As a design strategist and UX working in tech, I’m always trying to learn from people to design the most engaging digital experiences researchers. I want to understand how they think, feel, act, and, most importantly, why they do so in a certain way to come up with the most interesting concepts. To keep innovation happening, and our concepts relevant to users, we need to learn from them continuously and that is not always the easiest of tasks. Luckily, we are witnessing a rapid shift in how we can gather insights from users, and data is at the forefront of it. Now that we can rapidly track, gather, and analyze data, AI emerges as a key tool to make adjustments to the experiences we design in real-time. Today, I want to share how AI has helped me create concepts that connect real-life experiences with digital ones by leveraging users’ data.

AI and user experience (Ux)

AI can detect similarities and correlations among different data points and use these patterns to make accurate predictions or provide recommendations. This is done by analyzing large data sets and identifying patterns and relationships that may not be immediately apparent.

For example, I worked with a financial institution to design a new feature of their app that would make the checkout process at different retailers faster. Using AI, the app would analyze customers’ purchase history, browsing behavior, and demographics to identify patterns of retailers they are likely to be interested in. Based on these patterns, we can then provide personalized recommendations of places where they might like to connect their credit card for an expedited checkout, creating a seamless experience for users and potentially increasing card usage.

AI’s advancements: moving beyond pattern analysis to user learning and enhanced experiences

AI can also go a step further and not only analyze patterns and correlations but also learn from users’ performance and feedback to enhance experiences. This was the case for a project I worked on with a big fitness company for which we created a training app. Using machine learning algorithms, the app can analyze a user’s fitness level, workout history, and personal preferences to create a customized plan that meets their specific needs. Furthermore, AI can learn from the user’s feedback and adjust the program based on their experience, creating a more personalized and effective training regimen over time. The result is a tailored training program that maximizes the user’s fitness gains and provides a more engaging and enjoyable experience.

AI’s critical role: creating omnichannel experiences for seamless customer journeys

Additionally, AI plays a critical role in creating omnichannel experiences by providing a seamless, consistent, and personalized customer journey across multiple channels. By analyzing customer data from various touchpoints, such as social media, e-commerce websites, and physical stores, we are able to gain insights into customer preferences, behaviors, and purchase histories. By leveraging this data, AI can provide personalized recommendations, offers, and promotions to customers through multiple channels. Additionally, AI-powered chatbots and virtual assistants can provide instant support and assistance to customers across channels, improving customer satisfaction and loyalty.

This is exactly what we wanted to leverage when we came up with a concept for a big national retailer that was looking to improve its at-store experience. We designed an in-store experience that was highly interactive and provided a seamless experience even after users left the store and continued their journey online by receiving highly accurate product recommendations via email, social media, and mobile app notifications. By installing iPads across the store users could scan the products they liked, which would then be placed in their dressing room ready for them to try, and see personalized recommendations of available products. This would also help store associates understand users’ preferences, and provide recommendations of other available products thus improving shopping support.

What can we learn from ChatGPT and the challenges ahead

Since its launch at the end of 2022, there has been much hype surrounding ChatGPT and its capabilities. The general public has been mostly welcoming and accepting of it, and we’re seeing how relevant it has become in our lives. This is a clear example of how we are becoming more accepting of AI technology in our daily lives. Its popularity suggests that people are becoming more comfortable with the idea of ​​interacting with machines and are willing to engage in conversations with them as if they were talking to another human being.

However, it is important to note that the extent to which people feel positively or negatively about AI can vary greatly depending on the specific application and context in which it is being used. Some people may view AI as a helpful tool that can assist with tasks and improve efficiency, while others may be wary of its potential to replace human workers or invade privacy.

Our collective focus as designers

As designers, we need to understand these nuances, so that we can use AI in a way that is helpful to users without being intrusive or overly pushy. Many people are concerned about the potential risks associated with AI, such as the loss of jobs or invasion of privacy. To address these concerns, we need to be transparent about the use of AI in the digital experiences we create, and explain how the technology is being used to benefit our users.

Another important thing to keep in mind is that we should provide control and customization options when it comes to AI-powered features, such as the ability to turn them on or off, adjust their settings, or provide feedback. People often appreciate having control over their digital experiences.

Finally, it is important to maintain a user-centric mindset at the core of our process. Creating solutions that are empathetic to users will be the key to success. We can incorporate elements of empathy into our AI-powered experience by creating personas, incorporating natural language processing, and providing feedback that feels personalized. Beyond that, we need to keep listening to our users, interacting with them, and learning from their stories and experiences, to effectively create AI-powered solutions that are helpful, transparent, ethical, and empathetic.

Andrea Sanchez is a Brooklyn-based Design Strategist and Researcher who currently leads digital transformation strategy projects at Globant.