“Design used to be the seasoning you’d sprinkle on for taste. Now it’s the flour you need at the start of the recipe.’’

— John Maeda, Designer and Technologist
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Privacy Policy

This Privacy policy was published on March 1st, 2020.

GDPR compliance

At UX GIRL we are committed to protect and respect your privacy in compliance with EU - General Data Protection Regulation (GDPR) 2016/679, dated April 27th, 2016. This privacy statement explains when and why we collect personal information, how we use it, the conditions under which we may disclose it to others and how we keep it secure. This Privacy Policy applies to the use of our services, products and our sales, but also marketing and client contract fulfilment activities. It also applies to individuals seeking a job at UX GIRL.

About UX GIRL

UX GIRL is a design studio firm that specialises in research, strategy and design and offers clients software design services. Our company is headquartered in Warsaw, Poland and you can get in touch with us by writing to hello@uxgirl.com.

When we collect personal data about you
  • When you interact with us in person – through correspondence, by phone, by social media, or through our uxgirl.com (“Site”).
  • When we get personal information from other legitimate sources, such as third-party data aggregators, UX GIRL marketing partners, public sources or social networks. We only use this data if you have given your consent to them to share your personal data with others.
  • We may collect personal data if it is considered to be of legitimate interest and if this interest is not overridden by your privacy interests. We make sure an assessment is made, with an established mutual interest between you and UX GIRL.
  • When you are using our products.
Why we collect and use personal data

We collect and use personal data mainly to perform direct sales, direct marketing, and customer service. We also collect data about partners and persons seeking a job or working in our company. We may use your information for the following purposes:

  • Send you marketing communications which you have requested. These may include information about our services, products, events, activities, and promotions of our partners. This communication is subscription based and requires your consent.
  • Send you information about the services and products that you have purchased from us.
  • Perform direct sales activities in cases where legitimate and mutual interest is established.
  • Provide you content and venue details on a webinar or event you signed up for.
  • Reply to a ‘Contact me’ or other web forms you have completed on our Site (e.g., to download an ebook).
  • Follow up on incoming requests (client support, emails, chats, or phone calls).
  • Perform contractual obligations such as invoices, reminders, and similar. The contract may be with UX GIRL directly or with a UX GIRL partner.
  • Notify you of any disruptions to our services.
  • Contact you to conduct surveys about your opinion on our services and products.
  • When we do a business deal or negotiate a business deal, involving sale or transfer of all or a part of our business or assets. These deals can include any merger, financing, acquisition, or bankruptcy transaction or proceeding.
  • Process a job application.
  • To comply with laws.
  • To respond to lawful requests and legal process.
  • To protect the rights and property of UX GIRL, our agents, customers, and others. Includes enforcing our agreements, policies, and terms of use.
  • In an emergency. Includes protecting the safety of our employees, our customers, or any person.
Type of personal data collected

We collect your email, full name and company’s name, but in addition, we can also collect phone numbers. We may also collect feedback, comments and questions received from you in service-related communication and activities, such as meetings, phone calls, chats, documents, and emails.

If you apply for a job at UX GIRL, we collect the data you provide during the application process. UX GIRL does not collect or process any particular categories of personal data, such as unique public identifiers or sensitive personal data.

Information we collect automatically

We automatically log information about you and your computer. For example, when visiting uxgirl.com, we log ‎your computer operating system type,‎ browser type,‎ browser language,‎ pages you viewed,‎ how long you spent on a page,‎ access times,‎ internet protocol (IP) address and information about your actions on our Site.

The use of cookies and web beacons

We may log information using "cookies." Cookies are small data files stored on your hard drive by a website. Cookies help us make our Site and your visit better.

We may log information using digital images called web beacons on our Site or in our emails.

This information is used to make our Site work more efficiently, as well as to provide business and marketing information to the owners of the Site, and to gather such personal data as browser type and operating system, referring page, path through site, domain of ISP, etc. for the purposes of understanding how visitors use our Site. Cookies and similar technologies help us tailor our Site to your personal needs, as well as to detect and prevent security threats and abuse. If used alone, cookies and web beacons do not personally identify you.

