User Experience Design Trends

Product managers & designers working with AI face a unique challenge: designing a delightful product experience that cannot fully be predicted. Traditionally, product development followed a linear path. A PM defines the problem, a designer draws the solution, and the software teams code the product. The outcome was largely predictable, and the user experience was consistent. However, with AI, the rules have changed. Non-deterministic ML models introduce uncertainty & chaotic behavior. The same question asked four times produces different outputs. Asking the same question in different ways - even just an extra space in the question - elicits different results. How does one design a product experience in the fog of AI? The answer lies in embracing the unpredictable nature of AI and adapting your design approach. Here are a few strategies to consider: 1. Fast feedback loops : Great machine learning products elicit user feedback passively. Just click on the first result of a Google search and come back to the second one. That’s a great signal for Google to know that the first result is not optimal - without tying a word. 2. Evaluation : before products launch, it’s critical to run the machine learning systems through a battery of tests to understand in the most likely use cases, how the LLM will respond. 3. Over-measurement : It’s unclear what will matter in product experiences today, so measuring as much as possible in the user experience, whether it’s session times, conversation topic analysis, sentiment scores, or other numbers. 4. Couple with deterministic systems : Some startups are using large language models to suggest ideas that are evaluated with deterministic or classic machine learning systems. This design pattern can quash some of the chaotic and non-deterministic nature of LLMs. 5. Smaller models : smaller models that are tuned or optimized for use cases will produce narrower output, controlling the experience. The goal is not to eliminate unpredictability altogether but to design a product that can adapt and learn alongside its users. Just as much as the technology has changed products, our design processes must evolve as well.

Inclusive form design isn’t a luxury, it's a civil right. Most registration processes are forms based. Without accessible forms, people who use assistive technology can't get through the door. When we talk about submit buttons, the choice to make them active all the time isn’t about “just making things easier” — it’s about removing real accessibility barriers. An active submit button means users who rely on screen readers or keyboard navigation can always finish what they started. But most designers/UX folks talk about submit vs in-line field validation as an "or." I propose we look at them as an "and." Just like the little girl in the meme says, "why not both?" If you have an active submit button and ALSO add in-line validation, which flags issues as they arise, you are creating an experience that sets the standard for a best practice. You aren't just following the guidelines to achieve compliance, you are making sure that people with disabilities have the best chance of becoming customers as anyone else. Real-time feedback reduces stress for those who may struggle to go back and forth in a form, helping everyone complete it without hassle. Active submit combined with user-friendly error message means users don't get stuck looking through a long form trying to figure out which required field they missed. Companies like #Amazon have it right — they combine both. When we prioritize both an always-active button and in-line validation, we’re making digital spaces accessible, user-centered, and, most importantly, equitable. Alt: first image is a female child seated in an office with the caption: "Submit Button always active" on the left side and "in-line field validation" on the right side. Beneath it is a question: "why don't we have both? " second image shows group of persons lifting the female child up in celebration. #AccessibilityMemeMonday #InclusiveDesign #AccessibleForms #DigitalEquity #Disability #Inclusion #UserCenteredAccessibility https://lnkd.in/ecX_YG93

The future of customer experience is proactive, personalized, and powered by AI. This new era in customer experience represents a fundamental shift in how businesses will connect with their customers. Here’s how it’s taking shape: 1. Seamless AI-Human Collaboration The future of CX lies in the synergy between AI and human touch. AI will handle repetitive tasks and complex analysis, freeing human agents to focus on empathy and nuanced problem-solving. This isn't about replacement, but enhancement. 2. Proactive Issue Resolution We're moving beyond reactive CX models. Advanced AI systems will detect patterns and flag potential issues before they impact customers, shifting the paradigm from problem-solving to problem prevention. 3. Real-Time Personalization Beyond basic segmentation, AI delivers truly personalized experiences by analyzing customer data and contextual signals instantaneously. This enables businesses to dynamically adapt every touchpoint, creating experiences that feel custom-crafted for each customer. 4. Emotionally Intelligent Interactions The next frontier is AI that can sense customer sentiment and adjust communication accordingly. This emotional intelligence will be crucial in creating authentic, empathetic customer experiences at scale. 5. Evolving CX Systems: Static systems are becoming obsolete. The future belongs to AI that continuously learns and evolves from every interaction, constantly improving the entire CX infrastructure. The companies poised to lead are doing more than deploying AI—they’re reimagining the entire customer journey with AI at the center. I'm curious to hear from fellow leaders and innovators: What AI-driven CX innovations have caught your attention recently? How do you see these advancements shaping your industry? #CustomerExperience #AI #BusinessTransformation #CX

