This new AI just might make online shopping fun again
If you're searching for a new blazer or dress, you'll type keywords into Google or a retailer's search bar, then scan through rows of inventory. Often, the first results you'll see will be posts sponsored by brands, rather than results tailored to your needs. But even though shopping for fashion on the internet is laborious and clunky, it is now the status quo: Some 48% of all fashion retail sales worldwide happen on e-commerce, equivalent to $883.1 billion in revenue.
Retail veteran Julie Bornstein, who helped build e-commerce platforms for Sephora and Stitch Fix, wants to transform the way you shop online. Today, she launches a new platform called Daydream, an AI-powered chat-based shopping agent devoted specifically to fashion. Daydream's founding team brings together executives who previously worked at Google, Microsoft, Meta, Amazon, Farfetch, and other tech firms. It raised $50 million in seed funding from Forerunner Ventures, Index Ventures, Tre Ventures, and Google Ventures.
To use Daydream, you take a short quiz to ensure that the agent tailors results to your taste and sizing. Then, you can engage with the AI agent like you might with a human stylist, asking questions and providing specifics about what you're looking for: 'I need a new dress for a holiday in Barcelona,' or 'Can you find me heels for a board meeting that are comfortable enough so I can walk to work?' The platform will deliver results from an inventory of 2 million immediately available products from 8,000 brands, including Balenciaga, Nike, Khaite, Mytheresa, Uniqlo, and Dôen. These brands pay Daydream a commission when a customer buys a product, which allows the platform to remain free to users.
Like all AI models, Daydream is designed to keep learning as more users engage with it, both by understanding broad trends across the population as well as how to tailor products to an individual's shopping habits. In some ways, the most exciting possibilities are just around the corner. 'We're already thinking about what we can do with this technology,' says Bornstein. 'Imagine an agent that already knows every single item in your closet and can suggest items that can pair with what you already own.'
Taking the Pain Out of Online Shopping
Bornstein has spent her career trying to perfect the art of e-commerce. In the early 2000s, she helped retailers like Nordstrom and Urban Outfitters build their nascent online websites. She led Sephora's digital efforts before serving as COO of Stitch Fix, an online styling service that famously used a Netflix-like algorithm to identify the outfits its consumers might want.
In 2018, she decided to strike out on her own. She launched an app called The Yes that was designed to foster inspiration and discovery—something she felt was missing on most e-commerce sites that rely on consumers to search for and articulate what they want. The Yes created a social-media-like feed, where you could connect with friends and be served interesting products you might not have found on your own. Four years later, Pinterest acquired it for an undisclosed sum.
Over the past few years, however, generative AI has loomed over the tech world. In 2023, Bornstein began working on Daydream, considering how AI could transform the shopping experience. 'It was clear to me that when ChatGPT launched, it would open up a whole new set of possibilities,' she says.
Current AI agents like ChatGPT aren't tailored to shopping for clothing, though. If you ask the platform to help you look for a dress for a romantic dinner in Montreal in mid-July, it will scour the internet for options, but it has no way of identifying quality. Within a given price point, it will pull from no-name labels on Amazon and random brands known for making knockoffs. When it comes to taste and styling, ChatGPT has no sense of curation. It pulls from every blog, retail website, and influencer.
'ChatGPT is like a jack-of-all-trades, and it can respond to questions about clothing,' says Kirsten Green, founder of Forerunner Ventures, one of Daydream's investors. 'But at some point, you need some expertise to ensure that an AI is giving you really helpful results, whether it relates to fashion or biotech.'
Bornstein wanted to create an AI that had a more sophisticated sense of what consumers are looking for in terms of fashion and styling. For one thing, Daydream partners with 8,000 brands and has analyzed upwards of 2 million products. Further, Daydream's developers have brought nuance to the search process, helping the AI distinguish between high-end brands like Balenciaga and Chloé, versus mass-market brands like Uniqlo.
Also, with the help of developers, Daydream analyzes details like silhouette, fabric, and drape in a way that is more specific than general AI platforms. It incorporates information about sizing and fit based on reviews and data about the brand, so recommendations can be fully customized to the user. 'We have been looking at images of clothing to identify both its objective and subjective attributes,' Bornstein says. 'You need to be able to synthesize all of this information and make sure it is standardized.'
