For a long time, UX research moved slowly. We told ourselves that rigor took time, even when we spent most of that time watching recordings of which we already knew the outcomes or manually tagging participant quotations that all said roughly the same thing.

When stakeholders complained about our lack of speed, the answer was often: that’s just how research works. Then everything changed around us in ways that has impacted our work, as follows:

• Remote testing made it easier to run usability studies, but harder to keep up with the findings came out of them.
• Surveys got longer.
• Session replays multiplied.
• Support tickets became one of the richest sources of user insights, but also the easiest to ignore.
• Artificial intelligence (AI) arrived as a workaround. Someone turned on autotranscription and stopped dreading user interviews.
• Another researcher used a clustering tool just to see whether it could help, then realized that patterns had surfaced that they probably would’ve missed when tired on a Friday afternoon.

This article is about what’s already happening: AI is becoming embedded in UX research workflows, changing how teams prepare studies, connecting signals across data types, and deciding what’s worth acting on next. Read More

Every UX Design team experiences that moment when something feels off, users are clearly struggling, metrics are wobbling, and everyone quietly agrees there’s a problem. After a meeting, a few Jira tickets get reshuffled and the issue dissolves into the background. Not because it’s small, but because it’s uncomfortable. Such problems sit at the intersection of design, culture, and accountability, which makes them easy to acknowledge, but even easier to avoid.

The irony is that UX Design teams talk constantly about empathy, user centricity, and making evidence-based decisions. However, when ideas point toward a structural flaw in how work gets done, a team’s momentum often evaporates. The problem is not a lack of insight or talent. It’s the collective habit of treating certain design failures as inevitable rather than fixable. Read More

Artificial Intelligence (Al) is no longer just a futuristic idea. It is already in use in the applications that people use every day, from personal recommendations to filing for unemployment, checking the status of benefits, or renewing a driver’s license. By harnessing the power of AI, governments are helping citizens to access essential services such as healthcare, tax filing, legal aid, and documentation. But navigating government Web sites is often a complex, time-consuming, and frustrating experience for both government employees and citizen users.

Some government contact centers just aren’t yet where they need to be. Their development teams are often overwhelmed, with a never-ending backlog, juggling disconnected systems, and wasting time on repetitive tasks that AI could easily automate—for example, answering routine queries, sorting documents, or guiding users through filling out basic forms. Now that the public’s expectations are higher, it’s important for governments to avail themselves of the opportunity of using Al to improve their citizens’ lives, enhance accessibility, and grow their economy. Doing this can build trust in public services and improve service delivery. In this article, I’ll explore some key ways in which AI can enhance the user experience of government Web sites. Read More

In our fast-paced world, users who are adopting new software tools or trying a new Web site don’t want to waste their time on a long onboarding process. That’s why many Web-site owners are trying to find ways of engaging users. If you are thinking about adding a user-onboarding tool to a Web site, this article will guide you through the process. You’ll learn about the basics of user onboarding, its benefits, and strategies that can help increase user retention and grow a business.

What Is User Onboarding?

The process of onboarding users involves helping them easily understand the onboarding process once they’ve signed up for a product or service. An onboarding process typically includes a set of simple instructions, a short tour of the features, and step-by-step guidance. The main goal of user onboarding is to help users quickly see how a product can help them and encourage them to use the features of an app or tool. Companies such as Duolingo, Slack, and Notion use these simple walkthrough processes to prevent users from becoming confused. Read More

Artificial intelligence (AI) is fundamentally changing what UX designers design. For decades, UX design practice has centered on shaping user interfaces, focusing on workflows, layouts, interaction models, and information architectures. However, as generative AI is now beginning to produce wireframes, mockups, content, and even working code, the center of gravity of UX design work is shifting.

But take heart—this shift does not spell doom for the UX design profession. If anything, AI’s emergence is opening new avenues of creativity, reinforcing the underlying purpose of UX designers: We help organizations make better decisions about how technology should serve human needs. While this isn’t a new idea, AI is pushing this intent into frontiers that we’ve never explored before. In this column, I’ll explore these new frontiers, focusing on the following:

• shifting from user-interface design to designing decision-making
• defining the judgment layer
• manufacturing purposeful friction
• designing for probabilistic systems
• planning for composition in an era of interoperable systems
• ensuring AI decision-making remains visible
• reframing UX design as governance Read More

In 1967, psychologist Martin Seligman published an experiment that would reshape how researchers think about motivation, depression, and the relationship between actions and outcomes. When dogs that had been exposed to mild, inescapable electric shocks were later placed in a new environment where escape was straightforward—they simply had to step over a low barrier—they did not move. They had learned from their earlier inescapable predicament that their actions did not change outcomes, so they stopped acting.

Seligman called this phenomenon learned helplessness. Subsequent research has demonstrated that the same mechanism operates in humans across domains that range from education to workplace performance, as well as clinical depression. When people repeatedly experience situations where their actions have no effect on outcomes, they generalize their experience into a belief that action is futile. They stop trying, even when trying would work. Read More

Artificial intelligence (AI) doesn’t belong to the future anymore. It’s already becoming integral to how companies get work done. Finance teams use AI to spot patterns in huge datasets. Customer-support agents lean on AI to answer questions faster. Operations groups rely on AI to keep supply chains moving without constant human supervision.

Now a newer kind of AI, agentic AI, is taking things up another level. These agents aren’t tools that just blindly follow a script. You give them a goal, and they figure out the steps, change direction if the situation shifts, and keep pushing toward their outcome even when things get messy. That kind of independence delivers serious value. Businesses can automate processes that used to require whole teams. These agents cut wait times, handle way more data, and free people up for the work that actually needs human judgment. Read More

When you’re scaling a product, it’s important to attract and keep users for the right reasons. You want people to stay and share your app with others because they genuinely enjoy using your product. Or because it helps them solve a problem. Not because you hid the Cancel button or slipped an upgrade into their cart. Yeah, it happens.

Growth pressure can push some UX design teams to take shortcuts. They might bury settings. Or nudge people into autorenewals. Or, at the worst, guilt-trip users using popups. (This is an embarrassingly popular choice.) While these tricks might spike short-term numbers, they damage long-term user trust.

No company needs to do that. Companies can grow ethically and create transparency instead. When you design with the user in mind and are clear about what happens next, you earn better engagement and stronger loyalty from users. So, let’s take a closer look at the top UX design principles that can help a product grow in a healthy, ethical way. But first… Read More

In today’s digital landscape, the line between users getting helpful assistance or unwanted intrusions from their modern technology gadgets is becoming thinner than ever. Just imagine that you’re opening a fitness app at 6:00 am and you instantly receive a suggestion for a yoga routine. Or, while working in a design tool such as Figma, information automatically updates based on what you’ve selected. These things aren’t magic. This is context-based user-interface (UI) design.

Unlike traditional, static user interfaces, modern digital experiences reduce friction and improve the user’s efficiency by analyzing the user’s environment, behaviors, and intents in real time. Context-based UI design brings intelligence to design.

Many brands are now investing heavily in developing adaptive user experiences to improve user engagement and retention. Context-based UI design is no longer a differentiator; it’s becoming the foundation for modern user experience design. In this article, I’ll explore how brands can make use of context-based UI design as a powerful driver of user retention through balanced user control. Read More