AI might be the best thing to happen to design communication

Language-first workflows may be giving visual thinkers a powerful way to justify their choices — to both machines and people.

For as long as design has existed, its value has often been measured by what can be seen, not necessarily explained. The right layout, the perfect contrast ratio, the balance of form and whitespace — these are things designers often feel before they can articulate. This kind of tacit knowledge has long served as both our strength and our crutch. We speak through composition, not paragraphs.

Yet now, without much consent, a shift has begun.

The rise of AI tools — particularly language-based ones like ChatGPT — has been framed as a looming threat to creativity. Designers have voiced concerns about job security, creative dilution, and the flattening of aesthetics into AI-trained sameness.

These fears aren’t unfounded. But what’s been less discussed is the quiet, almost ironic benefit—the way it might be helping designers strengthen something they’ve long lacked — verbal communication skills.

AI, for all its synthetic nature, is requiring us to speak more clearly about the very instincts we struggle to defend.

From Intuition to Instruction

Traditionally, design often begins with visuals. A spark of inspiration might lead to thumbnail sketches, a color palette, maybe a mood board — something that gestures toward the end goal without requiring explanation.

The process tends to be iterative and embodied. Many designers learn through doing. Adjustments are frequently made by feel. Language, when it enters the picture, is often used after the fact — to rationalize decisions already in motion.

Even in UX — where research, testing, and user-centered rationale are considered foundational — intuition still plays a quiet but powerful role. Though we may not admit it, UX designers often make early choices based on what feels right — before we can explain why.

But when you start with AI — particularly through prompting — everything shifts. A designer can’t rely on a feeling—they have to begin with a sentence. And that sentence must carry intention. Something like:

“Design a checkout page for a boutique e-commerce brand targeting women aged 35–55. Use the brand’s existing muted terracotta and cream palette to maintain visual consistency and evoke warmth and trust. Prioritize simplicity to minimize cognitive load — especially on mobile — by limiting steps and clearly labeling each form field. Highlight key incentives like ‘Free Shipping on Orders Over $50’ above the fold. Place the primary CTA low enough to allow product and pricing confirmation, but still within thumb reach. The layout should balance brand elegance with conversion efficiency, supporting both user confidence and business goals.”

In the example above, starting the design process requires articulation, not intuition. Every element — color, hierarchy, phrasing — is intentional, deliberate, and spoken aloud before it ever appears on screen.

In this setting, vague inputs lead to vague outputs. So clarity isn’t a luxury — it’s the minimum requirement. And with that, designers are learning to name what they’ve historically only felt.

This doesn’t just produce better prompts. It produces better thinking. In translating vision into structured language, we’re forced to ask ourselves what we really mean by “trustworthy design” or “a clean aesthetic.” Those aren’t universal truths — they’re interpretations. And putting them into words makes them open to dialogue, feedback, and growth.

The Unspoken Gap

Designers have always lived with a kind of dual fluency requirement — visual and verbal — but the imbalance has been evident. We develop deep skill in one, and just enough in the other to survive a stakeholder meeting. This asymmetry often goes unnoticed until pressure mounts—a client asks why a layout changed, an executive questions color choices, or a developer misinterprets spacing logic.

That’s when the limits of instinct show. We default to lines like “It just felt more balanced,” or “It draws the eye better this way.” These explanations may be true, but they’re fragile. They don’t translate well across disciplines. And they don’t inspire confidence.

This is the actual cost of being under-articulated—not the inability to design, but the inability to defend, share, and scale that design. AI, ironically, is exposing this weakness by demanding specificity from the start.

And what begins as a technical exercise — writing better prompts — soon reveals itself as a philosophical one—how well do I really understand what I’m doing, and why?

Beyond Prompt Engineering

Most of the discourse around AI and design fixates on productivity, efficiency, and prompt engineering. There’s endless chatter about mastering the syntax of LLMs, chaining prompts, and building smarter workflows. But little attention is paid to what that process is doing to us, cognitively and interpersonally.

We’re not just getting better at talking to machines. We’re practicing how to talk to each other — more clearly, more intentionally, and more often through structured thought.

This matters. Because as design becomes increasingly embedded in interdisciplinary teams — alongside product managers, engineers, marketers — the ability to communicate intent becomes as valuable as the artifact itself. You can’t simply hand off a Figma file and hope the layers speak for themselves.

What AI demands is what humans desire—explanation without oversimplification.

And that’s a transferable skill — relevant far beyond the design world.

Designer Fear and the Paradox of Growth

Much of the anxiety around AI comes from the fear that it will replace what makes us uniquely creative. But what if creativity isn’t just the spark — it’s the articulation of that spark? After all, what good is an idea if no one else can understand it?

If anything, this push to put vision into words feels like a return to intentionality. We’re not just making things that look good. We’re being asked to explain how they work, what they mean, and why they matter.

The irony here is sharp—the very tools we fear will erase our humanity may be reinforcing our need to understand ourselves. When AI hands back a design that feels “off,” the process of fixing it becomes introspective. You’re not just tweaking the output — you’re refining your input. You’re thinking more clearly about what you believe good design is.

And you’re learning how to say it out loud.

Language as Leverage

This isn’t a call to abandon intuition. Intuition remains essential. But it’s no longer sufficient. As the design world becomes driven by metrics, cross-functional collaboration, and evidence-based decisions, intuition must become communicable. It must evolve into language.

That’s where the deeper value of this shift lies — not in faster mockups or infinite variations, but in the cultivation of clarity. AI becomes a kind of Socratic tool—it won’t let you move forward until you define your terms. Until you choose your meaning. Until you take responsibility for what you’re asking for.

The prompt becomes a mirror. And what it reflects is often fuzzier than we’d like to admit.

But over time, this fuzziness sharpens. Designers will start to speak not only more fluently, but more confidently. Not because they’ve learned a script — but because they’ve been forced to think through their process in words.

And when the moment comes to present work — not just to stakeholders, but to ourselves — we can speak with clarity and confidence.

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AI might be the best thing to happen to design communication was originally published in UX Collective on Medium, where people are continuing the conversation by highlighting and responding to this story.

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