Walk into a beauty store or open a shopping app in 2025 and it is increasingly likely that the first “expert” you meet is an algorithm. From selfie based skin analyzers and virtual lipstick try ons to AI powered routine builders, beauty brands are using artificial intelligence to answer an old question in a new way: what should I buy for my skin, hair or look, right now.
The shift is not only global. India is one of the fastest growing beauty and personal care markets, valued at about 17.8 billion dollars in 2023 and projected to cross 45 billion dollars by 2033, with annual growth in the low double digits. Alongside products, a parallel market is emerging for beauty tech and devices, from at home gadgets to diagnostic tools, which is forecast to grow strongly this decade. Marketers see AI not as an add on, but as part of how discovery, advice and purchase now fit together.
Virtual try ons, AI driven recommendations and diagnostic tools are being deployed most aggressively in colour cosmetics and skincare, where choice is high and mis buying can lead to frustration or returns. For digital first players, these tools help reduce uncertainty that often blocks a purchase.
When Nykaa partnered with L’Oréal owned ModiFace to bring AI based virtual try ons to its platform, the goal was to add confidence to online shade selection. Anchit Nayar, CEO of e commerce beauty at Nykaa, framed the move in experience terms rather than technology. He said the partnership would provide a “rich, immersive buying experience” and that with the AI powered virtual try on option, customers can “confidently make a choice from our wide range of options wherever they are, whenever they want.” The integration signalled that virtual testing was moving from experiment to core part of the shopping journey.
For global beauty tech providers, India is now a priority market. Perfect Corp, which powers AI and augmented reality try ons for brands around the world, has expanded its local operations and client list. Country head Tanuj Mishra has described demand for AI led tools in straightforward terms, noting that “the demand for AI in skincare shopping is soaring” and that AI powered virtual try ons for jewellery are an emerging category. He has also said the company wants to “democratise the accessibility of cutting edge AI, AR and digital technologies within the retail industry,” including for smaller and women led beauty businesses.
These systems are not only for large brands. Perfect Corp and other providers have launched small business programmes to make AI and AR accessible to independent labels and regional retailers. The pitch is that if the underlying technology is easier to adopt, smaller beauty firms can compete on experience and advice, not only on price or discounting.
Among the most visible uses of AI in beauty marketing is the skin analyzer, a tool that uses a smartphone camera or in store device to assess concerns such as dryness, acne, pigmentation or fine lines. These analyzers sit at the intersection of marketing and service. For the consumer, they promise personalised diagnosis and a routine tailored to visible needs. For brands, they structure data and help convert browsing into a guided path.
In India, skin mapping tools are being deployed by both homegrown and multinational brands. Honasa Consumer, the parent company of Mamaearth and The Derma Co, has publicly credited augmented reality, virtual reality and skin mapping AI with a 30 to 40 percent lift in revenue, arguing that better product matching helps both conversion and retention. These tools sit on websites and apps, asking users a mix of visual and lifestyle questions and then recommending specific products and regimens.
Global providers are layering in more nuance. AI skin diagnostic tools are being trained to work across a range of skin tones and lighting environments, something that matters in diverse markets. As these systems are adopted by Indian brands and retailers, they quietly change how marketers think about campaigns. Instead of generic messaging for “oily skin” or “sensitive skin,” teams can map communications to clusters defined by actual diagnostic results, not only self perception.
The rise of AI powered analyzers also pushes brands closer to quasi clinical language. Many now highlight the number of images used to train models, the dermatologists consulted, or the percentage match between recommendation and user profile. Regulators have not yet drawn hard lines around such claims, but marketers acknowledge that overstatement could trigger scrutiny in future.
If skin analyzers are the diagnostic layer, virtual try ons are the experimentation zone. Using phone cameras or in store mirrors, shoppers can see lipstick, foundation, eye makeup, hair colour or even jewellery on their own face in real time. This is where AI, computer vision and augmented reality meet brand storytelling.
For early adopters, virtual try ons were a differentiator. In 2025, they are close to hygiene for large online beauty platforms and many mall based stores. Nykaa’s use of ModiFace, global services such as Sephora’s shade matching systems and a range of AR mirrors in flagship outlets have set expectations for how beauty shopping should feel.
