AI Models vs. Real Models for Diversity

The fashion industry is rethinking how it represents diversity in campaigns. Brands are now exploring AI-generated models alongside human models to address representation gaps, cut costs, and create scalable content. AI models offer efficiency, cost savings, and customization, while real models bring emotional depth and genuine connections. However, both approaches face challenges like bias, logistical hurdles, and audience perception. Many brands are adopting hybrid strategies, blending AI's speed with the authenticity of human models to create more inclusive campaigns.

Key Points:

• AI Models: Faster, cost-effective, and scalable but lack emotional depth and may reinforce biases.

• Real Models: Offer genuine connections and community insights but are costlier and slower to manage.

• Hybrid Approach: Combines AI efficiency with human creativity, ensuring ethical and relatable campaigns.

Quick Comparison:

The future of diversity in fashion lies in balancing AI's efficiency with the depth human models provide, ensuring campaigns resonate with consumers while addressing ethical concerns.

Fashion Brands Are Using AI Models For Diversity

AI Models for Diversity: Benefits and Challenges

Artificial intelligence is transforming how fashion brands approach diversity, creating opportunities to represent a broader spectrum of people in their campaigns. By enabling brands to design and test diverse representations before launching large-scale campaigns, AI is redefining inclusivity in the fashion world. However, as this technology evolves, it’s important to weigh its benefits against its challenges to ensure authentic representation.

Benefits of AI Models for Diversity

AI offers a practical and efficient way for brands to create diverse visual content. With AI, companies can generate models of varying ethnicities, body types, ages, and abilities without the logistical hurdles of traditional photo shoots. This means brands can experiment with diverse representations faster and more affordably. Expenses like model fees, photographer rates, studio rentals, and travel are no longer barriers, which makes this technology especially appealing to startups and smaller businesses.

For U.S.-based fashion brands operating in multiple markets, AI’s scalability is a game-changer. Instead of coordinating separate shoots for different demographics, brands can quickly produce tailored campaign variations for various audiences, saving weeks of work. AI also ensures creative consistency - models can maintain the same poses, expressions, and styling across product lines, helping customers focus on the clothing itself rather than inconsistencies in the imagery.

Despite these advantages, AI-generated models are not without their flaws.

Drawbacks of AI Models

One of the biggest challenges with AI models is their inability to capture the emotional depth and personality that human models bring to the table. Subtle expressions and authentic connections - key elements in creating impactful campaigns - are often missing in AI-generated images.

Bias in AI training data is another pressing issue. A 2023 study found that 75% of organizations fail to address bias in their AI systems. When AI models are trained on datasets that reflect societal prejudices, they risk reinforcing stereotypes. This problem is further compounded by the lack of diversity within the AI workforce, where men account for 91.88% of the field.

"Fairness in AI is not just an option; it's the foundation of equitable technology for all. Accountability in AI (is) where innovation meets responsibility, ensuring technology serves humanity."
– Franki Tabor, AI ethics and fashion consultant

Historical examples highlight these concerns. In 2014, Amazon’s AI recruitment tool discriminated against female candidates because it was trained on male-dominated resumes. Similarly, Facebook’s 2017 hate speech detection algorithm showed bias by failing to protect certain groups while overcompensating for others.

AI models also tend to produce overly idealized images, perpetuating unrealistic beauty standards. They struggle with complex poses and nuanced community-specific cues, which can result in visuals that don’t resonate with or accurately represent the intended audience.

How BetterStudio Supports AI-Driven Diversity

BetterStudio is addressing these challenges head-on with its content creation platform. The platform allows brands to create hyper-realistic AI models with extensive customization options, making it easier to craft diverse representations at scale.

Brands can adjust facial features, skin tones, and body proportions to align with their target audiences while avoiding stereotypical depictions. BetterStudio also focuses on eliminating the "uncanny valley" effect, ensuring the final images feel natural and relatable. Bulk editing tools make it simple to apply diversity standards consistently across entire campaigns.

The platform goes a step further by integrating AI-generated models with digital twins of real models and influencers. This hybrid approach combines the authenticity of human connection with AI’s efficiency. For larger brands, BetterStudio offers API integration, enabling seamless incorporation of diverse content into existing workflows.

"The datasets that are going to drive business for the next five to 10 years are being built now, and the training sets we're using now are biassed or built by a very specific population. It's really exciting and important that brands can train image models with diverse models rather than using AI to replace diverse models."
– Ranjan Roy, VP of strategy at Adore Me

BetterStudio emphasizes the importance of high-quality training data and continuous improvement. The platform equips brands with tools to refine their diversity strategies, ensuring AI models enhance rather than replace genuine inclusion efforts. Next, we’ll explore how real models contribute to advancing diversity in fashion.