Green notes that none of this is easy. 'This is the power of leveraging training models, understanding the details of product categories that have a lot of minute descriptors, understanding how to read images,' she says.
The result is an AI agent that approximates a human stylist. Bornstein promises that Daydream will better understand the nuances of customers' questions, offering more expertise around trends and personal taste. This means that two people might ask the same question and receive different results. It will pull from well-known brands, tailoring results to your budget. As you click on items you like, the AI will refine options. You can also pick one item, such as a blue dress, and say that you like the silhouette but would prefer it in red. It's also possible to upload an image of a dress you like and find similar options.
Bornstein points out that some consumers like being able to have lots of choices, whereas others find that prospect overwhelming. Daydream's AI can adapt to either approach. 'Some people will just want the five best options for a particular dress or blazer,' she says. 'Daydream can do this too.'
The Future of Fashion
For Bornstein, launching Daydream is just the first step in her vision of transforming online clothes shopping. For one thing, AI will allow an unprecedented level of customization, tailoring results to each user's individual tastes, budget, and body shape.
In the near future, Bornstein imagines a technology that already knows everything that's in your closet. Imagine Cher's closet from Clueless, which came with a computer that identified each piece of clothing and could coordinate looks. This isn't so far away, Bornstein says. 'We're already thinking about how we could identify what is already in your closet, by looking at your credit card statements or your shopping history with a retailer,' she says. 'Or you could imagine an AI tool that would quickly scan your closet with a camera and identify every item.'
A technology like this could serve as a useful tool for helping people get dressed in the morning by suggesting what to wear given their plans for the day and the weather. It could also integrate into a broader shopping platform, like Daydream, allowing the AI to get a sense of a user's aesthetic and size before recommending items that fit into their existing wardrobe. 'Sometimes there's a pair of shorts you might have that you would get so much more use out of if you just had the right top,' Bornstein notes as an example. 'This would allow us to suggest items that someone really needs and doesn't just double up on something else they already have.'
It's clear that a transformation is around the corner, as people increasingly incorporate AI into their lives. Green says she's heard from many retailers whose search box is becoming useless because customers are treating it like an AI agent and asking it natural language questions, rather than typing in keywords. 'Really great startups sometimes struggle because customers aren't ready for the technology,' she says. 'This isn't the case here. I think we're all ready for something better than a search bar.'
The extended deadline for Fast Company's Next Big Things in Tech Awards is this Friday, June 27, at 11:59 p.m. PT. Apply today.
Hashtags
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
CBS News
25 minutes ago
- CBS News
Is a fixed or variable annuity the better choice this August?
Annuities aren't exactly flashy, but these retirement tools have been quietly gaining popularity over the past year, and for good reason. With inflation ticking back up over the last couple of months and interest rates still elevated, and with stock market volatility becoming the norm rather than the exception, a large number of soon-to-be retirees are trying to find ways to better secure their retirement portfolios. And, many are turning to annuities, in particular, as a safe way to lock in guaranteed retirement income. But if you've started exploring your annuity options, you've likely run into a key question: Should you go with a fixed annuity or a variable one? After all, both annuity options are designed to provide long-term income, so they can both be worth considering as part of a well-balanced retirement portfolio. However, these two annuity options operate in very different ways, and in today's unusual economic climate, where questions about interest rates and inflation loom large, the distinction matters more than ever. So, is a fixed or variable annuity the smarter move this August? Here's how each product fits into today's climate — and how you can determine which one makes sense for your situation. Find out how to add an annuity to your retirement portfolio today. Both fixed and variable annuities have distinct advantages in today's market. The better option, though, depends largely on your risk tolerance, time horizon and how you view the current interest rate environment. If you're prioritizing safety and guaranteed returns, fixed annuities may offer a strong value proposition this month, largely due to the current interest rate environment. Because rates remain elevated, insurance companies are offering competitive fixed annuity yields right now, and it's easy to find fixed annuities with rates of 5.5% to 6.5% or higher. High rates aren't the only benefit of fixed annuities, however. These types of annuities function similarly to a CD: You invest a lump sum and receive a predictable, set rate of return for a specific period. That means there's no exposure to market or rate volatility, which