Does AI Face Replace Instagram Face as the Beauty Standard?

For years we chased the hyper-filtered features of our favorite influencers, but now AI is turning our attention away from others' faces and toward impossibly perfected, artificial versions of our own.

According to Anil Joshi, cosmetic surgeon and president of the British Society of Facial Plastic Surgeons: “I think we are witnessing the possible evolution of the ‘Instagram Face’ into what we might call the ‘AI Face’.” He notes that patients arrive at appointments “very regularly” carrying AI-generated renderings of themselves to illustrate the look they want. Because such AI-produced images are now so easily produced via chatbots that have become part of daily routines, surgeons report that these mock-ups are taking over from celebrity photos and heavily filtered selfies as the template for a “perfect” face.

The same day we spoke, one of Joshi’s patients turned up with an AI-generated nose image that looked nothing like what had been discussed during earlier rhinoplasty consultations — a situation that creates fresh challenges for aesthetic doctors, who need to manage expectations while keeping patients safe.

Joshi says: “It took a very long consultation to address some of the requests. An AI-generated face must be understood as a creative interpretation, not an anatomically accurate prediction. My concern is that technology may encourage people to confuse digital possibility with what surgery can realistically achieve.”

With AI image generators growing sharper and more convincing by the day, the boundary between digital fantasy and surgical possibility keeps blurring further. AI's advancing “multimodality” — including its capacity to process image, audio and video inputs along with text — has given rise to a cottage industry of dedicated facial analysis tools. These offer AI-powered scans that score users' appearances, identify perceived flaws, and suggest changes to ‘optimize’ their looks measured against supposedly objective, ‘science-backed’ beauty ideals.

These include LooksMax AI and Umax, both downloaded more than 10 million times on Google Play alone. There's also Qoves, a facial analysis firm whose founder and CTO Shafee Hassan describes its output as “educational videos” that break down celebrity features against supposedly scientific beauty standards, shared with its three million social media followers.

Qoves charges $150 annually for individualized facial evaluations, stating that its proprietary AI models are paired with human review to measure clients against what it terms “research-based aesthetic benchmarks,” covering upwards of 160 facial markers that range from facial symmetry to skin quality. Afterward, clients get a tailored “improvement protocol” — a step-by-step plan suggesting changes to their appearance, paired with AI-generated images showing what the results might look like. The service has caught on: Qoves currently has 80,000 clients aged 20 to their late 50s, and those willing to pay an extra $180 can also receive surgical recommendations.

Amid this rising desire for a digitally polished self-image, demand for cosmetic surgery has been climbing as well. The American Society of Plastic Surgeons reports that cosmetic surgical procedures in the US increased 7% last year. Every surgeon interviewed by Vogue Business described a marked rise in demand since Covid, connecting the shift to lives spent increasingly online.

“We’ve gone from the mirror generation, who used to look at themselves maybe three or four times a day when brushing their teeth or taking the lift, to the selfie generation, who stare at themselves constantly on-screen, take pictures and are so much more critical because they constantly see what the ‘ideal’ is,” says Dr. Brian J. F. Wong, a professor of otolaryngology and biomedical engineering at the University of California, Irvine. “Now, that ideal is being driven by what the large language models [LLMs] get by scraping the internet.”

Unrealistic expectations

Dr. Wong's research, which sets AI-generated attractiveness scores against human judgements, shows the two tend to match closely — not entirely surprising, since AI models learn from enormous datasets shaped by existing human perceptions and biases around beauty. Even if AI tends to reinforce rather than reshape conventional beauty standards, the ease of generating idealized self-images carries the risk of skewing what people think is realistically achievable. “It’s amplifying the insecurities that we all to some degree feel,” Dr. Wong says. “You just can’t make someone look completely different and like what Dr. AI can create, and it’s distressing seeing younger patients that are so heavily influenced by what they see online, as well as what they can create using the very sophisticated software that now lives on their phones.”

Aesthetic doctors now face a two-part problem: patients show up with digitally refined versions of their own faces, looking more photorealistic and within reach than conventional celebrity reference photos, while sometimes showing alterations that surgery simply cannot anatomically produce. Traditional Instagram filters typically alter an existing photo, whereas generative AI can rebuild facial features without being bound by the biological constraints of the original face.

“AI is effortless and much more convincing,” states Dr. Anisha Kumar, who works as a facial plastic surgeon in New York and serves as an assistant professor at Stony Brook University; her research looks at how beauty standards and expectations around cosmetic surgery can be shaped by AI facial analysis tools.

Dr. Kumar points out that among the limitations patients may overlook, AI-generated simulations fail to factor in individual anatomy — skin thickness, cartilage strength, bone structure — or how tissue scars and heals after surgery. A static image, often shot facing forward, also can't show how a face appears from other angles or while in motion.

