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U.S. President Donald Trump’s sweeping tax-cut legislation would effectively transfer wealth from younger Americans to older generations, nonpartisan analysts say. Though the bill contains tax breaks for parents, newborns, private-school students and other younger Americans, those benefits would be outweighed by the trillions of dollars it would add to the $36.2 trillion national debt, they say. That could push down economic growth over the long term and leave younger people saddled with higher taxes and mortgage payments. “Future generations are kind of left holding the bag,” said Kent Smetters, director of the Penn Wharton Budget Model. The nonpartisan research organization found that a 40-year-old earning close to the median income would effectively lose $7,500 over the course of a lifetime if the bill became law. A 70-year-old with the same income, by contrast, would end up $17,500 richer. Several factors contribute to this disparity. Younger workers, who typically earn less, would not benefit as much from the bill’s income tax cuts compared to those at the peak of their earning years. They would also be more exposed to cutbacks in student aid and the Medicaid health program, which covers 4 out of 10 hospital births in the United States. “In the short term the benefits are certainly tilted towards higher earners, which is often a good proxy for age,” said Jessica Riedl of the conservative Manhattan Institute. But the biggest factor, analysts say, is the $3 trillion the bill would add to the national debt. That is likely to push up interest rates in the years to come and require the government to devote a growing portion of its budget to debt service rather than other purposes. “There is an obvious intergenerational transfer here,” said John Ricco of the Yale Budget Lab, which found that the bill would add $4,000 to the annual cost of a home mortgage in the year 2055, when today’s newborns will be 30 years old. Republican lawmakers say the bill, which passed the House of Representatives and is now pending in the Senate, would help younger Americans by putting Medicaid on a more sustainable footing and boosting economic growth and entrepreneurship, which would help younger people entering the workforce. The bill also follows through on Trump’s campaign promises by carving out new tax breaks for tipped income and overtime pay, which Republicans say could help younger workers in service and hourly wage jobs. Savings accounts The bill also would set up $1,000 savings accounts for newborns and expand a child tax break, though the details differ between the House and Senate versions of the bill. Number two House Republican Representative Steve Scalise said after the bill’s passage in May that the legislation would increase take-home pay for a median income household with two children by $4,000 to $5,000. That calculation, however, does not factor in the increased costs many lower- and middle-income families would have to pay for health care, student loans, and groceries due to the bill’s cutbacks in those areas. The Congressional Budget Office and other outside analysts have found that those costs would outweigh any savings those households might gain from tax cuts, while the child tax credit and other targeted tax breaks also would not be fully available to low-income families. That pattern holds true for poor Americans of all ages. The bill includes a targeted tax break for people over 65 promised by Trump during last year’s election, but many do not pay enough income tax to qualify for it, said Brendan Duke of the left-leaning Center on Budget and Policy Priorities. “The tax cuts basically do nothing for the lower-income half of seniors,” he said. Still, those seniors benefit from another Trump campaign promise, as the bill spares Medicare, the health plan for seniors, and Social Security, the U.S. pension program, from the sort of cost-cutting it applies to Medicaid. Medicare and Social Security are growing rapidly as the population ages, crowding out other government spending, and are projected to run short of funds in 2033. But Trump and his Democratic rivals have both vowed to shield the two politically popular programs from restructuring, which will leave future generations to confront the problem. “I think ultimately Republican and Democratic lawmakers have been engaged in intergenerational theft for a long time,” Riedl said. Andy Sullivan, Reuters
Category:
E-Commerce
Let’s face it. Shopping for clothes online is a drag. The online shopping experience hasn’t changed much since Amazon started selling books online three decades ago. 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. Julie Bornstein [Photo: Cristopher Wu/Daydream] 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 youre 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. [Image: Daydream] 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 discoverysomething 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. [Image: Daydream] “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 Daydreams 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 analyzedupwards 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.” [Image: Daydream] 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. Its 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.” [Image: Daydream] 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 thats 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.”