can be comforting for near-retirees or conservative savers who want to lock in today's higher rates before they fall. In fact, many fixed annuities are outperforming traditional fixed-income options like Treasury bonds or high-yield savings accounts right now. And, the Fed has signaled that rate cuts may be coming later in the year, so locking in a solid guaranteed return this August could be a timely move. Learn more about annuities and the benefits of buying one now. Variable annuities, on the other hand, present a compelling alternative for those willing to accept market exposure in exchange for growth potential. Unlike fixed products that cap your returns, variable annuities allow you to participate in market gains through various investment sub-accounts, potentially delivering returns that far exceed what fixed rates can offer. And, while it may seem counterintuitive, the current high-rate environment actually strengthens the case for variable annuities. As rates decline, as is expected to happen later this year, the opportunity cost of choosing guaranteed returns over market-linked growth becomes more pronounced. Variable annuities also offer more flexibility in terms of investment options and income timing, allowing you to adjust your strategy as market conditions change. For younger investors or those with longer time horizons, variable annuities can provide inflation protection that fixed products simply cannot match. While a 5.5% guaranteed rate sounds appealing today, and while it can be a great rate over the long term, it's still important to remember that inflation can erode purchasing power over time. But variable products, particularly those with equity exposure, historically provide better long-term inflation hedging. If you're trying to decide whether a fixed or variable annuity is the better option for you, start by asking these key questions: There's not one annuity option that works best for everyone, especially in today's economic environment. Fixed annuities could be a strong play in August for those seeking guaranteed returns before interest rates potentially fall. Variable annuities, meanwhile, may appeal to those who want to tap into the market's upside and can tolerate the risk that comes with it. Whether you're approaching retirement or just trying to create future income streams, though, the key is choosing the annuity that aligns with your goals and risk comfort. And if you're considering either this month, now is a good time to shop around, because today's rates and market conditions won't last forever.
Forbes
25 minutes ago
- Forbes
AI Models Replace Fashion Models And Business Models
Fashion modeling faces significant technological disruption as AI platforms expand beyond basic model generation into comprehensive content creation systems. Precedence Research projects the AI fashion market will reach $60 billion by 2034, with annual growth rates of nearly 40%. The transformation happening in fashion offers a roadmap for how other industries can leverage AI not just for efficiency but for fundamental business model innovation. Fashion's combination of creative content, rapid market cycles, and direct consumer feedback loops exists across sectors from hospitality to financial services. This shift aligns what's happening in venture capital, where data-driven methodologies are transforming traditional investment paradigms—a movement reminiscent of how algorithmic trading revolutionized public markets. AI is Now More Than a Fashion Accessory More recently, leading retailers have progressed from testing AI to full deployment. H&M announced in March 2025 that it plans to create 30 digital versions of existing models. Levi Strauss began experimenting with AI models in 2023 as part of diversity initiatives, and Burberry introduced immersive virtual fitting rooms, among other innovations, that offer personalized experiences. Sara Ziff, who founded the Model Alliance, expressed concerns that apply across industries: "In an industry that has historically been a backwater for workers' rights, H&M's new initiative raises critical questions about consent and compensation." The Fashion Workers Act in New York, effective June 19, 2025, now requires explicit consent from models before their likeness can be used in AI applications. Learning From Failure: A Revenue-First AI Approach Ella Zhang's experience with Creati highlights a critical lesson for AI implementation. Her first AI platform attracted 7 million users but generated no revenue. This aligns with McKinsey Senior Partner Gemma D'Auria's assessment that many companies lag "way behind" in translating analytics into business value. "The product validation should come from revenue, not just users," Zhang explained. "If they're not paying, they're telling you something's wrong." This principle applies universally. Zhang conducted more than 300 customer interviews before discovering that companies were "still spending $70,000 to $100,000 on agencies just for a launch video," with costs driven by creative ideation rather than production. Zhang repositioned Creati as a comprehensive ideation engine generating both digital models and viral marketing strategies. The company now reports revenue exceeding $13 million, demonstrating the value of solving real business problems rather than showcasing technical capabilities. Cross-Industry Application of an Element-Based Architecture Creati's technical approach centers on what Zhang calls an "element-based" architecture, allowing users to modify products, backgrounds, and