Relating to users that sit at the opposite end of the tech adoption spectrum can be challenging for ‘edgy’ designers and developers — a community known for their speedy adoption of new technologies. Using methodologies stemming from UX research and design thinking, we sat down with late majority and laggard users, male and female of different age groups to delve into their perception and state of awareness regarding AI and define a successful approach to designing AI products.
Most users express mixed feelings about AI and yet, a big part of the tech discourse focuses on the cheerful side of it. We constantly hear about how ‘the future is AI’. Tech companies do their share by targeting mainly early adopters — heavily relying on their influence to drive potential adopters’ decision. This leaves the late majority left out of new developments in AI, despite inexperienced or non-techie users accounting for nearly 50% of the population according to Rogers’s popular theory on diffusion of innovations. And one may ask, why don’t we design for everyone? Shouldn’t that be part of our duty as UX designers and researchers? Why not target both eager AND reluctant adopters?
We wondered — what can we learn from late adopters to improve their experience? When average users imagine AI, what drives them and what holds them back? How can we go from resistance to thoughtful adoption? How can we turn fears into true cheers?
By understanding how people are exposed to AI in their daily lives and what the future of AI holds for users, we can design better suited solutions for today and tomorrow.
In conclusion, to create more valuable AI products it is essential to bring users to the center of the design process:
As innovators and early adopters are familiar with state-of-the-art technology, they are prone to judge the value of AI more positively. On the other hand, late majority and laggards are notably afraid of the ‘dark side’ of A.I and hidden implications.
When planning AI-based products targeted at these segments, designers and product developers must consider the following:
- Identify and address the users’ real pain points and provide solutions to enhance comfort, security and health: always be driven by what is actually needed versus what is technically possible.
- Give the end-control to users: they should have the option at all times to opt-out and turn off functionalities.
When developing brand new products users should have a place at the table to provide input and suggestions – no one knows better than them, regarding which aspects and functionalities will motivate and demotivate them.
The following must be taken in consideration:
- Make users aware of the gap between negative perceptions and real-life applications of AI: Knowledge is power, and users tend to be more positive towards products and services when they understand how do they work.
- Consider both efficiency and emotional response to decide on the suitability of AI applications: Being able to accomplish a task is equally important to feel safe, relaxed and in control while doing it; and both aspects need to be ‘handled with care’ when tweaking functionalities – a user may be able to understand and use an application but if they don’t feel positive using it they will hardly adopt it.
A top-notch design is nothing without a good launching strategy. Once the AI product is ready to hit the market, the following guidelines must be considered:
- Provide clear examples of how the product will help users to address pain points. Keep the functionalities real and concrete.
- Find the right tone of voice. Avoid jargon, and technical terminology - keep it natural so it can be seamlessly integrated into everyday life.
- Be careful to set the right expectations. Do not ‘overpromise’: users will feel cheated if they are promised a service that does not meet standards - trust is hard to earn but easy to lose!
- Be democratic. Late adopters and laggards do not feel as part of an ‘elite’ – they think of themselves as ‘average Joes’ and are comfortable with this. Therefore, their acceptance is higher when they acknowledge that ‘users like them’ have already incorporated the service or product.
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