As AI reasoning models become more sophisticated, they're also becoming slower—deliberately taking time to process complex problems. This creates a UX challenge we haven't fully solved: How do we design interfaces that make AI thinking time productive rather than frustrating? One potential solution is to treat these windows like "supersets" in weightlifting. You do a push exercise, then immediately a pull exercise while your push muscles recover. You're always productive, just shifting focus. Applying this concept to AI interfaces: Imagine you're a lawyer using AI to review a complex 100-page contract: "Identify any unusual clauses, compliance risks, and compare terms to our standard agreements." While the AI works through this deep analysis, instead of watching a loading screen, the interface prompts you to begin preparing client-specific context notes or to outline negotiation strategy options based on different potential outcomes. The system intelligently guides you through complementary tasks matched to the processing time. When the AI completes its review, you've already completed valuable work that enhances your overall legal strategy. This "multitasking UX" approach seems better than the alternative of letting the user wait, sitting on their hands. Sure, over a long enough time horizon, this lag will eventually disappear. But in this emerging era, UX designers will increasingly need to solve for "reasoning model lag." Not by making users wait but by making waiting time productive.

🎭 Accessibility isn’t just a checkbox. It’s a catalyst for innovation. Last year, I created the first accessible HTML Playbill. This year, I coordinated the Playbill for Oliver! The Musical. And the curb cut effect showed up in full force. On opening night, the printer broke. The next day, the network went down. No printed programs. No network. But because I had already built an accessible HTML version for this show, we had a fast-loading, mobile-friendly program ready to go. I added a QR code, step-by-step instructions, and URLs for folks unfamiliar with QR tech. It loaded quickly on a finicky network and people could view it in low light during the show when it's too dark to see the printed program. The organization later added a QR code to a PDF version. If I could do it again, I’d direct people to the accessible version. At the top of that version, I'd link to the PDF version. This lets people choose between the faster loading page on mobile devices in a building with a poor connection or the full image program. This is the curb cut effect: a solution designed for accessibility that benefits everyone. And it’s also a reminder ... Hire us. Involve us. Disabled people bring lived experience that leads to creative, practical, and inclusive solutions. We don’t just advocate for accessibility. We design and build it. Accessibility isn’t charity. It’s a strategy. Want resilient systems? Involve disabled problem-solvers. If you're a person with a disability or have worked with disabled collaborators, what unexpected value do disabled people bring to the table? Accessibility isn’t just about compliance. It’s about creativity, resilience, and insight. If you’re ready to build smarter, more inclusive systems, drop a comment or DM. 🔔 Tap profile bell (You may need to do it again. LinkedIn reset it.) 👉 Follow #MerylMots for past posts #UserExperience #Accessibility The image shows what the signs looked like: "Oliver! Playbill" with four steps. A box where the QR code appeared and the URL beneath it.

AI is killing the UX Design role as we know it. Designers who adapt will evolve into Strategic Experience Architects who will be in high demand. While traditional designers are "pixel-pushing," a new set of designers is emerging.  They're using AI to fast-track design ideas and turning prototypes into working code. A lot of what UX designers are doing manually today is exactly what AI tools are getting good at: • Rapid wireframing concepts • UI component creation • Basic user research • Persona development • Usability testing automation The ability to automate some UX tasks is already here. We have to assume that the technology will only advance quickly. I recently spoke with several Product Managers who are already replacing basic UX tasks with AI tools. When PMs can generate, iterate, and validate designs using AI, what happens to the traditional UX role? Simple products and startups will streamline. PMs with AI will be able to handle the basics. We're already seeing this shift. However, there's a big opportunity here as well. AI has a critical blind spot: it can't grasp the nuanced psychology of human behavior. It can't navigate complex stakeholder dynamics. It can't translate business objectives into meaningful user experiences. This is where the evolution happens. The future belongs to Strategic Experience Architects who: ✦ Define the right problems to solve ✦ Extract insights from human complexity ✦ Align teams around user value ✦ Guide AI with human context The market is splitting: → Basic products: UX roles blend into other roles on the team → Complex enterprises: Strategic UX roles become critical Fortunately, most valuable products are complex and human-centered. Want to stay relevant? Here's what to consider. 1. Master AI design tools   But don't just use them, learn to orchestrate them 2. Evolve from maker to strategist   Your value is in thinking, not in pushing pixels (AI will eventually handle this) 3. Develop business intelligence   Connect user needs to revenue 4. Study human psychology    This is your moat against AI 5. Learn systems thinking Focus on developing repeatable systems in your daily work The UX industry isn't dead, but it is transforming. -- ♻️ Share if you think this will help others ➕ Follow Jason Moccia for more insights on AI and Product Design

