The State of AI in UX/UI Design at Adobe

Picture an artificial intelligence-powered “assistant” working in step with a designer to get the job done — to find that perfect image, crop it, retouch it, and keep tabs on its future performance to ensure it’s moving the needle in its latest campaign. And while all this is happening, the human designer has the bandwidth to tackle bigger, more nuanced projects that drive his vision — and his company — forward.

That’s where we’re heading, writes Rubens Cantuni, a member of the UX Collective. Rubens envisions a future where AI designers “will work as smart assistants of human ones,” he says. “They’ll be powerful tools designers will learn to master and use at their advantage… [They will] add value to your profile as a design consultant and innovator and delegate to bots all the boring tasks of your day to day.”

UX and UI designers are increasingly aware of AI’s potential to improve their overall productivity and capabilities — and they want in.

The vast majority of creatives report spending more than half of their time on repetitive, uninspiring, or administrative tasks. Now, they’re seeing these tasks as the perfect to-dos for their future AI sidekick.

Understanding artificial intelligence versus augmented intelligence

This shift clears the way for AI to streamline and simplify the UI and UX design process for online interfaces and experiences. Adobe is already leading the charge, using Adobe Sensei to eliminate tedious tasks from designers’ workflows, free them up for truly creative pursuits, and maximize their ability to deliver powerful digital experiences.

The following are just a sampling of the ways Adobe is applying AI to give UI and UX designers the experiences they need to have more time to create and produce more effective customer interactions.

1. Tedium-less design workflows

The modern design workflow is still bogged down by inevitable moments of manual nipping and tucking. A designer can lose precious time recoloring, resizing, or cropping photos or shifting and adjusting different elements to find just the right layout. This wasted time is then multiplied as designers are asked to repeat this process over dozens of pieces — for instance, to create different-sized versions of the same image to fit various screen sizes.

This is where the Adobe Sensei-powered Content Aware Layout feature comes to the rescue. Using layout heuristics and built-in common design rules, it reads the content the designer has chosen for the design and automatically maps layout positions and text placement in Adobe Spark and Photoshop.

The Smart Crop feature, found in Adobe Experience Manager and After Effects, can sense the focal point of images, video, or text in a design and then intelligently crop and resize them to fit a desktop, tablet, or mobile screen — a feature that saves designers from mind-numbing tedium, but also drastically reduces image file sizes and page load times.

2. Integrate the ultimate creative collaborator

Similarly, Adobe Sensei has been put to good use in InDesign’s Content Aware Fit feature, which identifies the most important content on the page to keep in the designers’ predetermined frame, while resizing or cropping other content. No matter how content is adjusted, the proportions of the frame remain the same.

Adobe Experience Manager Sites leverages Adobe Sensei to match experience fragments that have been created using audience segment preference data to achieve desired KPIs. The Smart Layout feature enables brands to segment customers into various personas, creating the most effective layouts and best assets for those specific audiences. Creatives or marketers can, then, determine what they want to optimize for — social shares, for example, or mobile engagement — and the system runs A/B tests, optimizing the experience based on results.

This process, though, requires a significant number of digital assets to support the numerous platforms and personas — enter Adobe Experience Manager Assets. This AI-enabled digital asset management system (DAM) enables brands to organize, tag, and disseminate assets across their organization.

By automating tedious tasks — and ensuring the right assets get to the right spots in the customer journey — an AI-enabled DAM system enhances customer experiences and drives ROI. Experience Manager Assets leverages Adobe Sensei, and has been proven to accelerate the creation of assets by 47% and the campaign launches by 20% — definitely a creative collaborator any designer would want on their side.

In these scenarios, AI reduces the workflow of a few dozen manual steps down to just a handful and saves the designer hours — and no small amount of sanity. It can solve complex challenges, pick up where we left off, and catch things we may have missed.

3. Maximizing design effectiveness

Beyond design production workflows, UI and UX designers thrive on real-world feedback. It has the power to help them improve their craft and arrive at an optimized interface. Unfortunately, that feedback often comes in the form of anecdotes, rather than reliable data, and it is often delayed in its delivery.

AI, on the other hand, can analyze customer behavior data and make changes to UI and content in real time. In Adobe Target, Adobe Sensei powers the Auto Target feature, which automatically identifies those design elements that are most effective for each individual customer — and provides a data-driven source of constant improvement for designers.

Auto Target enables UI and UX designers to target multiple winners to individuals that adapt over time as each visitor’s interests change. Using an ensemble algorithm method and multiple machine-learning models, this feature results in one-click personalization for the whole site experience, not just a single banner or offer.

Ultimately, this AI-driven feature enables UI and UX designers to be absolutely confident in the effectiveness of their designs to deliver better CX.

4. Data visualizations in real time

Designing compelling graphs or charts to illustrate key data points has traditionally required a time-consuming back-and-forth process that starts with the data, converts it into a graphic, and then tweaks the resulting design according to designer and client feedback.

Adobe is developing a technology called Project Lincoln, which would enable the creation of these types of data visualizations with just a few clicks. However, unlike typical data visualizations, Project Lincoln users would start by designing a graphic and then tie data to it versus starting with data and creating a graphic to match. This “flipped” approach allows for much faster and easier customization of visual data representations — visualizations that help democratize data by making it simple, visual, and easier to act on.

The flexibility of a tool that can be used by non-analysts allows for an explosion of creativity, an ongoing parade of marketing insights, and more informed decision-making across levels and areas of the business. These changes lead to increased ROI, and better customer relationships.

Additionally, with the rapid efficiency of machine learning producing insights and predictions, executives are better able to make more complex decisions that yield favorable outcomes, and have better predictive capabilities to anticipate future changes.

Already, though, Adobe is using AI to improve and accelerate CX-enhancing data visualization creation. Fitness brand Equinox uses similar features in Adobe XD to capture and visualize all personalized activity data for each member to highlight their fitness performance and habits — for example, the member’s favorite time of day to work out. It’s a personalized, value-added design experience that Equinox’s customers have come to look forward to — and one that would be virtually impossible without the help of AI.

Putting intelligent design to the test

Armed with these kinds of AI-driven tools, more than three out of five designers see a dramatically improved future ahead, according to the Pfeiffer Report on creativity. For them, AI is also opening the door to other more prohibitively difficult creative work, such as coding, AR/VR, 3D, motion graphics, and video.

Far from taking over creative jobs, the partnership with AI is expanding UI and UX designers’ horizons more than ever before.

Read about more ways to integrate AI and machine learning into your creative and design processes.