Artificial intelligence (AI) can potentially transform several industries, such as the UX industry Different AI applications have the potential to handle routine, creative, analytical, and strategic processes, such as writing a script or summarising an article. Specific AI applications, such as ChatGPT, have gained widespread popularity for their intelligence and seamless conversation capabilities. How organizations should handle the wide use of AI technologies is still uncertain. Also, there is a global debate whether these AI applications should be officially banned from access for various reasons such as concerns about negative impacts on students’ learning.
AI is expected to have a significant impact on UX Design, also. Here are some potential ways:
- Personalization: AI can help analyze user data to provide personalized experiences, such as tailored content and recommendations. For example, AI algorithms can integrate data from various sources, such as user behavior, demographics, and preferences, to create a highly personalized experience for each user.
- Predictive Analytics: AI algorithms can analyze user behavior, preferences, and patterns to predict users’ needs, making the UX more intuitive and efficient. For example, AI algorithms can predict user’s engagement, and detect unnoticed patterns in user data.
- Automation: AI can generate automated design or personas and automate repetitive tasks. This allows designers to focus on more complex design challenges, resulting in faster design iterations and improvements. For example, AI tools can be used to automatically create personas that aim to represent the target audience.
- Voice Interfaces: AI-powered voice assistants provide a new dimension to UX by allowing for hands-free, voice-controlled interactions with products and services. For example, AI Chatbots can help in scheduling meetings, and setting up reminders.
- Data analysis: AI can help analyze user data and feedback to identify patterns and areas for improvement in UX. For example, AI tools can be used to help e-commerce sites predict what products a user might be interested in.
Different research has looked at the adoption and impact of AI among UX professionals.
For example, a survey targeting design professionals found that designers do not understand the limits, constraints, and challenges of AI on their work [1].
In addition, a survey of 46 designers from professionals from the creative industries revealed that most of the respondents (68.9%) predicted that AI technology would have a high or very high impact on their work.
However, this does not seem to be a cause for concern as most of those surveyed (86.6%) were either optimistic or neutral about the nature of this impact [2].
Other surveys have revealed that AI can help UX professionals with tedious and creative tasks [3]. Tedious tasks include helping users to go beyond their areas of expertise (e.g., with accessibility checking or internationalization tips) or doing design work (e.g., checking values such as color or spacing) [3]. Creative tasks include generating templates for specific types of screens (e.g. a prototypical “login screen”), and showing designers inspiration to continue in their process [3]. Similar research has found that AI facilitates designers’ work by helping in designing inspiration search, designing alternative exploration; designing system customization; and designing guideline violation check [4].
Overall, AI may have the potential to transform the way designers approach UX design, making UX design more personalized, intuitive, and efficient.
References:
[1] Graham Dove, Kim Halskov, Jodi Forlizzi, and John Zimmerman. 2017. UX Design Innovation: Challenges for Working with Machine Learning as a Design Material. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI’ 17). Association for Computing Machinery, New York, NY, USA, 278–288. https://doi.org/10.1145/3025453.3025739
[2] Main, Angus and Mick Grierson. “Guru, Partner, or Pencil Sharpener? Understanding Designers’ Attitudes Towards Intelligent Creativity Support Tools.” ArXiv abs/2007.04848 (2020).
[3] Tiffany Knearem, Mohammed Khwaja, Yuling Gao, Frank Bentley, and Clara E Kliman-Silver. 2023. Exploring the future of design tooling: The role of artificial intelligence in tools for user experience professionals. In Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems (CHI EA’ 23). Association for Computing Machinery, New York, NY, USA, Article 384, 1–6. https://doi.org/10.1145/3544549.3573874
[4] Yuwen Lu, Chengzhi Zhang, Iris Zhang, and Toby Jia-Jun Li. 2022. Bridging the Gap Between UX Practitioners’ Work Practices and AI-Enabled Design Support Tools. In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (CHI EA’ 22). Association for Computing Machinery, New York, NY, USA, Article 268, 1–7. https://doi.org/10.1145/3491101.3519809