How AI is Revolutionizing Application Development and User Experience Design
By Anoop Kumar P
Artificial Intelligence has disrupted the way humans interact with technology. At the front end of development, AI helps create an engaging user experience (UX). According to Gartner, by 2027, chatbots will become the primary customer service channel for roughly a quarter of organizations. At the back end, with AI-powered tools aiding the development workflow and data management, it is an important ally that helps streamline processes, enhances analytical capabilities, and makes it more secure. AI can drive industry-level innovations in experiences, platforms, capabilities, and even open-source applications and create the next-generation customer journey of highly interactive and immersive experiences.
The Use of AI in UX design and its Benefits
AI automates repetitive tasks, provides personalization, and improves user interface by amplifying experience, capabilities, and engineering functions. Machine Learning (ML) algorithms and AI-powered design tools help sift through colossal amounts of data in real time to provide insights that help understand customers better and suggest design improvements. AI optimizes the development lifecycle, enhancing efficiency and reducing time-to-market. There are several dimensions where AI can contribute to building better UX designs. AI can collect and streamline raw thoughts and requirements from stakeholders and analyse experiences to generate user stories and product concepts. Innovations in prompt engineering are helping inspire better AI-powered designs.
AI makes existing content valuable by discovering untapped potentials that can be combined with robotic content generation to add significant value across various facets, such as marketing campaigns, customer communications, creating brand websites, and generating legal or contractual documents.
Next, AI brings task automation to a new level by enabling intelligent business assistants that comprehend the context and provide optimal data for decision-making by consolidating traditional and modern decision-making mechanisms. This is evident in areas like sales assistance, service assistance, field assistance, audit and inspection assistance, and domain virtual agents. A business advisory experience design that co-exists with every workflow will become a key consideration.
Thirdly, AI enhances customer service through Natural Language Processing (NLP) powered interactions, personalizing customer experiences, sentiment awareness, and providing personalized recommendations. This allows for a better understanding of customer intent and helps resolve issues more effectively through self-service bots, chatbots, in-app assistance, FAQ engines, and Q&A engines. Conversational experience design will become an innovative area to embody intuitive concepts.
Lastly, AI creates delightful interactions by offering a more acceptable avenue for accessibility, support, simplicity, and data-intensive interactions. This innovative approach may lead to the development of single-touch apps that understand user intents more accurately. The combination of voice, image, and video with enterprise data can create AR/VR synthetic environments more effectively with hyper-personalized avatars. Innovative content mashups with enhanced creativity will elevate experiences to an unprecedented level, apparent in interactive and personalized learning, accessible education, and voice and image-centric interactions.
Challenges in AI adoption
As with any new and emerging technology, the primary concerns with AI are security and privacy. Given that AI systems depend on sensitive and personal data, steps such as data anonymization, security in storage, and compliance, must be taken to alleviate privacy concerns. The high cost and resource consumption of AI systems is another challenge. AI demands extensive processing power, and with companies needing to meet ESG considerations, this is a huge concern. With the AI landscape constantly shifting, the velocity of application development and trainability are areas of concern. AI algorithms often inherit existing biases, resulting in discriminatory decisions, and creating ethical issues that must be addressed. Lastly, several industries are bogged down with legacy systems, and therefore, integrating complex AI models into these outdated systems is a major hurdle.
The future is about humanized experience
AI must create empathetic experiences, as customers understand products that have a human-centred design. There are two components to creating humanized experiences. First is experience design, where the focus is on end-user experience, real-time monitoring of how humans engage with systems, what they look at, how they select products, claim a loyalty bonus, deal with issues, amongst other things, and apply a hyper-personalization brand strategy. The second component involves adopting a holistic business approach, where AI tools craft the screens based on customer requirements to create prototypes. AI becomes a strategic co-pilot to address the most pressing operational challenges and has a tangible impact on business performance.
AI is indispensable to daily operations and is changing application development and UX design. With time, as AI tools become more sophisticated and augment design capabilities, UX designs will be crucial to retain a humanized perspective on the design process.
Author:
Anoop Kumar P is an Associate Vice President at Infosys and is part of the Digital Experience practice. He has 28 years of experience in the industry and has been a veteran in the digital transformation landscape. He currently works on AI-led digital experience initiatives and solutions and leads the architecture community, and the views expressed in this article are his own
