1. Subscription-based models will soar
“From the cars we drive to the content we consume, digital services like Uber, Airbnb, and Netflix have made us less likely to own things and more likely to pay for access to them. Ownership is seen traditionally as a status symbol. But we’re seeing consumer attitudes shift as technology has made the subscription model cheaper and more accessible.
Movements such as The Minimalists and the subscription economy reflect user desire to have more flexibility, choice, and customization when it comes to product consumption – all on-demand and for finite periods of time. Video and music streaming services have offered this type of model for years, and now we are seeing clothes and food-based subscription services becoming more widely used, and even preferred.
This shift is a sign that in the near future we’ll see this trend move into more difficult sectors (such as finance, education, and government) as subscriptions drive customer retention by adapting to changing user preferences.”
-Kim Turley, Director of Technology, Beyond New York
2. Continued adoption of voice-driven interfaces
“2017 was a big year for voice-driven user interfaces, driven by the popularity of smart speakers like Amazon’s Alexa and the Google Home; Apple, too, has a horse in the race with Siri getting in the smart speaker game this year with the HomePod. With the major players all vying for a piece of the pie – paired with a greater consumer appetite for the convenience of voice control – in 2018 stands to see a strong uptick both in the number of available smart speakers and the power of the AI assistants that fuel them.”
-Jarrod Tredway, Client Strategist, Beyond Austin
3. UX will play a pivotal role with machine learning
“UX, and specifically the skillsets of UX experts, will play an increasingly important role in machine learning in 2018. When communicating machine learning complexity, a UX mindset is vital to articulate mathematical models and algorithms in a simple manner.
Similarly, think about the visualisations, dashboards, and other types of interfaces that’ll need to be created to untangle the ‘black boxes’ of deep-learning, automated decision-making. Researchers at Columbia University and Lehigh University are already exploring this with their tool DeepXplore. Their aim: Ensure machine logic outcomes are accurate, fair, reliable, and transparent.
What’s more, UX will be valuable in determining marketable use cases where AI can thrive using innovation methodologies and design thinking techniques. I mean, who wouldn’t want an AI-powered cocktail maker at their party, right?”
-Andy Shanley, Director of Experience Design, Beyond New York
4. AI will unlock creativity – and jobs
“As the focus around AI sharpens, we’re set to see the evolution of established job roles and the genesis of some new ones.
AI is already automating some of our mundane administrative tasks, and the combination of man and machine will signal a new era of creativity. By doing the heavy lifting, technology will free up our cognitive capacity for creative thinking and high-level problem solving.
But before the era of blended man and machine workforces hits the mainstream, enter a new breed of workers: the Trainer and the Explainer. The Trainer will be an integral part of tech-forward companies, coaching their bots and algorithms, and the Explainer will coach the C-suite on what exactly is going on – and we shouldn’t underestimate the significance of this role.
We’re predicting a new partnership, which will define the creative landscape, and a host of indispensable jobs that will usher in this new way of working.”
-Charlie Lyons, General Manager, Beyond London
5. More systematic analysis of qualitative research
“We’re predicting a rise in more systematic analyses of qualitative research.
New tools are already emerging that streamline the analysis of interview and focus group data. For example, one of our clients has a custom database of user research videos, marked with content tags and participant demographics. As such, you can query the database and say, “I want to see video clips of men, age 25-34, who experienced issue X during testing” and it will pull every relevant clip.
Similarly, user research platform, Optimal Workshop, recently released a note-taking tool for interviews called Reframer that supports tagging and tag analysis so you can run basic data analysis or tabulations once your notes are tagged.
Ultimately, the next logical extension is using machine learning or AI to parse qualitative research videos and recordings.”