The Impact Of AI On User Experience Innovation

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

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

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.

In customer experience (CX), the closed-loop feedback (CLF) model has been a cornerstone for over two decades, originally designed to ensure responsiveness and adaptation. It's time for a change. With the advent of artificial intelligence, it's clear that merely adapting this model isn't enough. It's old tapes. It needs to evolve. Here's what's next: Real-time Interaction Management: Traditional CLF reacts to feedback after the fact. And, traditionally, closing the "inner loop" requires a human to follow up. AI turns this on its head. Imagine a system that adjusts the customer journey in real-time based on predictive analytics, reducing friction points before they affect the customer experience. Large Action Models: We all know that AI can dive deep into data lakes to instantly identify patterns and root causes of customer dissatisfaction. This rapid analysis allows companies to not only close the feedback loop faster, but also implement more effective solutions. This will come in the evolution of Large Language Models, or LLMs, to LAMs, or Large Action Models. Continuous Learning Systems: AI transforms CLF from a loop that ends into continuous cycle of improvement. These systems learn from each interaction, constantly updating and refining strategies to enhance the customer experience. This means that the feedback loop is ever-evolving, driven by AI's ability to adapt to new information and complex variables, seamlessly. CX leaders have to embrace AI's potential to redefine our foundational practices. It's time to innovate beyond the traditional CLF and leverage AI to deliver personalized experiences, and at scale. How are you thinking about adaptive, predictive, and personalized CX strategies? Your answer can't be to hire more people to close more loops. #customerexperience #ai #journeymanagement #survey #CLF

The rapid development of artificial intelligence (AI) is outpacing the awareness of many companies, yet the potential these AI tools hold is enormous. The nexus of AI and emotional intelligence (EQ) is emerging as a revolutionary game-changer. Here’s why this intersection is crucial and how you can leverage it: 🔍 AI can handle data analysis and repetitive tasks, allowing humans to focus on empathetic, creative, and strategic work. This synergy enhances both productivity and the quality of interactions. Imagine a retail company struggling with high customer churn due to poor customer service experiences. By integrating AI tools like IBM Watson's Tone Analyzer into their customer service process, they could identify emotional triggers and tailor responses accordingly. This proactive approach could transform dissatisfied customers into loyal advocates. Practical Application: AI-driven sentiment analysis tools can help businesses understand customer emotions in real-time, tailoring responses to improve customer satisfaction. For example, using AI chatbots for initial customer service interactions can free up human agents to handle more complex, emotionally charged issues. Strategy Tip: Integrate AI tools that provide real-time sentiment analysis into your customer service processes. This allows your team to quickly identify and address customer emotions, leading to more personalized and effective interactions. By integrating AI with EQ, businesses can create a more responsive and human-centric experience, driving both loyalty and innovation. Embracing the combination of AI and EQ is not just a trend but a strategic move towards future-proofing your business. We’d love to hear from you: How is your organization leveraging AI to enhance emotional intelligence? Share your thoughts and experiences in the comments below! #AI #EmotionalIntelligence #CustomerExperience #Innovation #ImpactLab

When UX Becomes Human Something fascinating is happening in the world of user experience. After years of perfecting clicks and swipes, we are witnessing a fundamental shift - UX is learning to feel. AI powered platforms should be able to understand frustration in typing patterns, adapt its approach in real-time, and turn what could have been a poor customer experience into a positive interaction. Not through better button placement, but through better understanding. The evolution we are seeing is - From user journeys to emotional journeys From touch points to trust points From interface design to emotion design From user personas to human relationships The best UI is sometimes no UI at all. As we move toward ambient computing, with smart glasses, AR interfaces, and whatever comes next, the line between digital and human experience will continue to blur. The winners won't be those with the slickest interfaces, but those who create the most emotionally intelligent ecosystems. Are you ready for the era where UX isn't just about user experience, but human experience? #HumanExperience #AIInnovation #FutureOfUX #cio #ceo #cto #cdo #cfo #caio #EmotionalIntelligence #DigitalTransformation All opinions are my own and not those of my employer. 

I had an engaging discussion with a client about Agentic AI and its transformative potential for Customer Experience (CX)—an area deeply tied to my previous work at Cisco and my current Seridian Group clients.   Innovation is thriving in CX, where AI is being deployed in agent augmentation, internal support, hybrid workflows, and even autonomous customer interactions—unlocking efficiency and personalization.   Key takeaways: - Success hinges on the use case, autonomy, and transparency. - Implementation requires governance and workflows that align technology, employees, and customers. - The future lies in hyper-personalization, proactive actions, and a seamless omni-channel experience.   Agentic AI is a game-changer in B2B and B2C, where solutions must balance complexity and customer experience. Grateful for the chance to explore how businesses can navigate this exciting frontier!   #AI #CustomerExperience #Innovation #AgenticAI

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