According to experts, it falls on each doctor to grasp the limits of treatment and to explain the gap between reality and what AI might depict. “I have to spend a lot of time with patients telling them that the difference of a millimeter, for example, on the nose is profound,” says Dr. Wong. “It’s very hard to do with the precision that pushing a button on your phone will render with AI, and there are risk and reward curves.”

Joshi says that a client arriving at a consultation with an AI-generated image shouldn’t be brushed aside. “It can be an excellent starting point for a meaningful conversation. My first question would be: What exactly is it about this image that you like?” he says. Similarly, when he relies on AI simulations in his own practice to show clients what’s possible, Joshi stresses that it functions as a “communication tool”, not an exact promise of the end result.

Joshi, along with other doctors, is pushing for additional training so surgeons can better grasp how AI changes facial images, where its anatomical limits lie, and what psychological effects it might have on patients. He is also seeking clearer industry guidelines regarding how clinics convey the scientific validity of AI-generated assessments and recommendations.

“There are fundamental expectations around patient safety, informed consent, appropriate treatment, psychological wellbeing and honest communication. However, I believe we need clearer guidance on how to apply these principles to emerging AI technologies,” Joshi says.

Hyper-homogenization

Beyond the issue of unrealistic expectations, experts point to a broader consequence: as AI plays a growing role in shaping how we judge and modify our faces, it may speed up the homogenization of beauty standards, narrowing our collective idea of attractiveness even further.

The Instagram Face had already set this standardization in motion, marked by cheekbones that pop, lips with added fullness, jawlines cut sharp and eyes pulled upward. According to doctors, the AI Face leans toward those same traits, though rendered more subtly and with extra focus on skin that looks impossibly smooth and free of pores. Joshi explains it this way: “In some ways more deceptive. AI can generate aesthetic uniformity remarkably well, but this should never become our definition of beauty.”

This sits at the heart of what Dr. Kumar explores in new research published for the Journal of Medical Internet Research, looking at how AI training data carries built-in bias — both through the faces it includes and through whose standards of attractiveness get prioritized — in ways that could lock in narrow beauty ideals. With wider adoption of these tools, Dr. Kumar cautions that patients and surgeons alike may be pushed toward sameness in standards, where ethnic features that stand out get treated as problems needing correction. Dr. Kumar's current work looks at whether rhinoplasty simulations generated by AI keep patients' ethnic traits intact or end up changing them.

She further cautions about a feedback loop forming, in which beauty standards generated by AI shape what patients ask for, and the images produced from those requests could then be folded back into training datasets, narrowing the standards even more. For this reason, Dr. Kumar and her co-researchers contend that commercial facial AI apps and filters, which remain unregulated, ought to be required to publicly reveal how their tools were trained and tested.

Dr. Maryam Zamani, founder of Maryam Zamani Clinic. Photo: Courtesy of Maryam Zamani Clinic

Some experts additionally caution that this homogenization's effects may not stop at the faces patients want, but may also reach into how they see their own. “When we are constantly exposed to filtered or digitally enhanced images, our perception of what is normal can gradually shift. This is a type of perception drift,” says Dr. Maryam Zamani, founder of the eponymous Chelsea clinic. “We start to think the enhanced images are what we are striving for. Features that are entirely natural may begin to appear imperfect simply because we are comparing ourselves with images that have been altered.”

According to psychologists, studies examining how the growing presence of AI-generated imagery affects mental health and body dysmorphia remain at an early stage, though initial results hint it may worsen existing anxieties about appearance. Some draw on feminist objectification theory, which connects societal pressure around looks to ongoing self-scrutiny, cautioning that the “optimization recommendations” from AI facial analysis apps could deepen this pattern.

“The process of being told precisely how to ‘fix’ or ‘optimize’ your appearance can prompt greater self-scrutiny of how you look,” Dr. Nadia Craddock explains; she works as a psychologist and research fellow at the Centre of Appearance Research, UWE Bristol. Research she cites also indicates that people tend to feel worse when comparing themselves to peers rather than celebrities, possibly because peers set a more achievable benchmark that people believe they ‘should’ reach. “This suggests that how much a person can distance themselves from the target image is important.”

Following this reasoning, an AI-generated image of one's own face, refined past what is realistically attainable, might turn out to be the hardest comparison to face, since almost no psychological distance exists from it. Surgeons caution that once this idealized self-image becomes the standard, even perfectly normal features can start to appear as flaws that need fixing.

“There is a distinction between wanting to look and feel your best and feeling compelled to correct every perceived imperfection,” says Dr. Zamani. “My concern is that these technologies could encourage people to view normal human variation as a defect requiring correction. We should be using technology to support clinical judgement, not allowing an algorithm to dictate what a face should look like. The perception drift is real.”