How long we keep your data

We store personal data for as long as we find it necessary to fulfil the purpose for which the personal data was collected, while also considering our need to answer your queries or resolve possible problems. This helps us to comply with legal requirements under applicable laws, to attend to any legal claims/complaints, and for safeguarding purposes.

This means that we may retain your personal data for a reasonable period after your last interaction with us. When the personal data that we have collected is no longer required, we will delete it securely. We may process data for statistical purposes, but in such cases, data will be anonymised.

Your rights to your personal data

You have the following rights concerning your personal data:

  • The right to request a copy of your personal data that UX GIRL holds about you.
  • The right to request that UX GIRL correct your personal data if inaccurate or out of date.
  • The right to request that your personal data is deleted when it is no longer necessary for UX GIRL to retain such data.
  • The right to withdraw any consent to personal data processing at any time. For example, your consent to receive digital marketing messages. If you want to withdraw your consent for digital marketing messages, please make use of the link to manage your subscriptions included in our communication.
  • The right to request that UX GIRL provides you with your personal data.
  • The right to request a restriction on further data processing, in case there is a dispute about the accuracy or processing of your personal data.
  • The right to object to the processing of personal data, in case data processing has been based on legitimate interest and/or direct marketing.

Any query about your privacy rights should be sent to hello@uxgirl.com.

Hotjar’s privacy policy

We use Hotjar in order to better understand our users’ needs and to optimize this service and experience. Hotjar is a technology service that helps us better understand our users experience (e.g. how much time they spend on which pages, which links they choose to click, what users do and don’t like, etc.) and this enables us to build and maintain our service with user feedback. Hotjar uses cookies and other technologies to collect data on our users’ behavior and their devices (in particular device's IP address (captured and stored only in anonymized form), device screen size, device type (unique device identifiers), browser information, geographic location (country only), preferred language used to display our website). Hotjar stores this information in a pseudonymized user profile. Neither Hotjar nor we will ever use this information to identify individual users or to match it with further data on an individual user. For further details, please see Hotjar’s privacy policy by clicking on this link.

You can opt-out to the creation of a user profile, Hotjar’s storing of data about your usage of our site and Hotjar’s use of tracking cookies on other websites by following this opt-out link.

Sharethis’s privacy policy

We use Sharethis to enable our users to share our content on social media. Sharethis lets us collects information about the number of shares of our posts. For further details, please see Sharethis’s privacy policy by clicking on this link.

You can opt-out of Sharethis collecting data about you by following this opt-out link.

Changes to this Privacy Policy

UX GIRL reserves the right to amend this privacy policy at any time. The latest version will always be found on our Site. We encourage you to check this page occasionally to ensure that you are happy with any changes.

If we make changes that significantly alter our privacy practices, we will notify you by email or post a notice on our Site before the change takes effect.

A minimalist graphic defining Artificial Intelligence (AI). The text reads: 'THE SCIENCE OF CREATING INTELLIGENT MACHINES THAT CAN [MIMIC] HUMAN [PERFORMANCE AND] NATURALLY ACQUIRED CAPABILITIES.' Below the text is a small, centered, greyscale photo of a white robotic hand, and the caption 'Artificial Intelligence'

Innovation

AI Demystified: Breaking Down the Basics

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WSTAW
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Welcome to the era of Artificial Intelligence, a revolutionary field that is reshaping the world as we know it. AI, once relegated to the realm of science fiction, has now become an integral part of our daily lives, impacting everything from our smartphones to the way we interact with businesses. In this article, we will explore the fundamental concepts of AI, its immense potential, and the exciting opportunities it offers, while also considering its challenges and possible threats.

What is AI?

Artificial Intelligence, or AI, is the science of creating intelligent machines that can mimic human intelligence and perform tasks that typically require human cognitive abilities. These tasks encompass a wide range of activities, from understanding natural language, decision-making, and problem-solving to recognizing patterns in data, and even driving autonomous vehicles. AI systems are designed to learn, reason, and adapt based on the data they receive, allowing them to make predictions and take actions. Thus based on vast amounts of information, algorithms adapt their behavior accordingly, making AI systems invaluable tools for numerous industries.

