Artificial intelligence (AI) is reshaping the very fabric of human interactions with digital products. With a skyrocketing AI software market, everyone — be it a CEO, a product owner, or a junior designer — needs to get on board with using AI in UX.
So how about we dive into the AI principles in UX design together? You will learn more about key AI advancements, their impact on UX, and the power they hold to push digital products further. All of it is served with real-world examples — both as implemented AI in a final product and as AI tools used to speed up the design process.
This guide is a summary of Cieden’s observations of AI technology in the past years. Not only have we observed; we’ve actively used our knowledge to implement AI in design.
Now grab your coffee, and let’s explore the future of UX with AI technology.
How far along are companies with AI?
Over the years, the history of tech advancements within the digital landscape has rapidly progressed. Top companies have embraced technology in diverse ways.
This journey through various technological epochs, from the early days of the internet to the rise of cloud computing, has paved the way for the next significant leap in business technology: the integration of artificial intelligence. Based on a May 2023 Forrester Research survey, businesses eager to integrate AI are spreading their investments across various tech niches. The survey, polling 1,981 global data and analytics leaders, reveals machine learning platforms (77%), machine vision (76%), and AutoML (76%) as the primary investment hotspots.
Despite going through multiple AI breakthroughs over the last four decades, the journey is not complete. Businesses continue investing in tech niches like machine learning (ML) changing the way humans interact with computers. Next up, learn how AI is used to redefine user interaction in real-life digital products.
AI in UX: changes to human-computer interaction
AI and UX are converging, transforming how users interact with digital products. This shift isn't just about new features; it's about reimagining the user experience. AI's integration into UX design is making products smarter, more intuitive, and highly responsive to user needs.
Consider Duolingo, which employs AI to customize language learning paths, or Grammarly, which uses advanced NLP to provide real-time writing assistance, going beyond basic spell check. These apps, alongside countless others, demonstrate a proactive approach, setting new standards in user engagement and satisfaction.
For product developers and managers, this means adapting to a landscape where AI-driven interfaces are becoming the norm.
Computers understand and speak human language
The latest tech breakthrough has changed forever the way we interact with machines. Natural Language Processing (NLP) became a bridge between computers and humans enabling both to interact using natural language. It is the NLP that allows computers to understand, interpret, and generate human language.
Traditionally, NLP relied primarily on text-based inputs, processing them to generate text-based outputs. Now, NLP has evolved to encompass auditory and visual tasks like speech recognition, speech synthesis, text-to-speech, and image captioning. Researchers have also delved into multi-modal settings for tasks like sentiment (emotional) analysis.
The evolution of NLP is evident in the increased adoption of Conversational User Interfaces (CUI). In the world of e-commerce and customer support, chatbots and virtual assistants have become the norm, using NLP to provide contextual, real-time assistance.
In personalizing user experiences, NLP is revolutionizing how e-commerce and streaming services tailor content to user preferences. By analyzing inputs, Netflix and Spotify provide almost intuitive recommendations, boosting user engagement. Additionally, NLP's role in enhancing accessibility is significant, broadening access for users with visual or cognitive impairments and fostering a more inclusive digital environment.
This shift towards conversational interfaces is more than technical advancement; it reflects a deeper understanding of user needs and behaviors.
Multimodal interfaces redefine user experience
As of 2024, multimodal technologies are reshaping the look and feel of digital product interfaces, ensuring an immersive, cohesive experience across multiple devices. Combining various modes of input (text, voice, touch, or gestures) and output (like visual, auditory, or haptic responses) multimodal technologies facilitate more natural and intuitive communication with digital systems.
For instance, smart assistants have evolved to understand voice commands, recognize images, interpret text, and even perceive emotions, enabling users to engage in more human-like dialogue.
Smart assistance and flow optimization by AI agents
AI agents are redefining user experiences by enhancing user flows, automating tasks, and offering smart assistance. These agents, powered by artificial intelligence, not only perform tasks on behalf of users but also learn from interactions to provide more personalized experiences over time.
A great example of this is the innovative startup HyperWrite. It revealed an AI agent capable of navigating and interacting with websites. CEO Matt Shumer demonstrated the AI's abilities, such as completing an online order on Domino's Pizza, via their Chrome extension.
HyperWrite's AI learns from past interactions and promises to usher in a new era of web automation and personalized assistance.
Though promising in automating web tasks, concerns around security like phishing, hacking, and fraud were addressed, with Shumer ensuring they are working on these issues.
The current generation of assistants primarily functions through text analysis rather than computer vision and is limited by small context windows. However, with enhanced training datasets and integration with GPT-4, which can process hundreds of thousands of tokens, their performance will significantly improve. Thus, the question isn't whether AI agents can be enhanced, but rather when this advancement will occur – whether it will be within a year or even in the next six months.
No more inaccurate support due to speech recognition technologies
– You: "Hey, Siri, lower the lights.
– Siri: "Sorry, I can't find the song 'Love is the light' in your music history."
Don’t we all hate when this happens? Hopefully, things are going to be much better in the near future. Speech recognition is the ultimate marriage of NLP and AI, bringing us closer to a world where computers can understand and transcribe human speech with ease. As for now, it is possible to accurately transcribe spoken words, even in noisy environments or with different accents.
Fortune Business Insights projects that the global automatic speech recognition market size is expected to grow from $12.62 billion in 2023 to $59.62 billion by 2030, at a CAGR of 23.7% during this period (2023-2030).
One of the multiple Ńases of speech recognition enhancements is Whisper AI, a cutting-edge AI model that cuts transcription errors by 50%, effectively dealing with accents, background noise, and complex vocabulary. It can transcribe in 99 languages and translate them to English.
It was trained on 680,000 hours of multilingual internet data and includes extensive punctuation support. Whisper stands out from earlier OpenAI models like DALLE-2 and GPT-3 as it's open-source and freely available.