Netflix just launched an OpenAI-powered search feature that's completely changing how we discover content. Instead of just searching by title or actor, you can now find shows based on your emotions and specific situations. As a Product manager, this fascinates me because it solves a real user problem. We've all experienced "decision paralysis" scrolling through endless options. Netflix recognized this pain point and created a solution that understands natural language and context. What's brilliant about this approach is… how it transforms the user experience from transactional to conversational. Rather than forcing users to think in keywords, it allows them to express what they actually want: "Something uplifting after a tough day" or "A thriller that won't keep me up all night." The rollout strategy is equally smart - testing in Australia and New Zealand on iOS before expanding to the US. This controlled release allows them to gather feedback and refine the algorithm before a wider launch. This is product thinking at its best - using AI not as a flashy feature but to solve a fundamental user problem. It's also a reminder that even established platforms can innovate on core experiences that seem "good enough." What do you think about this approach? Would an emotion-based search make you more likely to find something to watch instead of endlessly scrolling? #ProductManagement #UserExperience #AIinProduct #Netflix

AI products like Cursor, Bolt and Replit are shattering growth records not because they're "AI agents". Or because they've got impossibly small teams (although that's cool to see 👀). It's because they've mastered the user experience around AI, somehow balancing pro-like capabilities with B2C-like UI. This is product-led growth on steroids. Yaakov Carno tried the most viral AI products he could get his hands on. Here are the surprising patterns he found: (Don't miss the full breakdown in today's bonus Growth Unhinged: https://lnkd.in/ehk3rUTa) 1. Their AI doesn't feel like a black box. Pro-tips from the best: - Show step-by-step visibility into AI processes - Let users ask, “Why did AI do that?” - Use visual explanations to build trust. 2. Users don’t need better AI—they need better ways to talk to it. Pro-tips from the best: - Offer pre-built prompt templates to guide users. - Provide multiple interaction modes (guided, manual, hybrid). - Let AI suggest better inputs ("enhance prompt") before executing an action. 3. The AI works with you, not just for you. Pro-tips from the best: - Design AI tools to be interactive, not just output-driven. - Provide different modes for different types of collaboration. - Let users refine and iterate on AI results easily. 4. Let users see (& edit) the outcome before it's irreversible. Pro-tips from the best: - Allow users to test AI features before full commitment (many let you use it without even creating an account). - Provide preview or undo options before executing AI changes. - Offer exploratory onboarding experiences to build trust. 5. The AI weaves into your workflow, it doesn't interrupt it. Pro-tips from the best: - Provide simple accept/reject mechanisms for AI suggestions. - Design seamless transitions between AI interactions. - Prioritize the user’s context to avoid workflow disruptions. -- The TL;DR: Having "AI" isn’t the differentiator anymore—great UX is. Pardon the Sunday interruption & hope you enjoyed this post as much as I did 🙏 #ai #genai #ux #plg