We can distinguish many different branches in the AI industry, among which the most popular currently include:

Natural Language Processing (NLP): NLP focuses on enabling machines to understand, interpret, and generate human language. It powers applications like chatbots, language translation, sentiment analysis, and text summarization. Advanced language models, such as GPT-4, have made significant strides in this field, allowing for more sophisticated language understanding and generation.

Computer Vision: Computer vision involves teaching machines to interpret and understand visual information from images and videos. It finds applications in facial recognition, object detection, autonomous vehicles, medical imaging, and augmented reality. Deep learning techniques like Convolutional Neural Networks (CNNs) have been crucial in advancing computer vision capabilities.

Machine Learning: Machine learning is a broader field that encompasses algorithms and techniques enabling systems to learn and improve from data without explicit programming. Supervised learning, unsupervised learning, and reinforcement learning are common paradigms within machine learning. It is the backbone of many AI applications, including recommendation systems, fraud detection, and predictive analytics.

Deep Learning: Deep learning is a subset of machine learning that uses artificial neural networks to model and solve complex problems. It excels in handling large amounts of data and is responsible for significant breakthroughs in image and speech recognition, natural language processing, and game playing (e.g., AlphaGo).

Reinforcement Learning: Reinforcement learning is a subset of machine learning that focuses on training agents to make decisions in an environment to achieve specific goals. It is instrumental in developing AI systems capable of playing games, optimizing processes, and controlling robots.

Robotics and Automation: AI-driven robots are becoming more prevalent across various industries, from manufacturing and logistics to healthcare and household assistance. These robots use AI algorithms to perceive their environment, plan actions, and perform tasks autonomously.

Generative Models: Generative models, particularly Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), can create new content based on existing data. They have been used for image synthesis, video generation, and even creating realistic AI-generated artwork and music. In recent weeks, popular tools like Midjourney, Photoshop, and Framer AI have been leveraging generative AI to provide their users with features that were once considered abstract just a few months ago. Currently, these are among the fastest-growing algorithms in the industry.

Why should you be interested in AI and start learning it?

The relevance of AI has never been more apparent than in today's fast-paced world. By understanding AI, we unlock the potential to develop cutting-edge solutions to complex problems, leading to technological advancements that can improve our quality of life. As AI permeates various industries, learning about it becomes a strategic advantage for individuals and businesses alike. The recent months have, in many cases, exceeded our expectations. People have seen that the potential of AI tools can be accessible to everyone, and the content being generated is already so realistic and complex that it can mimic (and in many cases, even enhance) human creativity. 

Given how AI is growing quickly and finding new uses, it's clear that AI skills are in high demand today. The increasing number of job opportunities in fields such as data science, robotics, and AI research and more and more interest in AI tools by most of the big companies and start-ups should be the best proof.

Those who are willing to learn, collaborate with AI, and embrace the AI revolution with an open mind will emerge victorious. Those who neglect these opportunities will inevitably fall behind.

The Benefits of AI

The benefits of AI are immense and wide-ranging, promising a transformative impact on society. One of the most significant advantages is enhanced efficiency and productivity. AI-powered systems can handle repetitive tasks at an unprecedented speed and accuracy, liberating human resources for more creative and strategic endeavors.

Additionally, AI has revolutionized various sectors, such as healthcare. With AI-driven diagnostics and personalized treatment plans, medical professionals can make more accurate and timely decisions, potentially saving countless lives. In agriculture, AI helps optimize crop yields and monitor livestock health, contributing to sustainable and efficient food production.

Moreover, AI has vastly improved user experiences across various industries. Virtual assistants like Siri and Alexa have become our helpful companions, providing us with useful information and managing our daily tasks. AI-driven recommendation systems in online shopping platforms, music streaming services, and video content providers cater to our preferences, making our lives more convenient and enjoyable.

Both companies and individuals are now using AI-based tools in their daily lives. From well-known ones like ChatGPT and MidJourney to tools such as Copilot, Jasper, copy.ai, Adobe Firefly, and a variety of specialized plugins and enhancements that enable more effective business management, time management, social media content creation, and much more.

