In the intricate ballet of design and technology, Artificial Intelligence (AI) has taken center stage, guiding the steps of UX designers and developers alike. Though met with an initial air of skepticism, the potential of AI in sculpting user experiences is undeniable, as it deciphers and mirrors user behaviors. Let's take a deep dive into the transformative role of AI in the world of UX design.

The tapestry of UX design is being re-woven with AI threads, bringing with it an invigorated design approach. Let’s pull back the curtain on some groundbreaking AI tools lighting up the design arena: ChatGPT and Midjourney.

ChatGPT, an AI conversational maestro, has opened up a galaxy of possibilities for UX designers. However, like every prodigy, it has its quirks. Here's a blueprint of how ChatGPT finds its place in the UX toolkit:

Crafting User Personas: By simply prompting ChatGPT with a user type and industry, designers can receive a foundational user persona. Further probing with pointed questions, such as understanding a user type from a UX researcher's perspective, refines the output, creating a more tailored persona.

Upon comparing ChatGPT generated personas with traditionally crafted ones, a striking 80-90% match was observed in general industry knowledge. While ChatGPT shines as a tool for creating baseline protopersonas, its efficacy diminishes with the need for detailed iterations. Thus, early-stage product development becomes its playground.

Demystifying Competitors: Researching features of competitors can be tedious. Enter ChatGPT. With its adeptness and prompts fortified with data from resources like getapp.com, ChatGPT can deftly compare features, conduct SWOT analyses, or even discern a USP.

Documenting Requirements: While ChatGPT’s prowess is commendable, it fell short in translating client requirements into actionable documents. Some things are best left to human touch.

With a foundational understanding of AI's potential in enhancing UX design, the next step is to traverse the path of designing products with AI at their core. As we journey forward, the key will be harmonizing AI's capabilities with human intuition to craft experiences that truly resonate.

Delving into the realm of AI-infused UX design, the trajectory of AI’s impact on design and vice-versa is clear. But when we design AI-powered products, the synthesis of trust becomes paramount. A product’s success hinges on its ability to foster trust in users, to ensure they comfortably adopt and use the AI-driven capabilities.

Let’s explore the intricacies of trust-building when designing AI-powered systems:

Transparency Through SimplicityDemystifying AI isn't about showcasing complex algorithms but about relaying its workings in layman’s terms. Using intuitive visuals, concise explanations, and relatable metaphors makes AI more accessible to users. When they understand, even at a basic level, how an AI feature works, it reduces fear and increases acceptance.

Accountability and Feedback LoopsAs designers, building systems that allow users to provide feedback or challenge AI decisions is crucial. This makes users feel heard and gives them a semblance of control over AI-driven processes.

Fairness and BiasAI systems can sometimes be fraught with biases stemming from the data they are trained on. Designing with ethics in mind means ensuring fairness in AI processes. Regularly testing AI outcomes for any signs of discriminatory or biased results and correcting them is imperative.

Privacy and Data UsageTrust also means being transparent about how user data is utilized. Clearly stating how AI uses data, ensuring users can opt out, and maintaining stringent data privacy standards will go a long way in building trust.

Personality and VoiceJust as we humanize brands, giving AI a voice or personality can make it more relatable. Whether it’s Siri’s witty remarks or Alexa's helpful demeanor, imbuing AI with character can enhance user trust.

Emotionally Intelligent ResponsesAI that can pick up on user emotions or sentiments and respond empathetically can make users feel more understood and valued. This does not mean making AI overly human-like but rather ensuring it is responsive in a way that respects user emotions.

Progressive InteractionIntroducing users to AI features progressively, allowing them to get comfortable with basic functions before moving onto more advanced ones, can ease them into the AI experience.

Seamless OnboardingAs mentioned, demos during the onboarding process are vital. Interactive tutorials, walkthroughs, and tooltips can guide users as they navigate the AI-enhanced product.

The fluidity and adaptability of AI present unique challenges for traditional usability testing. An AI system can continuously evolve, so it might not be in its final form during usability tests. Designers must, therefore, adapt and devise innovative ways to simulate AI's behavior, ensuring the user experience aligns with intended outcomes. By clearly demarcating AI-generated content, we respect users' intelligence and autonomy, ensuring they are always informed participants in their interactions.

Current AI applications in design, like Khroma or Fontjoy, are largely task-oriented. They optimize specific design processes but don't holistically transform the design journey. That said, their very existence is testament to the leaps AI has taken and the untapped potential in the horizon.

As designers, our role will morph. We'll shift from being mere creators to collaborators, working alongside AI. This co-creation model will redefine the design landscape. It's akin to a musician working with an advanced synthesizer; the machine might produce the tune, but it's the human touch that gives it soul.

In conclusion, the interplay between AI and UX design is still in its nascent stages. With time, education, and experimentation, it's poised to reshape the design landscape. By prioritizing ethical considerations, understanding and countering biases, and embracing AI as a collaborator rather than a tool, we can herald an era where design is not just human-centric but human-AI collaborative.