styles in real time while maintaining visual consistency. This mirrors how successful viral content works: remixable components that maintain brand identity. More importantly, this represents a shift from AI tools to AI agents, systems that work autonomously on behalf of users rather than merely assisting them. Creati's platform generates more than images; it creates viral marketing strategies, optimizes based on performance data, and continuously improves the output. This agent-based approach transforms AI from a productivity tool into a strategic partner. Financial services organizations also could transform customer acquisition using similar viral content engines. Instead of static rate comparisons, banks could deploy AI agents that generate thousands of personalized financial journey videos, each showing different life scenarios (first home, retirement, college savings) with consistent brand messaging but customized visual narratives that resonate with specific demographics. The agent would autonomously test, learn, and optimize which narratives drive conversions. Pharmaceutical companies also face similar content challenges when explaining complex treatments. An element-based approach would allow them to generate patient education videos that swap out demographics, conditions, and treatment scenarios while maintaining medical accuracy. The same drug interaction could be explained through culturally relevant scenarios for different communities, increasing comprehension and compliance. Similarly, many software companies struggle to demonstrate product value across a diversity of use cases. Creati's model suggests that such companies could generate viral demonstration videos where the core functionality remains constant but industry contexts, user personas, and problem scenarios adapt dynamically. "Consistency is crucial for e-commerce owners when selling physical goods," Zhang noted. This principle becomes even more critical when the "product" is trust—whether in financial services, healthcare, or enterprise software. Data Lakes as a Competitive Moat The Creati platform also creates a competitive advantage through an integrated data infrastructure. It automatically connects with advertising platforms to track performance metrics, then optimizes content. This demonstrates how information assets become competitive moats in the digital economy. Unlike physical assets that depreciate, data gains value through use and integration. The viral content space amplifies this effect because success metrics are immediately measurable through engagement rates and conversions. Similar dynamics drove the algorithmic trading revolution that transformed financial markets, where firms that integrated data feedback loops gained insurmountable advantages over traditional traders. Insurance companies, for example, could adopt this approach to track which risk scenarios generate the most policy inquiries and automatically generate more content variations around successful themes. Streaming services could analyze which preview styles drive subscriptions, then generate thousands of variations for different audience segments. The key is that each iteration makes the system smarter, creating barriers competitors cannot easily overcome, much like how quantitative hedge funds can dominate markets through data accumulation and algorithmic refinement. Zhang's philosophy guides successful adoption: "In a space dominated by demos and prototypes, Creati stands out by doing the hard thing: building something people will pay for." This revenue-first approach demands identifying processes where human creativity costs exceed value delivered. Viral content creation represents one such area across industries. Building integrated feedback loops ensures continuous improvement rather than static automation. Element-based architectures enable mass customization within brand constraints. Value-sharing models align AI benefits with creative professionals rather than displacing them entirely. The Virtual AI Workforce: An Economic Reality The Bureau of Labor Statistics counts 3600 professional models in the United States. Naomi Ellis of Arizona State University argues that professionals who master AI tools will maintain advantages rather than face replacement. The fashion industry's transition offers concrete models. H&M grants models ownership of their digital twins, creating ongoing revenue streams. And Creati's marketplace enables content creators to earn from viral templates they design. This shift from one-time payment to recurring revenue could transform creative industries. These new 'infonomics' prove compelling. A professional fashion shoot in the US typically costs $10,000–$30,000 for a day's production (with luxury editorials occasionally topping $50,000 for exclusive campaigns). Daily model rates usually range from $500 to $5,000, with elite talent earning more. While creative agencies may charge $10,000–$50,000 for digital-first viral concepts—and sometimes up to $100,000 for major productions—a new wave of AI platforms offers nearly unlimited, studio-quality fashion content from just $29–$59 per month, drastically reducing barriers for brands and creators. Street Vogue exemplifies transformation potential. Within six months of adopting Creati, the company grew from one to 20 employees and multiplied revenue twelvefold. The key: redirecting production budgets toward distribution and paid amplification of AI-generated content. However, New York's Fashion Workers Act establishes compliance restrictions such as