Real Models for Diversity: Strengths and Drawbacks

Real models remain an essential part of creating authentic representation in fashion. Their presence brings a depth of connection that stems from their personal stories, backgrounds, and lived experiences - qualities that resonate strongly with audiences.

Strengths of Real Models

Human models bring something AI simply cannot replicate: authenticity. Each model carries their own unique story, shaped by their background and experiences, which helps campaigns connect on a deeper level with viewers. Their natural expressions, movements, and individuality create a relatable impact that enhances marketing efforts.

"We believe human models will continue to play a vital role in the fashion industry, establishing genuine connections with consumers; our technology aims to support this. And, yes - we need more of them to come from underrepresented groups if fashion companies are serious about inclusion efforts."
– Michael Musandu, CEO and founder of Lalaland.ai

Real models also offer invaluable insight into their communities, helping brands avoid missteps while ensuring campaigns feel genuine. Their input shapes everything from styling to poses, making the final product more meaningful and culturally aligned.

"The entire point of diversity representation is to celebrate the authentic, the cultural, the unique, and the lifestyle... AI does not celebrate diversity but parodies it."
– Rebecca Valentine, London-based Grey Modeling Agency

Challenges in Using Real Models

While the benefits are clear, using real models comes with logistical and financial hurdles. Coordinating photoshoots that include models of various ethnicities, ages, body types, and abilities requires significant planning, larger budgets, and extended timelines. For brands operating in multiple markets, the costs and complexities of ensuring diverse representation across regions only increase.

The industry also faces systemic diversity issues. Although nearly half (47%) of models in advertising and on runways are people of color, only 9% of executive marketing roles are held by people of color. This lack of diverse leadership often leads to blind spots in casting decisions and campaign strategies.

"We have this amazing Earth that we're living on. And you have a person of every shade, every height, every size. Why not find that person and compensate that person?"
– Yve Edmond, New York City area-based model

Another obstacle is consumer skepticism. Nearly half (48%) of adults reported feeling excluded from fashion ads in the past year. Audiences are increasingly wary of brands that appear to use diversity as a marketing tactic rather than a meaningful commitment. Performative representation can backfire, alienating the very consumers brands aim to engage.

The representation gap remains a persistent issue. Over 40% of consumers struggle to find clothing in their size or envision themselves in advertised products due to a lack of diverse models. Additionally, 30% of women aged 55 and older say they have difficulty finding age-appropriate clothing options.

Economic challenges have also slowed progress. Only 5% of recruiters currently rank diversity and inclusion as a top priority. This shift has created fewer opportunities for underrepresented models and hindered the industry's ability to achieve real progress in representation.

"Divesting from DE&I because it's no longer 'trending' is a short-sighted view because it overlooks the influential association customers make between their purchases and their principles."
– Yaseen Eldik, Executive Advisor for DE&I at Fixer Advisory

Ultimately, addressing these challenges requires more than surface-level changes. Achieving true diversity means transforming the industry at every level - from hiring practices to supply chain decisions. It’s a long-term commitment, not a quick fix, and it demands sustained effort from all stakeholders.

Next, we’ll explore how these challenges compare to the potential and limitations of AI models in fashion.

AI Models vs. Real Models: Direct Comparison

Fashion brands often weigh the pros and cons of using AI models versus real models, factoring in costs, representation, and the emotional connection with their audience. These considerations shape how brands approach their marketing and representation strategies.

Key Comparison Factors

Authenticity and emotional connection stand out as the primary distinction between AI models and real models. Real models bring genuine, lived experiences to the table, creating a deeper connection with audiences. On the other hand, AI models risk delivering overly polished or formulaic representations.

"One model does not represent everyone that's actually shopping and buying a product. As a person of color, I felt this painfully myself." - Michael Musandu, co-founder and CEO of Lalaland.ai

Cost and scalability are where AI models shine. They significantly cut production costs and allow brands to create vast amounts of content quickly and efficiently.

"With traditional photography, companies need to hire models, work with third parties like model agencies, hair stylists, makeup artists - not to mention undergo reshoots, which happens on average two-to-eight times per collection... So it makes it very difficult or at least unfeasible for a brand to showcase 20 different models wearing one product for every single collection without drastically having to increase the price on the product." - Michael Musandu, CEO and Co-Founder of Lalaland.ai

Bias and representation accuracy pose challenges for both methods, though in different ways. AI models can unintentionally reflect biases present in their training data, leading to skewed outputs. Real models, while authentic, rely on inclusive casting and diverse creative teams to ensure accurate representation.

