It’s been about two years since ChatGPT took the world by storm, setting off an AI frenzy that shows no signs of cooling down.
Generative AI has reshaped product strategies, with investors redirecting funds and companies pouring billions into R&D—not just to seize opportunities but to stay relevant.
2024 has been particularly fascinating, with a mix of groundbreaking AI use cases and UX models, some celebrated, others criticised (remember Rabbit R1?). Despite the technology’s rapid evolution, we’re still figuring out what works best for AI product UX. The hits and misses are all part of the iterative process. And as AI Agents emerge as the latest trend, 2025 promises to be even more exciting.
Let’s explore how the UX of AI is evolving and share actionable insights for integrating AI into your platforms.
ChatGPT Remains King
The race for AI dominance continues, with ChatGPT, Gemini, and Claude vying for the top spot. As the performance gap narrows, UX is becoming the ultimate differentiator. The winner will likely be the one that best adapts to users’ needs.
Take OpenAI, for example. Switching between multiple tools is a hassle, so integrating its image generator DALL-E 3 into ChatGPT as a unified platform was a smart move. Sora, its video generation model, might follow the same path as it matures.
Another key evolution in ChatGPT’s UX is its focus on users’ needs. People use it to accomplish certain tasks more efficiently, so it has developed simple but impactful features that make it a great work tool. For instance, its ‘canvas’ option for writing documents, social media posts, or even code enhances productivity and allows users to tailor outputs to their objectives.
Similarly, the recent launch of its Tasks beta underscores this philosophy. Tasks automate everyday actions, like summarising daily AI news, reinforcing the platform’s role as a productivity tool, as do many more features such as ‘Marketplace’ and ‘Search.’
UX Insights
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Solve the User’s Problem, Not the Prompt
Most users aren’t prompt experts. The key is designing tools that help the model infer the problem they need to solve. Tags like “Create image” or “Summarise” are a great start, but you can do more. For example, if someone’s working on a presentation, why not automatically generate image suggestions? Or if they’re learning about a topic, offer next steps like “Find certifications” or “Create a training plan.”
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Create Specific UX for Specific Tasks
ChatGPT’s ‘canvas’ feature is a great example of designing UX for specific use cases, like simplifying coding. You need to explore use cases in depth and extract what tasks the user needs to perform. For instance, creating social media posts is a common use case. An interface with quick toggles to select the social media platform, tone of voice and post frequency would be a great feature.
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Ideas Are Born in the Real World
Great ideas don’t come solely from staring at your screen. To create truly impactful products, connect with your end-users, understand their daily routines, and grasp the context in which they interact with your solutions. Start with the basics: engage with people who have industry and functional expertise to gather meaningful insights. But interviews only scratch the surface. The real magic happens when you shadow your users over several days, experiencing their challenges firsthand. By living their struggles, you’ll generate invaluable ideas.
Closing Thoughts
Across platforms like ChatGPT, LinkedIn, Canva, and CoPilot, one principle holds true: exceptional UX is the key to standing out. Don’t rely solely on user data; engage directly with your audience, collaborate with experts, shadow end-users, and take notes.
Yalla! 😊
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