In India, virtual try on technology is being used not only for colour cosmetics but for jewellery and accessories. Try on layers sit inside apps and websites, on in store kiosks and, increasingly, on social platforms. For marketers, one draw is measurability. Every virtual application is a data point: which shades are tried most often, how many trials lead to cart additions, how long a shopper spends experimenting before they decide.
Mishra and other executives point to this blend of engagement and outcome as a reason brands are willing to invest. If a try on journey both entertains and reliably pushes a user closer to purchase, it earns a place in the core stack. The geographic reach is significant too. Because the experience runs on a smartphone, a shopper in a tier 3 town can access a similar level of advice and experimentation as someone in a metro store.
A newer layer in beauty martech is the “AI esthetician”, conversational systems that sit on websites, apps or messaging platforms and guide users through diagnosis, routine building and product selection. These differ from basic chatbots because they rely on multimodal and profile data, not only rules. They can combine questionnaire responses with scanner outputs and purchase history to make more targeted suggestions.
Some global brands deploy these as named personalities with distinct tones of voice. In India, early versions are more functional, often living inside WhatsApp flows or brand apps. They answer questions about ingredient combinations, routine order, or whether a given serum can be layered with an acid. For marketers, they offer two advantages. First, they provide round the clock hand holding in a category where regimen discipline affects outcomes. Second, they create structured logs of concerns and questions that can feed back into product development and content planning.
Experts caution that these systems need clear boundaries. An AI esthetician nudging a user to apply sunscreen more regularly comes across as helpful. A system suggesting treatments that border on medical advice, without clear disclaimers, is riskier. Legal and regulatory teams in large beauty companies are therefore closely involved in designing prompts, hand offs to human advisors and escalation rules.
For Indian marketers, the common thread across skin analyzers, virtual try ons and AI estheticians is the shift from one directional campaigns to interactive journeys. AI tools make it possible to respond to what a customer shows and says in the moment, rather than targeting only based on demographics or past purchases.
Abhishek Gupta, Senior Vice President for Growth at Honasa Consumer, has said that predictive analytics and AI guided journeys work because they help consumers choose the right product and help the brand convert and retain them. His comment reflects a broader view in the industry that AI’s value is not in novelty but in reducing the friction between intent and purchase.
Mishra’s focus on accessibility highlights another important angle. For many aspirational shoppers in smaller cities, physical access to multi brand beauty stores or dermatologists is limited. Virtual tools that work on mid range smartphones offer a version of that experience at home. This is one reason providers talk about bridging urban rural gaps and supporting women owned beauty businesses, not only large chains.
Global consultancies and Indian research firms also point to category growth as a driver of experimentation. The beauty and personal care market in India is expected to log double digit annual growth this decade, and separate estimates place the broader beauty devices segment in the billions of dollars by 2030. In that environment, brands see AI as a way to differentiate without simply lowering prices.
Behind the enthusiasm, practitioners acknowledge open questions. One is inclusivity. AI models trained largely on lighter skin tones can misdiagnose or mis shade Indian users. Beauty tech providers say they are expanding training datasets and working with dermatology partners, but independent audits remain rare.
Another is data governance. Skin analyzers and AI estheticians handle highly personal information, including close up images and self reported concerns. Marketers must navigate consent under evolving data protection rules, clarify how long such data is stored and who can access it, and avoid repurposing it in ways consumers would find intrusive.
A third is creative sameness. If many brands draw on similar diagnostic tools and recommendation engines, the risk is that experiences start to feel interchangeable. Some marketers are therefore experimenting with distinct narrative layers on top of shared technology, for example by pairing AI recommendations with human content creators or beauty advisors in live sessions.
For now, the trajectory is clear. As beauty and personal care spending grows, AI is moving from pilot projects into the daily fabric of how brands in India and globally attract, advise and retain customers. Skin analyzers replace some of the role once played by in store consultants. Virtual try ons make experimentation possible without a tester in sight. AI estheticians extend the consultation beyond store hours.
Whether these tools deepen trust or feel like over automation will depend less on the underlying models and more on how marketers use them: transparently, with realistic claims, and with room left for human judgment and preference. In a category built on emotion and self expression, that balance may decide which brands benefit most from the latest wave of beauty tech.
Disclaimer: All data points and statistics are attributed to published research studies and verified market research. All quotes are either sourced directly or attributed to public statements.