Integrating UX Design Principles in AI-Driven Systems: Enhancing User Experience in Emerging Technologies

The paper proposes a comprehensive methodology for integrating UX design principles into AI-driven systems to enhance user experience in emerging technologies. The approach emphasizes a user-centered, iterative development process that incorporates advanced prototyping tools, continuous feedback loops, and collaboration between UX designers and AI developers. By focusing on refining user interfaces through detailed analysis of user interactions and behavior, the proposed methodology ensures that AI systems are not only functional but also intuitive and accessible. Key elements include leveraging machine learning models for personalization, utilizing natural language processing to enhance communication, and implementing recommendation systems that align closely with user needs and preferences. Data from external APIs, historical records, and real-time user behavior further support the AI engine in making informed, user-centric decisions. Continuous feedback mechanisms play a pivotal role in refining both AI algorithms and UX components, allowing the system to adapt dynamically to user feedback and evolving requirements. This methodology aims to bridge the gap between advanced AI capabilities and user-friendly design, ultimately driving higher user engagement, satisfaction, and trust in AI-driven systems.

Authors

Publication Details

Journal
Panamerican mathematical journal.
Published
2024-11-21
DOI
https://doi.org/10.52783/pmj.v35.i2s.2416
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.00
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article

Integrating UX Design Principles in AI-Driven Systems: Enhancing User Experience in Emerging Technologies

Prasad Raghunath Mutkule
Panamerican mathematical journal.
Digital Transformation in Industry
article

Integrating UX Design Principles in AI-Driven Systems: Enhancing User Experience in Emerging Technologies

Prasad Raghunath Mutkule
article en

Abstract

The paper proposes a comprehensive methodology for integrating UX design principles into AI-driven systems to enhance user experience in emerging technologies. The approach emphasizes a user-centered, iterative development process that incorporates advanced prototyping tools, continuous feedback loops, and collaboration between UX designers and AI developers. By focusing on refining user interfaces through detailed analysis of user interactions and behavior, the proposed methodology ensures that AI systems are not only functional but also intuitive and accessible. Key elements include leveraging machine learning models for personalization, utilizing natural language processing to enhance communication, and implementing recommendation systems that align closely with user needs and preferences. Data from external APIs, historical records, and real-time user behavior further support the AI engine in making informed, user-centric decisions. Continuous feedback mechanisms play a pivotal role in refining both AI algorithms and UX components, allowing the system to adapt dynamically to user feedback and evolving requirements. This methodology aims to bridge the gap between advanced AI capabilities and user-friendly design, ultimately driving higher user engagement, satisfaction, and trust in AI-driven systems.

Panamerican mathematical journal.Vol. 35(2s)
Openalex Percentile: Top 61%
Digital Transformation in Industry
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