28 APR 2025 | 10 min read

I am as amazed and intrigued and cautious as anyone by how quickly these tools have democratized some degree of creative expression. Today, anyone who wants an illustration to help express an idea can prompt a generative AI tool for a mockup. The tool will render in moments something that might pass as professional grade—emphasis on “might.” If we don’t like it, we can ask for modifications: make it look more retro, incorporate typography. This is output that until very recently has been the domain of veteran creators—among them top design professionals who have devoted years to studying and honing their craft.

The speed with which generative AI can create shiny artifacts leads some to question the value of the design function, resurfacing tired misperceptions of design’s value (or lack thereof) in the first place. Lately, the conversation has been taken captive by loud narratives that center on efficiency. Wall Street and venture capital firms ask how leadership will tighten belts to navigate the forest of ambiguity that grows wider and darker with every new generative AI model release: If generative AI is engineering-led, why should we continue to invest in design? Unfortunately, in the past 24 months I’ve watched some of the most incredible in-house design studios and agencies fall victim to such thinking.

If creativity is on trial, I believe it’s at least in part because of proximity to power. The value of a company’s design and creative function is far more than sharpening PowerPoint presentations. The often-hidden value is in helping leaders look at the distant time horizon and start to see around corners. Design has an important hand in shaping new futures that could be potentially realized. In my work, I’ve seen firsthand how executives react when they embed into the creative process with talented design professionals. They see how designers’ ability to uncover human truths and pinpoint the problems that need solving can be a compass for innovation.

One of the ongoing narratives about AI is the expectation that it will free up people—knowledge workers in particular—to make higher-level contributions and do way more with their creative energy. I suggest that’s exactly the kind of latitude your creative teams need to help catalyze innovation for your company.

Now, for the record—and this may even make some of my designer friends shudder—I’m not dismissing generative AI as a design tool. There’s no argument that it represents a paradigm shift. We all should understand it and learn to work with it. My stance is that generative outputs are non-deterministic and still require a human in the loop to steer the iterations for the better. It’s always a catch-22: Do I keep prompting, or do I make the sketch myself with my No. 2 pencil? I think for the task-focused aspects of professional design work, it will be this way for a while.

I also believe that when spending on design comes under the microscope, it’s often accompanied by a myopic view that ignores the broader design skillset. Beyond the output of artifacts, design is an approach to problem-solving—to excavating the uniquely human experiences that lead our customers into what I call “moments of truth.” That’s a lot different than stepping into line within a brand’s marketing funnel. In those moments of truth, we have an opportunity to connect with our audiences, serve them and build relationships with them. Novel ideas for doing so simply can’t come from data and predictive models alone. They require different ways of working. That’s fertile ground for the application of the broader design skillset and frameworks, even in the era of generative AI.

In terms of fertile ground, there may be none more mainstream right now than the obesity epidemic and the profound impact of GLP-1 agonist medications. For those who can tolerate the medications, they have proven to offer some utility as weight-loss tools—particularly because they curb peoples’ appetites. But there’s a catch: Once someone stops injecting the medications, appetites return, and the weight often comes back.

As with generative AI tools, I’m not dismissing GLP-1s. But I’m calling out the point that they’re a tool. The meds suppress human behaviors that can lead to weight gain, but they don’t necessarily change them.

I am working with a biotech client on a different approach to weight management, which I share not to suggest as an apples-to-apples comparison, but to highlight how we’re looking at the problem through a design-led, human-centered lens.

My client makes a device that records biomarkers found in the human breath. By exhaling into the device each morning, a customer can get insights into the performance of their metabolism in the preceding 24 hours, and their body’s ability burn fat. The test device creates a moment of truth: am I really eating as well as I think I am? The moments of truth provide a platform for engagement. Healthcare professionals then can guide a tailored healthcare and weight loss journey. The approach opens a door to address the psychology around weight loss.

