AI Community Engagement: Lessons from The Doux

Most brands treat AI like a content vending machine. The Doux treats it like a community amplifier—and that’s why its approach stands out.

In early December 2025, The Doux’s co-founder and CEO Maya Smith said something a lot of U.S. consumer brands still resist: beauty companies are turning into tech companies. Not because they’re building data centers, but because the way they grow—customer communication, creative production, community building, and feedback loops—now runs through digital systems that increasingly include AI.

This matters for anyone building a digital service or scaling customer engagement in the United States. AI doesn’t just help you ship more content. It helps you involve more people in what the brand stands for—if you design it that way.

“AI is just another way to engage them.”

Below, I’ll break down what The Doux is doing, why it works, and how U.S.-based startups and digital businesses can apply the same playbook without losing the human part.

Community engagement with AI starts with access (not hype)

The fastest way to wreck trust with AI is to act like everyone has the same tools, time, and confidence. The Doux took the opposite route by building an initiative around education and accessibility.

Partnering with Black Girls Code, The Doux created the Black Beauty AI Challenge, inviting creators to submit AI-generated videos using only free tools (like Canva, CapCut, or Pika). That one constraint is strategic: it removes the “paywall” that quietly shapes who gets to participate in modern digital storytelling.

Why this approach converts attention into trust

If your campaign goal is leads, you need more than impressions. You need people to believe you’re serious—and to feel safe raising their hand.

Programs like this work because they:

• Lower participation friction (free tools, broad creative parameters)
• Create a repeatable community loop (submit → share → discuss → reward)
• Position the brand as a guide instead of a broadcaster

I’ve found that when brands teach a skill (even a small one), it changes the relationship. You’re no longer “marketing at” someone—you’re building capability. In the U.S. digital economy, that’s a strong form of authority.

A practical template you can copy

If you’re a SaaS company, agency, or digital service provider, you can run a similar challenge in your niche:

1. Pick one output (30–60 second video, 5-slide carousel, 1-page landing page)
2. Limit tools to free tiers to widen participation
3. Give a theme tied to your customer’s identity or mission (not your product features)
4. Offer a prize that creates momentum (cash, mentorship, exposure, a paid pilot)
5. Publish the best entries as a community showcase

The point isn’t the contest. The point is the community-powered content engine you get from it.

Use AI to clarify the creative vision—humans still lead

The Doux didn’t use AI to “come up with culture.” It used AI to translate culture into executable creative.

For product launches like the Press Play Collection, Maya Smith used image generation to turn an internal vision board into clearer creative direction. That reduces the expensive part of marketing production: revision cycles, misalignment, and “we’ll know it when we see it” feedback.

What AI is actually replacing in marketing teams

In real teams, AI isn’t replacing the creative director. It’s replacing the messy middle:

• early-stage mockups that used to take days
• repeated rounds of “close, but not quite” edits
• the time cost of aligning stakeholders before production

If you’re trying to scale customer engagement, this matters because speed isn’t just speed. Speed is more experiments per quarter, which means more chances to find messaging that resonates.

The skill nobody talks about: prompting is cultural specificity

One of the strongest insights from Smith’s approach is that using AI well requires more than writing prompts. It requires knowing what to ask for.

She describes needing art-history references, camera-angle language, and specific aesthetics. That’s a clue for startups: if you want AI to produce on-brand outputs, you need a brand language system.

Here’s what that looks like in practice:

• a one-page “visual vocabulary” (colors, lighting, mood, references)
• a list of “always” and “never” brand rules
• examples of what culturally accurate representation looks like

AI can generate options. It can’t define what “right” is for your community.

Bias is a product risk: “Train AI” is also brand strategy

The Doux’s stance is direct: representation and access lag behind AI’s speed. That’s not just a social issue—it’s a business risk.

When your AI outputs miss the mark culturally, you don’t get “meh” performance. You get screenshots, backlash, and a trust deficit that’s hard to repay.

What “training AI” means for most businesses

You don’t need to build your own model to reduce bias. But you do need a system for:

• feeding the right examples (approved imagery, language, and context)
• reviewing outputs before publishing
• capturing feedback from the community when you get it wrong

For U.S. digital services, this is where AI governance becomes practical. It’s less about policy documents and more about operational habits.

A simple, effective control that works in small teams:

• Create a “representation checklist” for AI-generated content
• Require a second reviewer for public-facing creative
• Maintain a “do-not-use” library (problematic phrases, visuals, tropes)

If your business depends on customer communication at scale, these guardrails protect your brand as much as they protect your audience.

AI can scale communication, but it can’t replace IRL community

The Doux’s Block Party launch is the part many AI-first teams forget: the highest-trust moments still happen offline.

The brand designed an in-person NYC event that reflected what its customers said they missed—neighborhood block parties, shared music, collective joy. AI helped shape campaign creative and metaphors, but the emotional center happened in real life.

Why in-person still wins in a digital-first economy

AI is excellent for:

• distributing stories
• creating more touchpoints
• speeding up production
• personalizing messaging

But community isn’t only messaging. Community is shared experience.

If you’re a U.S. startup or digital platform trying to generate leads, don’t treat events as a “nice-to-have.” Treat them as a conversion accelerant:

• Online content builds awareness.
• AI helps you scale and test messaging.
• In-person creates belief.

Even one small event per quarter (a workshop, meetup, customer dinner) can become the anchor content that AI then multiplies into emails, clips, posts, and landing pages.

The modern engagement stack (AI + human)

A balanced stack looks like this:

1. Listen: surveys, DMs, reviews, support tickets
2. Synthesize with AI: cluster themes, extract repeating language
3. Create with AI: draft concepts, mockups, scripts
4. Validate with humans: community review, internal brand check
5. Gather IRL stories: events, interviews, user spotlights
6. Scale distribution with AI: repurpose into multi-channel content

That’s how you build a customer engagement machine without turning your brand into a chatbot.

A 30-day plan to apply The Doux playbook

If you want to use AI for community engagement (and not just for output volume), here’s a practical month-long rollout.

Week 1: Build your “community truth” doc

• Collect 50 real customer quotes (calls, reviews, support chats, comments)
• Summarize 5 recurring identity themes customers care about
• List 10 things your audience hates seeing from brands (tropes, clichés, misrepresentation)

Week 2: Create an AI-ready brand system

• Write 20 approved phrases and 20 “never use” phrases
• Create 10 example prompts that produce on-brand content
• Define a review workflow (who approves what, and how fast)

Week 3: Launch a low-friction community activation

• Run a mini challenge that uses free tools
• Keep the creative prompt broad enough to invite interpretation
• Offer a prize that creates real motivation (money, time, access)

Week 4: Turn community output into lead generation

• Package the best submissions into a downloadable showcase
• Invite participants to opt in for a follow-up workshop
• Use AI to repurpose the same story across email, social, and your website

If you want leads, build an experience people want to join—not just a campaign they scroll past.

Where AI-powered community engagement is heading in the U.S.

The bigger story in this topic series—How AI Is Powering Technology and Digital Services in the United States—isn’t that AI is making marketing faster. It’s that AI is changing the shape of customer relationships.

The Doux shows what the next phase looks like: AI that supports culture, improves access, and scales communication—without pretending human connection is optional. That’s the bar I think more U.S. brands and digital service businesses need to aim for.

If you’re planning your 2026 growth strategy, here’s the question worth sitting with: when your customers look at your AI-powered content, do they feel seen—or processed?