UX is evolving. And it's not just about the user anymore. 🤖 Enter AX (Agent Experience). AX expands the design focus beyond just humans to include AI agents, humans, and digital coworkers. In the agentic AI world, all of them are interacting with systems to help get things done. 𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗨𝗫 𝗶𝘀 𝘀𝗶𝗺𝗽𝗹𝗲 𝗮𝗻𝗱 𝗱𝗲𝘁𝗲𝗿𝗺𝗶𝗻𝗶𝘀𝘁𝗶𝗰.  You tap a button. Something happens in the product. Job done. 𝗕𝘂𝘁 𝗶𝗻 𝘁𝗵𝗲 𝗔𝗫 𝘄𝗼𝗿𝗹𝗱 𝘁𝗵𝗶𝗻𝗴𝘀 𝗮𝗿𝗲 𝘄𝗮𝘆 𝗺𝗼𝗿𝗲 𝗱𝘆𝗻𝗮𝗺𝗶𝗰: - The agent tracks ongoing goals, nudges next steps, improves over time. - The system plans its own path - it senses, infers, chooses actions the designer didn't script. - Context is learned, not asked. Patterns, preferences, even team dynamics are remembered and reused. - And success is no longer just task completion. It's also things like earned trust, retention, and long-term value. 𝗪𝗲'𝗿𝗲 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗯𝘂𝗶𝗹𝗱𝗶𝗻𝗴 𝗶𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲𝘀 𝗮𝗻𝘆𝗺𝗼𝗿𝗲. We're designing incentives and interactions across humans and AI agents. 𝗗𝗲𝘀𝗶𝗴𝗻 𝗽𝗿𝗶𝗼𝗿𝗶𝘁𝗶𝗲𝘀 𝘄𝗶𝗹𝗹 𝗻𝗼𝘄 𝗶𝗻𝗰𝗹𝘂𝗱𝗲: → How do these AI agents learn and collaborate? → How do we ensure they align with human goals? → How do we build systems that evolve, not just react? The future of experience design is agentic. And this is a huge change in how we design, collaborate, and operate in increasingly AI-integrated systems. And the AX conversation is just beginning. 🔔 Share this with someone who needs to be prepared for the AX future. 👉 Know any new innovative tools or companies powering the AX revolution? Let me know! #AgenticAI #AgentExperience #futureofwork #design

It seems like every day, someone who doesn’t know anything about design proclaims “UI is going away” thanks to advances in AI. The logic goes that soon we’ll just converse with an AI assistant to get everything done. We won’t need any of these pesky menus, buttons, maybe not even screens. But user interfaces aren’t disappearing; they’re evolving. AI makes great UI more important than ever so that we can understand and use it effectively, building better mental models of what this technology can and cannot do. We cannot know AI capabilities and limitations solely from a text box. Let’s stop pretending that a single chat box is the pinnacle of user experience. Conversational AI is powerful, but one size doesn’t fit all for interactions. In many cases, a visual interface is far more efficient and user-friendly than typing or speaking. Consider voice assistants: Alexa was originally voice-only, but even Amazon realized pure voice has limits, hence the Echo Show and devices with screens. Why? Because humans consume visual information faster than spoken information. We can read ~250 words per minute but speak or listen at ~150 wpm. If you ask an AI assistant for the top five movies playing tonight, do you really want to sit and listen as it reads a list aloud? Probably not. The rise of AI is leading new kinds of UI, not a UIpocalypse. We’re already seeing the advent of UI for AI: interfaces designed specifically to harness AI’s power without dumping the burden on the user to craft perfect prompts. Instead of hiding functionality behind a blank text box, give people intuitive controls to direct the AI. Imagine an image editing AI. Rather than forcing the user to type “make the sky brighter and remove the tree on the right,” why not let them click or highlight the parts of the image they want changed? Select a region and adjust a slider, or paint over the object to remove. Tools, not just text boxes. This kind of direct manipulation is often more precise and user-friendly than playing AI Mad Libs with a prompt. AI is also enabling hyper-personalization of interfaces. Rather than one UI to rule them all, AI can tailor the layout, content, and functionality to each user’s needs in real time. Far from disappearing, UIs might become even more present but highly individualized. The future of UX could be one where every interaction is an individualized experience, with interfaces adapting on the fly to a user’s context and preferences. Rumors of UI’s demise are greatly exaggerated. User interfaces are adapting to AI. From multi-modal experiences that blend conversational AI with visual elements, to adaptive UIs personalized by AI, to new design patterns for AI-first products, it’s an exciting evolution. But nowhere in this future does the UI vanish into a black box. Good UI will be a competitive advantage and a key to unlocking AI’s potential for users. Read more: https://lnkd.in/esCfwmKz