The Threats of AI

While AI presents numerous benefits, we must also be mindful of the potential risks and challenges it brings. One of the most significant concerns is job displacement. As AI automates tasks previously performed by humans, certain jobs might become obsolete, leading to job insecurity for certain professions. However, it is essential to remember that AI also creates new job opportunities in related fields, requiring a skilled workforce to develop and manage AI systems.

Another critical aspect to address is AI ethics. As AI systems become increasingly sophisticated, they may face ethical dilemmas, especially in areas like autonomous vehicles and healthcare. Striking the right balance between AI autonomy and human control is crucial to ensure safety and accountability. 

Furthermore, there are concerns about data privacy and security. AI systems rely heavily on data for training and decision-making, raising the risk of potential data breaches or misuse. It is essential to develop robust data protection mechanisms and ensure responsible AI usage to safeguard individual privacy and prevent unauthorized access.

We must also remember that many publicly available AI tools still face several limitations, such as social biases, hallucinations, and adversarial prompts. It's important to be aware that not everything provided by, for instance, ChatGPT, should be taken as absolute truth. However, companies are continually working to improve and fine-tune their models. The latest language model from OpenAI, known as GPT-4, is claimed to be 82% less likely to respond to requests for prohibited content and 40% more likely to provide fact-based answers compared to GPT-3.5.

Nevertheless, it's essential to remember that these are merely tools in our hands. How we use them still depends entirely on us. Staying informed and aware is valuable, as the revolution doesn't happen overnight; it's a lengthy and error-prone process.

Let's take a moment to dive a little deeper and examine three concepts without which our current AI conversation would be meaningless…

Machine Learning: The Core of AI

At the heart of AI lies Machine Learning (ML), a subset of AI that empowers machines to learn from data without explicit programming. ML algorithms use statistical techniques to identify patterns in data, enabling them to make predictions or decisions based on new information. This ability to learn and improve with experience is what sets ML apart and makes it a powerful tool in various applications.

Prompt Engineering: Igniting Creativity in AI

Prompt engineering is a fascinating aspect of AI that involves crafting effective instructions or queries to direct AI models' output. By providing appropriate prompts, developers can influence the content, style, or tone of AI-generated outputs. This technique has been particularly instrumental in the development of Generative AI.

Generative AI: Fostering Creativity

Generative AI is a branch of AI that deals with machines' capability to create new content, such as images, music, text, and more.

In simpler terms, Generative AI is precisely the branch that has recently gained immense popularity thanks to tools like ChatGPT, MidJourney, DALL-E, or Jasper. As the name suggests, it's generative, meaning it can generate (or just create) new content based on specific queries, known as prompts.

But how is this even possible? In a nutshell, by learning patterns from a vast amount of data (such as existing articles, research papers, images, and more), the algorithm creates new content based on these patterns. Importantly, even though we "feed" the algorithm with certain content (pre-trained data sets), it doesn't mean we'll get copies or similar replicas of the input. The algorithm, using learned transformations, can iteratively generate genuinely new things. It's all powered by deep neural networks, but the exact workings and why the algorithm produces a specific response are not obvious, even to the creators of these neural networks. You input the data, and run the algorithm, but what happens inside the network remains a puzzle.

ChatGPT - What's All the Buzz About?

Imagine having a super-smart assistant, like a virtual wordsmith, at your fingertips, ready to help you create captivating content and answer your queries. That's precisely what ChatGPT is!

ChatGPT, developed by the American company OpenAI, is a content generator that relies on a large language model called GPT (currently in version 3.5 or, paid GPT-4). It's a bot with which you can communicate using natural language. This tool over 50 different languages, capable of answering questions, translating documents into various languages, conducting proofreading and language editing of texts, summarizing and analyzing scientific papers, suggesting solutions to diverse problems, crafting essays, scripts, debugging programming code, and searching through databases. In the paid version of the tool, you even have the ability to work with images, allowing you to upload an image as input and, for example, expect its analysis.

What's crucial is that the paid version of ChatGPT (GPT-4) now has (or, compared to the competition, is just getting) internet access. This means it can now browse the internet to provide you with current and authoritative information, complete with direct links to sources. It's no longer confined to data from before September 2021. Additionally, we can utilize various plugins and integrations, such as speech recognition (Whisper) and complex data calculations and analysis (Wolfram Alpha), making the tool even more powerful. Currently, there are over 900 plugins available!