And it works. People’s behavior changes. Compared to other weight-loss programs (as opposed to GLP-1s), people are losing a greater percentage of their body weight over a six-month period. The difference stems from meeting them at their moment of truth and facilitating a behavior change.

In constructing a wellness journey built around the moment of truth, we remained mindful of three criteria, which guide the art of showing up correctly:

New utility
Breakthrough ideas provide the customer with something different, and better, than they had before. That new utility isn’t just a feature function – it’s an entire experience, and benefits of the experience have to be clear enough and compelling enough that someone will be willing to step into the new world you’ve created. On behalf of the biotech client, we created a new experience around weight loss. We provided a novel utility—a breath score—that was potentially more helpful and less shaming than a bathroom scale. We integrated coaching and advice.

Information relevance.
We all know information overload is real. As designers, we need to be in tune with that humanity and make sure we only serve up information that makes people want to use the utility we afford them. We want to help our users manage information overload by making it compelling, clear and easy for them to understand why they should try a new experience—and that it was designed with their hopes, priorities, worries, difficulties and daily joys in mind.

We also have to make sure the benefits are quantified for them. Do they understand how much value the new experience will bring them?

Emotional resonance.
Design also has an emotive portion—it creates meaning that goes beyond the purely transactional; it unlocks potential. People become raving fans of a brand or an experience because it shows up where it matters the most. They go tell their friends about it because they want their friends to enjoy the same value.

For customers of the biotech client, we are successful in showing up where it matters most—in helping them realize their own potential and power to change their habits and improve their health. Data and reasoning models and compute power—without capable humans in the loop—just can’t do that. As far as I know, algorithms can’t make non-linear choices to sense a path to meaningful moments of truth, balancing human needs, scientific drivers and the confluence of business and industry drivers.

As leaders, we aspire to serve constituents who are varied and intersectional. These constituents often have value criteria that are complicated, nuanced and even contradictory. To serve those people in all their complexity, leaders and their teams benefit from a diversity of perspectives.

Said differently: we do a disservice when our teams see each other by only by title.

You are serving target audiences that are beautiful tapestries of intersectional beings. And they see you. So, if your brand is not evolving to meet that diversity, then disconnects and cognitive dissonance will surface all over the place and ultimately distract from the utility and experience you’re trying to deliver.

If we build teams that mirror our constituents and normalize that team members see each other in their full humanity, they start to recognize when their colleagues already deeply understand nuances among the people you’re looking to serve. This is not just about having creatives lead journey-map sessions with Sharpies, Post-It notes. These team members enable your business to create relationships with constituents who may not otherwise want to talk to you.

Leaders also need to acknowledge that human-centered innovation is non-linear. It doesn’t march to the beat of an agile sprint. Innovation teams need time and mental space to look out over the horizon and consider the long view—how the value criteria of your customers will change, as will the customers themselves; the resonance of what’s on offer for today’s customers as well as customers that might be served in the future. The long view helps teams anticipate when core offerings and services and practices that have served us well may need to change or even be replaced for success in the future.

Many organizations face a dearth of information in understanding exactly how this might happen. That’s why the design tenents of prototyping and experimentation are so valuable. With each iteration, you gain new information that informs decisions about the next one. Ask your teams what they learned last week, and how that differs from the initial work plan. Then ask how they’ll break or alter the work plan this week to get closer to the information that really matters. As an organization builds its innovation muscle, this process will yield new offerings that can augment or replace sections of the core.

We often think the core competency of a business is its ability to provide a product or service. But every business, no matter what it makes or sells, benefits from a parallel set of competencies aimed at innovation. If customer needs evolve, you better have the skills and frameworks to navigate a forest of ambiguity, to find new moments of truth and deliver differently.

Efficiency wins favor on Wall Street, but we know favor can be fleeting. Enduring, creative problem-solving skills propel innovation and can power companies for the long haul. If generative AI investments extend productivity and free up time for higher-level thinking, well, that may be exactly what your design teams need.