Speed and consistency heavily favor AI models. They enable brands to churn out content at lightning speed, keeping up with trends and seasonal demands. AI also ensures uniformity in product presentation, while real models naturally introduce variations that require more effort to manage.

Side-by-Side Comparison Table

The comparison highlights that AI models excel in efficiency and cost savings, while real models lead in authenticity and emotional resonance. With 70% of consumers preferring brands that showcase diversity in their marketing, the decision often goes beyond just cost.

Hybrid Approaches: A Balanced Solution

To bridge the gap, many brands are adopting hybrid approaches. This involves combining the efficiency of AI with the authenticity of real models. For example, some brands create digital twins of real models, blending scalability with fair compensation for the models.

"Empowering diverse models by giving them the means and protection to capitalise on their digital twins through licensing agreements is essential." - Dale Noelle, founder of True Model Management

The success of these strategies often depends on a brand's dedication to inclusivity. As Shereen Daniels points out, brands with a strong foundation in representation can use AI to amplify their values. However, those lacking diversity may face criticism for appearing to take shortcuts.

Business Solutions for Scalable Diversity: BetterStudio's Approach

Fashion brands face the challenge of producing diverse and inclusive content while working within tight budgets. BetterStudio tackles this issue by merging AI-driven efficiency with ethical practices that respect the roles of real models and influencers. This approach allows brands to expand their diversity efforts without compromising on quality or credibility.

Features That Support Diversity Goals

At the heart of BetterStudio's platform are custom AI models designed to represent a wide range of body types, ethnicities, and demographics. These tools let brands easily adjust visuals, making it possible to quickly test creative concepts tailored for different audiences. This adaptability is especially important for US brands, where the demand for inclusive representation continues to grow.

"BetterStudio's platform lets brands customize visuals by body type and ethnicity, aligning with consumer demand for inclusivity and enabling rapid testing of creative concepts to target diverse audiences." - Luca Arrigo, CEO of BetterStudio

The platform’s digital twins technology stands out by combining AI efficiency with the authenticity of real models. Models and influencers can license their digital likenesses while keeping ownership of their intellectual property. Additionally, bulk editing features simplify the process of implementing diversity by allowing brands to apply consistent adjustments - such as model representation, backgrounds, and styling - across entire product catalogs without disrupting their workflows.

This innovation goes hand-in-hand with BetterStudio’s influencer marketplace, which connects brands directly with real models and influencers. By blending AI scalability with genuine representation, the platform paves the way for deeper collaborations with these stakeholders.

"Our full vision is to allow real influencers and real models to be hired through our platform. We want to start collaborating with these stakeholders so that we build it in a way that is ethical and in a way that they are included in the conversation." - Luca Arrigo, CEO of BetterStudio

For US-based fashion retailers, BetterStudio also integrates seamlessly with Shopify, streamlining e-commerce workflows. By pairing AI precision with human authenticity, the platform enables brands to create more compelling and inclusive campaigns.

Solutions for US-Based Fashion Brands

BetterStudio's features translate into practical benefits for US fashion brands looking for scalable diversity solutions. Its pricing structure is designed to accommodate businesses of all sizes. Image costs range from $0.75 to $1.30, and the AI-powered tools can cut photoshoot expenses by as much as 80%. This makes it easier for smaller brands to compete with larger companies in creating diverse, high-quality content.

For larger retailers, enterprise integration options offer custom API solutions that embed diversity standards directly into their content management systems. Enterprise clients also benefit from dedicated account management and tailored strategies to align diversity efforts with their brand identity.

The platform’s credit packages, ranging from 10 to 1,000 credits, offer flexibility. Brands running seasonal campaigns or testing new markets can purchase credits without committing to fixed monthly costs, with lower per-credit rates for larger packages.

BetterStudio’s ability to generate diverse content in minutes gives brands the agility to respond to trends quickly. Localized content creation tools further enhance this by allowing companies to adjust model representation for specific geographic markets. This ensures that visuals resonate with local audiences across the country, reflecting the unique demographics of different states and communities.

The Future of Diversity in Fashion Photography

The fashion industry is at a crossroads, where technology and human creativity must work hand in hand to achieve true inclusivity. With 73% of fashion executives planning to integrate generative AI into their creative processes, the challenge lies in using AI to complement - not replace - the human touch.

The key to progress lies in a hybrid approach: blending AI’s efficiency with the authenticity that only real models can provide. A great example of this balance comes from sustainable accessories brand Thalie. They collaborated with photographer José Aragón and digital creative Carrie Crigler to launch their first AI-powered campaign. By using avatars created from the faces of real models - Olia, Liza, and Taja - Thalie ensured the models were fairly compensated and their intellectual property was protected.