Recently, ChatGPT also received an update that enables the ability to converse with the chatbot using voice commands. ChatGPT, GPT-3.5, and GPT-4 will be able to comprehend user questions and respond using one of five distinct voices.

Now, you might wonder why you should use ChatGPT. The answer is simple: it saves you time and boosts your productivity. Writing high-quality content can be time-consuming, and not everyone has the expertise to craft captivating texts. ChatGPT eliminates that hurdle, offering instant assistance whenever you need it. Furthermore, it helps overcome writer's block, as it can spark new ideas and inspire creativity. 

In short, ChatGPT can help us with a range of tasks, including:

  • Brainstorming
  • Exploring various options for what we want to do
  • Providing suggestions regarding different approaches, for example, how to do something on iOS or Android
  • Fueling creativity: X ideas for headlines, X ideas for navigation in the design industry, and so on…
  • Writing meeting summaries
  • Preparing transcriptions
  • Making analyses
  • Sprint management
  • Customer service
  • Delivering corporate wiki - uploading documentation to the AI model and using queries to direct to specific places, like where the button component is located
  • And much more!

Here are a few tips on how to effectively "converse" with Chat GPT (or any similar tool) to get the best possible responses:

  • Write simple and uncomplicated sentences
  • Break down sentences into shorter and more precise ones
  • Describe the context of your problem in detail
  • Start with the general idea and ask follow-up questions to refine your queries based on the response you receive
  • Speak as if you were talking to a 5-year-old

What is a noteworthy alternative to Chat GPT?

As you might imagine, the competition is not resting, and the market is flooded with a multitude of tools that utilize GPT models and more.

Currently, the two most popular tools, operating similarly to ChatGPT, are:

  • Bing - Microsoft's chatbot that uses the same GPT model as ChatGPT, but integrates it with the Bing search engine. This means that it can access the internet by default and provide you with relevant information, sources, and suggestions. You can also change the tone of the chatbot to be more creative, more precise, or balanced;
  • Bard - Google's chatbot that uses a combination of two language models: LaMDA and PaLM. LaMDA is designed for dialogue applications and PaLM is good at math and logic. Google Bard can also access the internet by default and display photos in the results. You can also export the results to Gmail or Google Docs, or modify them without typing. Google Bard is free and available for anyone to use.

The best chatbot for you depends on your needs and preferences. You might want to try them all and see which one suits you better. They are all amazing examples of how AI can help us communicate, create, and learn.

Two professionals working late in a modern tech office, focusing on UX design and coding. One is creating interface layouts on a screen, while the other uses AI-assisted development tools. The workspace is illuminated with soft purple and blue lighting, creating a focused and creative atmosphere.
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Design for Vibe Coding: Why Good UX Is Now the Fastest Way to Build

Software development is entering a new era. Writing code line by line? That’s old school. Today, you vibe code - flowing quickly with AI-assisted tools, generating features in minutes, and iterating with lightning speed.

But here’s the catch: without good design, vibe coding falls apart. No matter how fast you code, if your UX and UI aren’t rock-solid, your product will hit friction fast.

That’s why we at UX GIRL created our new service: Design for Vibe Coding. Because now that AI can write your code, great design is your real competitive edge.

Vibe Coding Isn’t Just Fast Code - It’s a New Way to Build

Vibe coding is the rising mindset in modern product teams - a way of working that’s fast, fluid, and creative. It's enabled by AI tools like GitHub Copilot, Replit Ghostwriter, and Codeium, which make coding feel more like jamming than engineering.

But here's the truth: AI can help you write code, but it can’t fix a broken UX. Without the right flows, component structure, and interaction logic, your fast code becomes messy code - and the vibe is gone.

Design Is Now the Foundation of Speed

According to McKinsey, companies that prioritize design outperform their competitors by up to 32% in revenue and 56% in total returns to shareholders . Forrester also reports that every $1 invested in UX brings up to $100 ROI.

In other words: code is cheap, but design drives results.