requirements for explicit consent, detailed usage parameters, and separate AI agreements. These will likely manifest in other industries as well, such as healthcare (patient data), finance (algorithmic decisions), and employment (automated evaluations). Regulatory compliance must be built into architectures from inception. And ideally, workforce transformation demands proactive planning and value-sharing models. Market Validation of AI-Based Approaches Several companies compete in this market with distinct approaches. Botika converts flat product images into on-model photography, creates inclusive digital avatars for 3D design integration, and emphasizes bulk processing. However, combining viral ideation with content generation seems to be the next frontier. The broader context reveals significant opportunity. According to Gartner, "91% of retail IT leaders are prioritizing AI as the top technology to implement by 2026." Yet challenges remain: "Despite an average spend of $1.9 million on GenAI initiatives in 2024, less than 30% of AI leaders report their CEOs are happy with AI investment return." This gap between investment Satisfaction indicates that the market requires solutions which provide measurable business value rather than merely technical capabilities. McKinsey's analysis adds perspective on creative applications: "Up to 25 percent of the potential of AI in fashion will come from the creative side," notes the consultancy. Market research firm projected last year that "the integration of AI and machine learning in fashion retail could result in a significant 40% reduction in inventory costs." Other brands have also validated AI-based approaches. The online fashion retailers Shein and Cider have been early adopters of Creati, virtual influencer Lil Miquela generates $11 million annually according to Storyclash, and H&M's digital twin initiative seems to signal industry-wide acceptance. Taking a Page Out of Fashion Every industry faces the same challenge as the fashion industry: leveraging AI for fundamental innovation rather than just incremental improvement. The shift from AI tools to AI agents that can act autonomously marks a critical evolution—systems that do more than assist but rather actively work on behalf of organizations to achieve strategic objectives. Success requires solving expensive problems with measurable ROI. Organizations must create systems that improve through use, building competitive moats from data. The pattern is similar to how algorithmic trading transformed finance: early adopters who built data feedback loops and autonomous trading systems gained advantages that traditional firms could never overcome. Zhang's vision extends beyond fashion: "Creati will be the ideation engine for everything." This positions AI as a universal creative platform rather than task automation. Companies understanding this distinction will transform value propositions and entire business models, not just operations. The technology exists and the economics are undeniable. Fashion's AI transformation offers a blueprint for other industries. Organizations that adapt these lessons to their unique contexts will define the digital economy's future. Those awaiting perfect clarity or that are waylaid by compliance, labor, or other roadblocks may discover competitors have already built insurmountable advantages through integrated AI platforms—ones that generate both ideas and content that shift the economics of their industry.
Yahoo
an hour ago
- Yahoo
OPEC+ Just Flooded the Market--Now It Might Pull the Plug
OPEC+'s oil strategy just took a sharp turn and it might not be the last. Over the weekend, the group finalized the return of 2.2 million barrels per day to the global market, wrapping up its post-2023 unwind. But insiders say this might just be the setup for the next move. Delegates emphasized that everything is still on the table: more increases, a pause, or even a full reversal. The group's next meeting is scheduled for September 7 and it could mark the start of another major pivot. Warning! GuruFocus has detected 9 Warning Signs with GS. On paper, demand has held up. But beneath the surface, cracks are forming. The International Energy Agency projects a 2 million barrel-per-day surplus by Q4, driven by slowing Chinese growth and swelling supply from the Americas. Crude futures are already down 6.6% this year to under $70 per barrel, and Wall Street doesn't look optimistic with Goldman Sachs (NYSE:GS) and JPMorgan (NYSE:JPM) warning prices could drift toward $60. That's well below what many OPEC+ members need to balance their budgets. Most traders Bloomberg surveyed expect the group to hold steady for now. But if U.S. supply slips or macro conditions turn, analysts like Eurasia Group's Greg Brew say more barrels could still come back online. Overlay that with rising geopolitical heat, and the picture gets even murkier. President Donald Trump is ramping up pressure on Russia over Ukraine, threatening secondary sanctions on buyers of Russian oil. Last week, Russian Deputy Prime Minister Alexander Novak made a high-profile visit to Riyadh, underscoring Moscow's ties with Saudi Arabia. But the tension is real and growing. Analysts say the alliance could face its toughest test yet: defend market share by bringing back the final 1.66 million barrels per day still offline, or maintain unity under increasing global pressure. Either way, September's meeting could be a turning point for global oil markets. This article first appeared on GuruFocus. Sign in to access your portfolio
