In March of this year, OpenAI’s GPT-4o sent the internet into a frenzy with its ability to generate Studio Ghibli-style images. The model produces realistic, emotionally nuanced visuals from a series of prompts — a feat that has led some to predict the end of traditional visual arts. Although these conclusions might be hasty, many professionals in the field believe AI could revolutionize how digital modeling agencies function.

This belief isn't confined to one startup. A new wave of AI-driven agencies — including FanPro, Lalaland.ai, Deep Agency, and The Diigitals — is exploring whether modeling can be automated without sacrificing its creative essence. Some utilize AI to create lifelike avatars. Others provide virtual photo studios, CRM (customer relationship management) integrations, or creator monetization tools. Collectively, they represent a significant change in how digital modeling agencies view labor, revenue, and scalability.

FanPro — launched by Tyron Humphris in 2023 to assist digital modeling agencies in scaling efficiently — serves as a compelling case study. Entirely self-funded, Humphris stated in an interview that the company achieved $1 million in revenue within its first 90 days and surpassed eight figures by 2024, maintaining a small team by automating nearly every process.

As Humphris pointed out, "The companies leading this next decade won't just be those with the best marketing or largest budgets. They'll be the ones using AI, automation, and systems thinking to scale with precision, all while staying lean and adaptable."

This explains the bold move by startups like FanPro — but how far can this really go? And why should digital modeling agencies care in the first place?

Automation In Digital Modeling Agencies

To grasp how automation functions in the digital modeling sector — a rapidly growing segment of the creator economy — it's helpful to understand what it's replacing. A standard digital modeling agency juggles five or more monetization platforms per creator — from OnlyFans and Fansly to TikTok and Instagram. Yet behind each viral post lies a grueling process of scheduling, analytics, upselling, customer support, and retention. On average, an agency might require 10 to 15 contractors to manage just a few high-performing creators.

These agencies oversee a complex cycle: content creation, onboarding, audience engagement, and sales funnel optimization, typically across several monetization platforms. According to Humphris, there's often a misconception that running a digital modeling agency is merely about posting attractive pictures. However, he emphasized, "It's CRM, data science, and psychology all rolled into one. If AI can streamline even half of that, it's a game-changer."

This claim reflects a growing challenge in the creator economy, where agencies navigate an ocean of tools trying to monetize attention for creators while managing marketing, sales, and customer support. For perspective, a 2024 Clevertouch Consulting study revealed that 54% of marketers use more than 50 tools to manage operations — many pieced together with Zapier or manual workarounds.

However, according to Humphris, "No matter how strong your offer is, if you lack systems, processes, and accountability built into the business, it's going to crumble under pressure."

Enter AI. Beyond handling routine tasks, large language models and automation stacks now enable agencies to expand operations while staying lean. With minimal human intervention, agencies can schedule posts, automatically respond to DMs, upsell subscriptions, track social analytics, and manage retention flows. What once required a full team of marketers, virtual assistants, and sales reps can now be executed by a few well-trained AI agents.

FanPro asserts that over 90% of its operations — from dynamic pricing to fan interactions — are now managed by automation. Similarly, Deep Agency allows creators to produce professional-grade photo shoots without booking a studio or hiring staff, and Lalaland.ai assists fashion brands in generating AI avatars to cut production costs and enhance diversity in representation.

A Necessary Human Touch

Nevertheless, not everyone believes AI can capture the subtlety of digital intimacy. Some experts have expressed concerns that excessive automation in creator-driven industries could flatten human expression into predictable engagement patterns, jeopardizing long-term user loyalty.

A 2024 ContentGrip study of 1,000 consumers found 80% of respondents would likely switch brands heavily reliant on AI-generated emails, citing a loss of authenticity. Nearly half reported feeling "less connected" to the brand.

Humphris concurs.

"AI can accomplish a lot, but it needs to be paired with someone who understands psychology," he stated. "We didn't scale because we had the best tech. We scaled because we understood human behavior and built systems that respected it."

Humphris' viewpoint isn't merely anecdotal but grounded in research. For instance, a recent study by Northeastern University indicated that AI influencers often diminish brand trust — particularly when users aren't aware the content is AI-generated. The message is clear: over-automating the wrong aspects of human interaction can backfire.

Automation doesn't — and shouldn't — mean human input becomes irrelevant. Instead, as numerous industry experts have noted, it will enhance efficiency without replacing empathy. While AI can handle data processing at speed and generate appealing visuals, it cannot mimic human creativity or emotional intelligence. Nor does AI possess the psychological understanding of human behavior that humans do, a quality Humphris attributes to their rapid success.

What’s Working — And What’s Not

Lalaland.ai and The Diigitals have garnered acclaim for boosting inclusivity, enabling brands to showcase underrepresented body types, skin tones, and styles. Meanwhile, FanPro concentrates on developing AI "growth engines" for agencies — full-stack systems combining monetization tools, CRM, and content flows.

Not all responses have been favorable.

In November 2024, fashion brand Mango faced criticism for its use of AI-generated models, labeled as "false advertising" and "a threat to real jobs." The New York Post detailed the fallout, highlighting ongoing debates about ethical boundaries.

As brands strive to balance cost savings with authenticity, some have started labeling AI-generated content more transparently — or integrating human oversight into workflows instead of eliminating it.

Despite offering an automation stack, FanPro wasn't an immediate adopter of automation in its processes. Nonetheless, as Humphris noted, embracing AI made all the difference for the company. "If we had adopted AI and automation earlier, we would've hit 8 figures much faster and with far less stress," he remarked.

Automation In The New Era

FanPro exemplifies how proper AI integration could prove profitable for digital modeling agencies.

Whether or not the company's model becomes the template for AI-first digital agencies, it's evident there's a substantial shift in the creator economy, where automation isn't merely seen as a time-saver but also as a foundational component of businesses.

As digital modeling agencies delve deeper into an AI-focused future, the greater challenge lies in remembering what not to automate — the spark of human connection that established the industry in the first place.

"In this new age of automation," Humphris said, "the wisest agencies won't just ask what AI can do. They'll ask what it shouldn't."

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