When your product is built on solid UX and clean UI, vibe coding becomes a superpower. You eliminate friction, cut dev time, and accelerate iteration - all without losing clarity.

How UX GIRL Designs for the Vibe

At UX GIRL, we design products that are dev-ready from day one. We don’t just deliver pretty interfaces - we deliver structured UX logic, scalable UI systems, and ready-to-deploy design blueprints that flow with your dev process.

Our process starts with UX workshops and research. We define user goals, create flows, build wireframes, and then bring it all to life in pixel-perfect UI. But here’s what makes us different: we design with vibe coding in mind.

That means:

  • Components are modular.
  • Layouts are logical.
  • Interactions are intuitive.
  • Everything is built to accelerate fast development and AI-assisted workflows.

Design for Vibe Coding is perfect for startup teams, AI-powered dev teams, no-code/low-code builders, and fast-scaling CTOs who need to ship fast - without sacrificing quality.

From Strong UX to Beautiful UI - in Record Time

Your MVP doesn’t start with code. It starts with clarity. A strong UX foundation and ready-to-use UI allows you to build smarter, faster, and better - whether you’re working with a team of devs or solo coding with AI.

With UX GIRL, our clients go from concept to implementation in weeks - not months. Our design packs are crafted to minimize development delays, boost usability, and drive adoption from day one.

Ready to Vibe Code?

If you’re building a product fast - and want it to work beautifully - start with a design that fuels your flow. With Design for Vibe Coding by UX GIRL, you’ll go from idea to live product faster than ever.

👉 Let’s design your next product the vibe way. Contact UX GIRL today.

Magdalena Ostoja-Chyżyńska, Founder & CEO of UX GIRL, standing in front of a white background with the Data Science Summit logo in the top left corner.
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5 min

How AI and Enhanced Data Access Are Transforming Today’s Design: UX GIRL at Data Science Summit

Artificial intelligence is no longer a distant promise for design teams-it is already reshaping how designers think, collaborate, and create. This shift was the focus of a talk delivered by Magdalena Ostoja‑Chyżyńska, CEO & Founder of UX GIRL, during Data Science Summit, one of the key events bringing together experts from data, technology, and digital innovation.

In her presentation, “How AI and Enhanced Data Access are Transforming Today’s Design,” Magdalena explored how artificial intelligence is influencing modern design practice-not as a replacement for human creativity, but as a force that is redefining how design teams work with data, insights, and complex business requirements

Two women standing at a conference venue in front of large illuminated ‘#DTS’ letters in green and purple lighting, wearing event badges and smiling at the camera

Design at the Intersection of AI and Data

The talk addressed a challenge many organizations currently face: how to integrate AI into design processes without reducing originality or oversimplifying complex user problems. As Magdalena explained, the growing accessibility of data and AI models has fundamentally changed how designers approach tasks such as briefing, user research, insight synthesis, requirements definition, and asset creation.

Rather than treating AI as a purely visual or generative tool, the presentation positioned it as a broader design accelerator-one that influences decision-making long before the first interface is drawn.

Insights from Real Client Projects

A key strength of the session was its grounding in real business practice. Drawing from ongoing client work at UX GIRL, Magdalena shared observations from testing different AI tools and models across multiple stages of the design process. These experiments focused on understanding where AI genuinely supports creative and analytical work, and where its limitations become visible in real-world conditions.

During the talk, she referenced commonly used tools such as Midjourney, ChatGPT, Claude, and Recraft, explaining how they were evaluated not in isolation, but in combination with different types of data and project constraints. The emphasis was not on novelty, but on effectiveness-how these tools behave when confronted with incomplete data, ambiguous requirements, or complex stakeholder expectations.

Creativity, Control, and the Role of Data

One of the central themes of the presentation was the relationship between AI output and data quality. Magdalena highlighted that AI-driven design outcomes are only as strong as the data and context provided to the models. Enhanced access to data can dramatically improve speed and clarity, but it also increases the responsibility of design teams to curate, interpret, and challenge that data rather than accept AI-generated results at face value.

The session made it clear that AI does not remove the need for designers’ judgment. On the contrary, it amplifies the importance of critical thinking, domain knowledge, and ethical responsibility in design decisions.

