelligent flows: we redesign journeys based on business rules, machine learning and real personalization.
• They translate intelligence into clarity: we transform automated decisions into understandable, human, and consistent interfaces.
• They integrate AI without losing control of the business: we create bridges between design, technology and data, so that AI amplifies the product - without generating unnecessary complexity.

Whether in a new product or in the evolution of an existing solution, our role is to ensure that the user perceives the system's intelligence in a natural and fluid way and that the business derives real value from it.
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If you're redesigning a product or want to understand how to apply AI in a practical and useful way to your digital one, it's worth exchanging an idea with us.

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