"We see it as a sustainable and innovative solution that aligns with our brand's values, and we plan to continue utilizing this technology in future campaigns. While the use of AI avatars has numerous benefits, we acknowledge there may be challenges, such as maintaining brand authenticity and connection. However, we believe that with a considered way of using it, as a supporting element during the creative process of creating our campaigns, these challenges can be overcome." - Nathalie Dionne, founder of Thalie

Key Takeaways

Here’s what we can learn from these developments: blending AI with human creativity can drive diversity while maintaining authenticity.

• AI offers scalability and cost savings, producing images for as little as $0.75 to $1.30 each, compared to the $50 to $200 price tag of traditional photography.

• Real models bring irreplaceable human qualities, such as genuine expressions and cultural connections, which AI-generated avatars simply can’t replicate.

The sweet spot lies in combining these strengths. Tools like digital twin technology allow real models to extend their careers by licensing their likeness while retaining control over how their image is used. This approach not only benefits models but also ensures campaigns remain authentic and ethical.

Behind the scenes, having diverse teams and prioritizing ethical AI practices is equally important. As Dale Noelle, founder of True Model Management, explains:

"Empowering diverse models by giving them the means and protection to capitalize on their digital twins through licensing agreements is essential".

What's Next

Looking ahead, the fashion industry appears poised to embrace hybrid strategies that use both AI and real models to create ethical, scalable campaigns. Licensing agreements for AI-generated images will offer seasoned models new income opportunities while extending their careers.

Brands are also exploring virtual try-ons and personalized fashion shows powered by AI. These innovations make shopping more inclusive while preserving the human connection that consumers value.

Transparency will be critical as regulations like the Fashion Workers Act in New York mandate consent and compensation for the creation and use of digital replicas. Companies will need to clearly disclose when images are AI-generated and ensure that their diversity efforts include meaningful participation from underrepresented voices.

"We believe human models will continue to play a vital role in the fashion industry, establishing genuine connections with consumers; our technology aims to support this. And, yes - we need more of them to come from underrepresented groups if fashion companies are serious about inclusion efforts." - Michael Musandu, CEO and founder of Lalaland.ai

Ultimately, the fashion brands that succeed will be those that balance innovation with ethics. By using AI to amplify the diversity and humanity of their campaigns, they can create content that is not only scalable but also deeply authentic. As Franki Tabor, Ethics and Fashion Consultant, puts it:

"In the labyrinth of AI, ethics is the compass guiding us towards responsible innovation."

FAQs

How do AI-generated models and real models work together to promote diversity in fashion campaigns?

In the world of fashion campaigns, AI-generated models and real models are teaming up to bring a new level of diversity and representation. Each brings something special to the table: real models offer genuine emotion, individuality, and a human touch, while AI models provide unmatched flexibility, scalability, and cost savings. Together, they’re helping brands showcase a wider variety of ethnicities, body types, and age groups.

This collaboration gives fashion brands the ability to produce high-quality, inclusive content on a large scale without losing the creativity or emotional connection that real models bring. By blending the emotional appeal of real models with the adaptability of AI, brands are not only reaching broader audiences but also redefining the standards of representation in the fashion world.

What biases can occur with AI-generated models, and how can fashion brands ensure diverse and authentic representation?

AI-generated models can sometimes mirror biases, including narrow representation, body type stereotypes, and insensitivity to cultural nuances. These issues often arise from imbalanced training data, leading to visuals that don't genuinely reflect diverse audiences.

Fashion brands can tackle these challenges by taking thoughtful steps such as:

• Training AI models with diverse and inclusive datasets to better represent varied demographics.

• Conducting regular reviews of AI-generated content to identify and address any biases that may surface.

• Ensuring human oversight to align visuals with the goal of authentic and fair representation.

By blending advanced technology with intentional practices, brands can produce content that connects with a broader audience while championing inclusivity.

How do digital twins balance the efficiency of AI with the authenticity of real models in fashion marketing?

Digital twins are transforming fashion marketing by blending AI precision with lifelike authenticity. These virtual replicas of models, garments, and other elements allow brands to create highly realistic content at a faster pace, scale campaigns effortlessly, and cut down on waste - all while reflecting diversity and inclusivity in their visuals.

With digital twins, brands gain precise control over their imagery, making it easier to craft personalized marketing strategies that align with modern values. At the same time, they open doors to new creative approaches. However, this technology also sparks conversations about its impact on opportunities for real-life talent within the fashion industry. Finding the right balance is key to embracing innovation while preserving the human element that makes fashion relatable.

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