Why This Talk Resonated at Data Science Summit

Presenting this topic at a data-focused conference was intentional. The session connected two worlds that often operate separately: design and data science. By showing how AI is already embedded in everyday design workflows, Magdalena demonstrated that design maturity today increasingly depends on data literacy and cross‑disciplinary collaboration.

For many attendees, the talk offered a rare perspective-AI discussed not from a purely technical standpoint, but through the lens of practical design leadership and real client constraints.

Looking Ahead

The presentation reinforced UX GIRL’s position at the intersection of design, data, and emerging technology. Rather than following trends, the studio actively tests and evaluates new tools in live projects, translating experimentation into informed design decisions.

As AI continues to evolve, the questions raised during this session remain highly relevant: how to preserve originality, how to use data responsibly, and how to ensure that technology strengthens-not flattens-the impact of design.

For those interested in how AI is shaping the future of design beyond surface-level automation, the work and insights shared by UX GIRL offer a grounded and experience-driven perspective.

A diverse UX team analyzing real user data in an office setting—heatmaps, feedback transcripts, and analytics on a shared screen, highlighting collaboration and insight.
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5 min

AI Shifts Us From Monitoring Numbers to Understanding Situations

For years, product teams have relied on metrics: KPIs, dashboards, charts. We’ve tracked conversion rates, NPS scores, session times, and click-throughs. But in today’s complex digital landscape-filled with nuanced user journeys and multi-touch interactions-numbers alone no longer tell the full story.

Artificial Intelligence is changing that. It’s not just processing data-it’s interpreting it. The shift is no longer from data to insights, but from measurements to meaning. AI enables us to move from simply monitoring activity to understanding the real-life situations behind the data.

The Problem: More Data, Less Clarity

Imagine a product team managing a mobile app. They notice a drop in daily active users. The dashboard makes the trend obvious—but not the cause.

Why are users dropping off? Is it a bug? New onboarding? Competitive noise?

This is the daily frustration for many teams. Analytics dashboards present signals, not narratives. Numbers show what is happening, but not why. As a result, decisions are often based on instinct instead of evidence.

The Power of Situational Awareness

Modern AI-powered by large language models and predictive algorithms-offers something beyond quantitative metrics. It enables situational awareness.

For example, instead of just reporting that “users bounce after visiting the product page,” AI might analyze multiple sources and suggest:
“Users are dropping off because the availability details are hidden behind a tab, causing friction in their decision-making.”

This is a leap-from interpreting events in isolation to connecting user behavior, interface patterns, and emotional friction.

AI can combine:

  • Support chat transcripts,
  • Voice-of-customer feedback,
  • Heatmaps and session recordings,
  • Usability testing outcomes,
  • Analytics patterns filtered by device, region, or time.

Together, these inputs form a rich narrative that answers:
What’s happening? Why is it happening? What should we do about it?

Redefining the Role of Product Teams

When AI handles the heavy lifting of data interpretation, product teams are free to do what they do best: make decisions, explore hypotheses, and run experiments.

AI doesn’t replace human intuition-it enhances it. Instead of endless reports, teams can respond to actionable, situation-based insights.

The Product Owner no longer has to guess why a user churned.
The UX researcher no longer has to manually synthesize 50+ interview transcripts.
The designer no longer operates in the dark.

With AI, the team sees the whole picture-faster.

But First, a Few Guardrails

AI-driven UX analysis is powerful-but not foolproof. To use it responsibly:

  1. Garbage in, garbage out. If your data is biased, incomplete, or misleading, your insights will be too.
  2. Context still matters. AI models lack cultural, emotional, and strategic context. Teams must interpret outputs critically.
  3. Transparency is key. Your team should know what data the AI is using and how it arrives at its recommendations.

How to Start Shifting From Metrics to Meaning

AI is not the future—-it’s the now. Here’s how to start the shift today:

  • Start with one source of qualitative data (like support tickets or survey responses) and use AI to identify common patterns or friction points.
  • Review AI-generated insights in weekly UX or product rituals to discuss, challenge, and prioritize actions.
  • Compare AI interpretation with your existing KPIs to create a more complete, situational view of your users.
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