September 3, 2020
Making an impression and impact with memorable user experiences has become an essential component of any service offering. There’s no doubt that AI today has a huge potential in enhancing user experience and improve our everyday lives as it did right from the first computer chess-playing program to driverless cars and smart personal assistants.
Machine learning and artificial intelligence, which have demonstrated enormous potential in improving the customer experience, are now being used by businesses to enhance user experiences. Nonetheless, AI plays a vital role in various sectors like healthcare, where it powers genetic testing and computer vision, and in financial sectors, where AI aids in risk assessment, fraud detection and also eases and automates government services.
On that note, it is soon that the use of AI has been welcomed by the UI/UX designers. According to a recent Adobe study, 62% of UI/UX designers are enchanted with Artificial Intelligence and are keen to savor the flavor that it would offer to the creative process. AI-included designs are known to improve the creative process and create a new level of relationship with an excellent customer experience. Many prominent minds have pointed to the ML-based algorithms that are applied to create AI UX design, which promises to provide a new level of digital experience for the designs.
“If AI is your exciting new friend taking you on a day out, then UX is the longstanding BFF who will make sure you all get home safely and securely.”
The rise of artificial intelligence and machine learning use cases has influenced not just end-users but has also increased the bar on overall experience and efficiency. AI-powered designs bring the client experience and Artificial Intelligence to a whole new level. User-friendliness is a significant component for organizations that need to promote brands and raise revenues, and thus these designs garner a lot of attention. On that note, let’s delve a little further…
Most of the time, the UX teams collect the user preference data and implement them into the design by adopting various tests like A/B tests, data usage, usability tests, and heat maps to enhance user engagement in their products. Now, with AI coming into play, these methods are on the verge of extinction as AI can collect and analyze huge blocks of data and suggest practical ways to enhancing user experience and draw sales. The real deal of involving AI is not only about collecting the data but lies in the way AI makes use of the data.
For instance, with the help of AI, an e-commerce store can keep track of user behavior across multiple platforms and analyze the data of its visitors along with their preferences. This will eventually generate more leads and increase sales. Furthermore, the designers get to improve and customize the UI/UX design according to user specifications based on the data analysis.
Information Architecture along with AI plays a vital role in getting the required user information from a large amount of data. AI using Information Architecture, can connect to the user interface and provide required content tagging based on user relevance.
This step simply means that the search for any information can be made more targeted, easily available, and cross-linked between the different interfaces. This is achieved by the means of AI creating a relationship between the data. Cross-linking data in this manner helps organizations to focus on the requirements of the end-users and gather effective results by enabling an interface to steer through huge amounts of data.
In the current phase, AI has slowly become a common occurrence in everyday life with the development of smart homes, automatic cars, and other controlled devices. Along with this exponential growth arises a fear from the fact that machines might take over the world and the tech users may lose control over it. In Spite of this it is necessary to acknowledge that as AI advances, users will have the opportunity to achieve more control over systems, gradually enhancing trust which will lead to more usage.
AI gets to create a deep connection with humans as the AI systems collect and analyze a huge amount of user data. This approach equips them for a more personal connection with the human and performs functions like a true personal assistant. Well, we must however agree to the fact that machines know and predict the user’s requirements just like how we experience it daily through digital assistants, personal smartphones, and more.
AI user experience adoption is taking up more innovative ways as the user benefits are extensive including scheduling meetings, shopping, browsing the internet, booking flights, and much more. The super predictive algorithm of Netflix, friendly-voiced and amazing personal AI assistants are cases of AI where it collects your data, learns about you, and provides improved AI user experience.
Believe it or not, UX can help one to focus on the AI user experience opportunities that will help businesses to grow with the best custom software development and services. It again works with the simple principle of putting your user at the heart of the process. This means developing experiences that put their interests first, protect their data, and ensure the best interaction with them that includes integrity and authenticity.
Opportunities To Automate: Anything that takes less than five seconds to compute can be considered for automation. Making use of user-centered design (UCD) helps to research user behavior and service design blueprints help to identify the points in your customer journeys where AI can improve the experience.
Get Data Together: To deliver and measure the best AI impact, it has to be implemented with proper data science, data collection, and data cleansing.
Personalize The Experience: AI can connect the dots for your customers. For example, in an app, if one hasn’t logged in to check for a while but makes an inquiry regarding it over the phone, then the system can be designed to make content and feature suggestions to the user based on that behavior. In short, UX can exhibit common-sense applications for AI.
Add Value: Using API-driven design can add value with chatbots and personal assistants to access the products and other customized services. All that is required to add value is to carefully plan AI implementation.
Practice What Is Right: As product and UX designers, one can use various AI assistant tools to augment transcripts. AI can even generate code in real-time using TensorFlow machine learning blended with computer vision image recognition.
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On getting the principles straight, the next step is to implement AI in a way that’s strategic, thoughtful, ethical, robust, and user-centered.
Lead projects: Start small, partner with software engineers who have experience using AI frameworks, learn and experiment to gain momentum. Also, use short sprints to drive success.
Build Your AI Team: Build your internal team for AI and provide broad AI training for the team so that your colleagues are well trained on AI and also understand its capability.
Research: Hold a service design workshop to establish the core product – user journeys, touchpoints, initial UI design elements, and data flow. Evaluate any risks that can or may occur. Human bias, for example, can be replicated and even amplified by AI and UX designers are primed for this specification of work.
Framework: Make use of software or frameworks that ensures compatibility and support (Azure/AWS).
Analysis: Conduct a regular audit and gap analysis of data and existing systems and design your data warehouse to cover ingestion, storage, processing, analytics, output, and how data is processed by the application.
Regular Reviews: The final step is to monitor AI and to ensure that it’s providing the perfect value. Review your workflows each week and then tweak, test, and adapt your experiences.
Consumers today are ecstatic, and one can safely assume that AI and machine learning are indeed responsible for refining and enhancing user experience. According to an IDC study, organizations that use sophisticated technology such as AI, ML and predictive analysis to boost their success rate by 65 % are predicted to outperform those that use traditional technologies.
The expansion of AI and machine learning in the UX sector is unquestionably in the cards. This is because any organization with the resources to use data to their advantage will not leave any loose ends as this will enable them to stay ahead of the competition in the industry and market space. The AI and its working potentially save time, give better insights, and guide one towards better decisions. Now, the combination of AI UX design puts every customer at the center of designed experiences and helps to handle any problem areas or elements in an AI user experience.
With a topic as vast and intricate as AI, there is indeed a lot to cover. Artificial intelligence is bringing a fresh perspective on how consumers and companies now see AI user experience. Without a doubt, there is no other technology that can improve UX as much as AI, and that is the truth. Enhancing user experience and design trends will continue to evolve over time. AI & UX together will provide more close engagement, specific contexts, quicker processing, innovative insights, and more intuitive interfaces.
So What do you think? Can artificial intelligence dominate the future of UX design?
It improves the usability of digital interfaces and UX processes. Spanning from data analysis, and design outputs to enhancing the user experience, AI is impacting the UX design to a great extent.
No! AI will not take over UX design, instead will provide new opportunities in this arena where designers can successfully help in enhancing user experience with stunning design elements.
Presently in practice, before developing any product there’s always a design layout or blueprint that helps in effective product build. Now, when the designers are all set for a designer-developer handoff what goes in and out makes a big difference.
An application that trails a smooth journey to its user gets into their wish list with ease. For an app to incorporate the complete UI UX design elements ability, the start (i.e ideas) should encounter research and analysis by the design experts.