How AI will Solve Your UX Design Problems which leads to Better Service Experiences?

Artificial Intelligence (or AI) is an advanced human-like computerized system that has the ability to intelligently manage the activities and systems which humans usually do manually.

AI is finding its application across multiple real-time scenarios:

• Handle data explosion – With the advent of smartphones and mobile devices, comes the explosion of data. As the amount of data grows, it is pertinent to have an AI system to analyze, process, organize, and interpret the data.
• The ability to decipher our intent – Intelligent systems can predict from your behavior what kind of TV show or movie will keep you glued to your sofa. Imagine if your AI system can adjust your car’s temperature and turn off the lights when you take your car out of the garage.
• Improving the customer experience – AI can dig deep into details which human eye could probably miss and help you focus on the right data.

AI is a combination of several nascent technologies- machine learning, deep learning, chat bots, augmented reality, virtual reality, robots- to name a few.

AI covers anything to do with infusing intelligence into machines/ devices so that they emulate the unique reasoning power of human beings. All of these can be accomplished by using algorithms that are capable of discovering human behavior patterns and generate insights from the data received and stored by the devices. Artificial Intelligence enabled devices or machines are programmed carefully so that they support in future decision-making.

AI is going mainstream with bots and robots fostering human-like interactions with the power of cognitive intelligence. However, robots cannot replace humans completely. Instead, AI nurtures fruitful collaboration in the domain of UX.

Use the power of predictive analytics to understand the online journey of users and map them into segments based on their behavior. The most powerful UX is the one that understands and even predicts user interests and actions.Once the designer is able to map a user’s journey, he can understand the paths a user is expected to travel in course of their digital interactions. AI-powered journey mapping allows you to create simple, engaging, and profitable UI.

Human designers should map out the ‘rules’ for how a layout should work and then provide the system with a library of raw graphic elements to work with and then capable of combining the rules with the image assets to create original movie poster and banner units.When AI handles such tasks, designers can focus more on understanding the user journey and refining these rules. It’s not unlike a scenario where a senior designer is directing a team of junior designers. Each benefits from the other.

AI technologies like machine learning empowers digital marketers for granular targeting.

How do you mold AI for a better UX?

AI systems have the ability to analyze large amounts of data quickly and also learn and adjust their behavior in real-time. AI systems can infer from the context and you need to supply them with additional information in the form of business rules, questions, metadata and similar other conditions.

As you work through each design phase to build a great user experience, you can constantly refine the questions that you ask your AI system. This will change the way it analyzes data.

For example, if you are managing a health insurance website, ask plain questions like:

• How many people between the age 40-60 use your application?
• How many expecting moms access the system?

The system takes your questions, analyzes the data and learns to throw up the best possible answers. Each time you feed a new data or criterion, the system conditions itself using AI technology to enhance your user experience.

The beauty of molding AI is:

• You can ask general to specific questions to your AI system. The system attends your questions, takes the data, and self-learns.
• AI can analyze all the queries made on your search engine, collect more user analytics, identify trends, and generate richer findings.
• Refine the quality of search results with data – AI can come up with better predictive search terms, provide recommendations, cross-topic referrals (similar to what Amazon offers), and bring more relevant content on top.
• Above all, AI learns from everyone who has visited your application till now and serves your users with needed content. This makes way for a richer user experience.
• Information Architecture with AI-AI analyzes both your internal and external data and helps you build information structure for your content management system and a navigation structure for your end users.

User experience is not necessarily about leveraging data insights, it’s about intelligence too. Artificial intelligence connects the dots by infusing intelligence into the disparate sources of data.

Though AI technologies like machine learning, chatbots, VR, robots, AR and other systems are gaining momentum, the growth seems to be gradual. AI, when combined with UX becomes the icon of the future technology. Merging AI with UX is a formula that should lead us to enhanced content findability and reachability.

SX is not an evolution of UX. It is a revolution of business and service design.

SX teams will develop independently from UX teams, combining business, engineering, and design

AI tools can provide tailored user experiences to everybody.

In the UX world, the impact of AI and automation is transforming the role of the designer, and presenting a new set of challenges and opportunities. Traditionally, UX teams would turn to metrics and tools such as usability tests, usage data and heat maps, to understand how to improve the functionality and effectiveness of a system. However, in the age of AI, we now have a myriad of empirical, actionable data that we’ve never been privy to before, giving us greater granularity into optimizing the user experience.

The user experience is fundamentally about one-to-one, human-to-computer interactions – one based around predicting how individuals would react to a set of structures or aesthetics. But with the advent of machine learning, businesses are adopting a more quantitative approach to UX, as more measurable data finds its way into the strategic decision making process. 

Artificial intelligence and UX: design decisions

The good news is that companies already have the information available to customize the user experience, and AI will simply enable businesses to effectively conduct quantitative usability testing. Information that UI can easily extrapolate include:

• User characteristics, such as a person’s location and job title
• Device from which the user is accessing the information – PC, Mac, tablet or mobile
• Session time and length, including the time of the day the user is accessing the application
• Source from where the user arrived at the application or website – such as a Google search, typing in a URL, or clicking on a link from another website
• User flows within the application
• Drop rates from this flow when using the application
• Screen recordings of any drops from user flows, to help analyze user behavior 
• Total number of users, unique visitors and sessions

It’s critical that the right set of solutions for UX teams – including guidance, tools, validations and mechanisms – can surface the right tools for an individual at the right time. This level of information is being acquired via AI. For example, if the data shows that a user – or a segment of users – previously failed to complete a specific form in an enterprise application, we automatically surface the guidance and tips at specific failure points to support this task completion.

Designing systems truly for the user

Artificial intelligence algorithms help make our jobs simpler and easier – and by taking advantage of AI to learn user behaviors, UX teams can quickly solve design problems to create models based on user preferences, and develop more personalized applications.

As businesses and users become more inclined to greater customization, it’s vital for designers to become data-savvy, and dive headfirst into scrutinizing the endless possibilities in engaging with any system. Ultimately, it’s this transition that is delivering a strategic business impact – whether it be through lower IT helpdesk queries from users, greater efficiency and accuracy, and overall productivity improvements.