What is human-centered design, really?

Human-centered design isn’t just a buzzword—it’s a methodology rooted in empathy, context, and iteration. As Sara explained:

“Human-centered design puts humans—people—at the center of the process. You’re interviewing them, understanding their challenges, motivations, and frustrations. You define the problem based on real needs before you ever touch a prototype.”

IDEO defines human-centered design as a creative approach to problem-solving that starts with people and ends with innovative solutions that are tailor-made to suit their needs.

In their Field Guide to Human Centered Design, they say, “When you understand the people you’re trying to reach—and then design from their perspective—not only will you arrive at unexpected answers, but you’ll come up with ideas that they’ll embrace.”

According to McKinsey’s The Business Value of Design report, companies in the top quartile of their Design Index saw 32% higher revenue growth and 56% greater total returns to shareholders over five years compared to industry averages. 

High-performing companies treat human-led UX as a strategic discipline, not an executional afterthought. They embed designers early, validate with real users through usability testing, and use design metrics alongside business KPIs.

The goal is simple: solve real problems for real people. But simple doesn't mean easy. Discovery research takes time. Recruiting participants, planning studies, synthesizing insights—all of this can stretch timelines and strain stakeholder patience.

And that’s where AI enters the picture.

How AI is reshaping UX research (but not replacing it)

AI can accelerate a lot of what slows research teams down. Summarizing transcripts, analyzing themes, even automating aspects of user research logistics are all on the table.

Sara explained how AI gives UX teams breathing room, “Stuff that used to take a really long time—like recruiting or setting up research plans—can now be much faster because of AI. But you still need a human talking to another human, drawing out the nuance in the conversation.”

This isn’t about replacing researchers. It’s about removing friction from the research process so teams can spend more time uncovering real insights—and communicating those insights effectively to the business.

That’s where the role of empathy comes in. AI can highlight patterns, but it can’t understand the deeper “why” behind human behaviors. It can’t build trust with stakeholders. And it certainly can’t craft a compelling narrative that gets people aligned around a customer problem worth solving.

Simulated or synthetic users are not a shortcut to empathy

AI-simulated users—sometimes referred to as synthetic users—have stirred up plenty of debate in UX circles (listen to this episode with John Whalen and Lija Hogan as they take on this topic). Used well, they can simulate how a certain persona might react to a product change. Used poorly, they risk replacing real voices with statistical noise.

Sara sees a place for these tools, if they’re grounded in actual research:

“If you've already done a lot of qualitative research and you're feeding that data into a synthetic user model, it can be really powerful,” she said. “But don’t use them to explore new ideas or try to uncover real problems. That’s where you need to talk to actual humans.”

In other words, simulated users can support design work, but they can’t replace qualitative insights that come from real conversations. And when it comes to customer experience innovation, those insights are the foundation of everything.

Stakeholder buy-in starts with speaking their language

One of the most actionable takeaways from the episode came when Sara explained how she used to pitch human-centered design early in her career—and why it didn’t work.

“I used to talk about the process, the personas, the journey maps. And I realized stakeholders don’t care about those things,” she said. “They care about business outcomes—customer churn, conversion rates, growth.”

Getting stakeholder buy-in requires UX professionals to shift from designer-speak to business-speak. That means:

1. Dropping jargon in favor of clear, outcome-focused language
2. Asking questions to uncover stakeholder pain points
3. Framing research as a way to reduce risk and uncover hidden opportunities

Most importantly, Sara emphasized the importance of building trust over time. “Start with small projects, show value, be responsive. Once they trust you, they'll give you more room to lead.”

The ROI of UX: using AI to show value, not just speed

A key theme of the episode was the tension between efficiency and impact. UX teams that leverage AI to move faster can’t just report speed—they need to show business value.

Sara shared an example where one of her designers measured how much time AI saved on a discovery project—around 40 hours—and then used that time to engage stakeholders in deeper, more actionable work.

“If you save a week of work and use it to run workshops or integrate findings into strategy, now you’ve shown that you’re not just faster—you’re more valuable.”

The takeaway? Don’t just tell your boss you finished early. Show what you did with that extra time and how it drives real outcomes. AI in UX research can create “found time,” but what you do with it is what matters most.

The future of UX is strategic and soft-skilled

For up-and-coming designers, Sara offered practical advice: focus on business acumen and soft skills. The bar for UX design execution remains high, but success increasingly depends on communication, strategy, and empathy.

Here’s how she broke it down:

• Business acumen: Know how to tie design work to key metrics and business goals
• Empathy & emotional intelligence: Be able to read the room and adjust your message
• Storytelling: Translate research into compelling, actionable narratives
• Stakeholder management: Build relationships and advocate effectively across functions

As Sara put it, “We’ve focused on hard skills for a long time; how beautiful the screens are, how easy the flows are. But now, soft skills are how you stand out.”

This perspective is especially valuable as many teams face uncertainty around AI’s impact on UX careers. Rather than resisting change, Sara encourages designers to embrace the tools, automate the tedious, and invest in what AI can’t do.

Human-centered design is more important than ever

Sara is optimistic about the future of UX, but she’s also realistic. Teams will need to become more strategic, more fluent in business, and more comfortable with change. But the core of great design hasn’t changed: understand people, solve problems, and communicate value.

That’s why human-centered design still wins—even in an AI-powered world.

“There are only going to be more interactions with technology,” she said. “And someone has to be the bridge between those systems and the humans using them. That’s what we do. That’s what UX is.”

Episode links: 

• Sara Fortier on LinkedIn
• Outwitly website
• Outwitly Academy
• Design Research Mastery Book - Preorders
• Nathan Isaacs on LinkedIn
• Success through human‑centered design — This on‑demand webinar explores how embracing human‑centered design helps tackle common design challenges.
• Reducing design rework with feedback — This on‑demand webinar discusses embedding customer feedback early to reduce costly rework.
• From insights to impact: making research stick — This on‑demand webinar focuses on structuring insights, storytelling, and using tools (including AI) to make research stick.
• The UX research methodology guidebook — a foundational guide covering attitudinal and behavioral research, methods, and when to use which approach.
• The ultimate guide to user‑centric product design — looks at how designers can build around human insight throughout product development.
• The complete guide to user interviews — deep dive on how to plan, run, and analyze interviews as part of qualitative research.
• Using AI to streamline and elevate UX research — This podcast episode discusses generative AI’s role in UX research workflows (analysis, storytelling, speed) with Google’s Alita Kendrick.
• Exploring AI in experience research — This podcast episode covers potential, risks, and the role of humans in experience research with UserTesting’s Chief Scientist.
• Rethinking UX with the Many Wizards of Oz approach — This podcast episode about adapting research methods to AI-driven experiences.
• Design’s critical role in AI products: Insights from Figma — This podcast episode explores how design evolves in AI product contexts.
• Why human‑centered design is your core product strategy — This blog post argues that prioritizing human‑centered design is essential for product success and efficiency.