There is very little to be said that can refute the idea of machines having made our lives easier. However, it is equally true that a quantum leap in digitalization was possible, majorly, due to a systematic and observant approach of enthusiasts to a dynamic evolutionary process. The merging of User Experience and Service Design with IoT, machine learning, AR/VR capabilities, robotics and automation has given a unique twist to the way AI is implemented in our daily lives.
Though there were a few attempts to automate the work of UX/UI designers through AI, the idea was soon found to be insignificant and the fact that ‘AI can never fully replace the need of a human touch in designing’ was established. One of the best examples of this was the failed attempt of websites designed and developed by The Grid, an AI platform that would develop site modules and website designs without the intervention of a UX Designer.
Having said that, it definitely doesn’t mean that AI and Service Design are not compatible or are a complete disaster together. Automation and AI has surely enhanced the proficiency of designers and helped them explore new horizons. Many new technologies have given the power to designers to overcome human limitations, as well as made their work a whole lot easier. Introducing AI in designs has been one of the biggest success of designers in recent years and it can be easily justified:
Constantly evolving and learning human behaviour
As service designers, AI gives the power to understand the behaviour and expectations of end-users through observational analysis and adaptation. Designers are able to gather data on exactly where the customer faces certain issues, or where their comfort zone lies. This helps in addressing the problems effectively. An example of this is Bitbar’s new AI test bot, that tests various mobile applications to ensure better usability so that UX designers can test apps more efficiently in shorter time periods and lesser investment.
Foresight and a long-term vision
The most important thing about AI is its data gathering capabilities in real-time and the power to analyse this data to provide usable reports. Instead of focus groups sessions and sample surveys, design engineers and market researchers get access to real-time market insights. This is propelling designers to have a better understanding of the customers’ needs and helping them come up with long-term solutions.
Helping overcome human disabilities
One of the major challenges of service designs is implementing systems that are user-friendly to the masses. This includes a wide range of demographics, including age, mentality, maturity, physical and mental disabilities, attention span and so on. AI gives the power to understand a person’s mind-set and adapt accordingly. This, in turn, means that designers get to overcome usability issues and provide a more generic solution that solves multiple issues. New age inventions like smartwatches and fitbits are changing the way people monitor their health, while voice recognition system’s like Apple’s Siri is helping disabled people to use their smartphones more effectively.
Personalization and human-like interaction
Automation at the base level for menial or recurring work is the gist of efficiency. AI-enabled chatbots are helping companies to reduce manual work, while increasing their customer interaction, and at the same time, making customers feel valued. Chatbots like Bold360 and Live Person are some great examples of this. In addition, Alexa and Google’s AlphaGo are providing customers with machines that show human-like thinking capabilities.
Making UI/UX work easier
Through all the support that AI provides through data analysis and customer interaction, it cannot be ignored how it is also making the work of designers easier and more efficient right at the ground-level. A few of the noteworthy ones are Adobe Sensei and Autodraw. Uizard is another useful tool that converts hand-drawn wireframe sketches into digital wireframes, thus saving a lot of time and efforts for designers.
In the coming years, it is predicted that Service design will be replaced with ‘System Designing’ or ‘Behavioural Designing’, that is more focused on feeding data to machines and developing AI Algorithms that determine behaviour patterns and parameters of automated systems. No matter how much advancements are made in AI, the need of service designers will always be necessary for optimizing the outcomes. In unison, the possibilities and opportunities of AI-enabled service designs seem to be endless.