Category:
E-Commerce
When Tony Bates became chairman and CEO of Genesys in 2019, the company was already a global leader in contact center software. But Bates was determined to evolve its role in a rapidly changing tech landscape. Throughout his careerfrom transforming Skype into a communications powerhouse to leading Ciscos $20 billion enterprise businessBates has built a reputation for guiding companies through pivotal industry shifts. Now, he is steering Genesys to the forefront of what may be the next defining wave of enterprise technology: agentic AI. Today, Genesys launched Cloud AI Studio, a new platform designed to help businesses create, manage, and scale AI-powered customer experiences. Its first release, AI Guides, allows teams to build autonomous AI agents without writing a single line of code. These agents can operate across departments, execute tasks, and trigger workflows, all governed by clear business rules. Bates sees Cloud AI Studio as more than just a product launch. It is part of a larger effort to create a responsible, no-code environment for building semi-autonomous AI agents that can drive meaningful interactions at scale. Unlike past technology waves that improved speed or scale, agentic AI can orchestrate meaningful experiences that feel personal and emotionally intelligent at scale, Bates tells Fast Company. Cloud AI Studio enables someone with deep knowledge of the customer journey but no coding skills to build an intelligent agent by describing its purpose using natural language, by uploading existing documentation, or by having the system learn from successful human agents. A Tech CEO Who Understands Customer Needs As SVP and general manager at Cisco, Bates oversaw $20 billion in annual revenue and more than 12,000 employees. At Skype, he grew the user base to over 170 million, which led to an $8.5 billion acquisition by Microsoft. There, he integrated Skype across flagship products from Windows to Outlook. That same approach of integration, scale, and strategic vision is now driving Genesyss cloud-first reinvention. Under Batess leadership, the company has evolved into a modern AI orchestration platform, supporting nearly 6,000 organizations in more than 100 countries. Since he became CEO, Genesys has also raised more than $580 million in funding. At Skype, I saw how peoples expectations of communication could shift quickly, but only if the experience was intuitive, secure, and reliable. The same is true with AI, says Bates. Our AI strategy (at Genesys) is rooted in explainability, transparency and control. Whether its how an AI decision is made or how outputs are governed, people need to trust that AI is working with them. Without trust, scale isnt possible. An IBM study found that 80% of business leaders view ethics, bias, or explainability as major obstacles to AI adoption. A new McKinsey report shows that more than 80% of companies using generative AI have yet to achieve meaningful productivity or ROI gains, largely because they are limited to copilots, not true AI agents. With public trust and enterprise adoption still fragile, robust governance is becoming essential for any serious AI deployment. Genesys is positioning its new AI Guides as a direct response to these concerns. The solution offers configurable guardrails and model-agnostic architecture that allow teams to test, refine, and safely deploy agentic AI in high-stakes workflows. I see companies struggle with realizing ROI when their AI lacks this built-in governance, doesnt gracefully move to a human-supported experience when needed, or cant be easily set up or managed over time, Bates says. To unlock the full potential of AI, companies need the foundation and flexibility to apply it thoughtfully and at scale. AI Guides are designed to overcome the barriers by enabling orchestrated, semi-autonomous action with built-in governance. What sets Batess vision apart is his belief that AI experiences must be not only fast and agile but also personalized and emotionally intelligent. Our goal is to ensure empathy doesnt get sidelined with agentic AI, but amplified. I call it empathy in action, he says. We can now use agentic AI to react to emotional cues like tone, context, and sentiment and guide how decisions are made in real time. Through AI Guides, organizations will be able to simulate an AIs behavior before launch, maintain oversight throughout the lifecycle, and have firm paths for human escalation. Cloud-first, Future-ready Agentic AI The companys five-year roadmap includes migrating customers from on-premises systems, expanding the Genesys Cloud CX platform, and achieving Level 4 AI-powered orchestration, where intelligent agents operate with semi-autonomy under business-defined controls. Generative AI can deliver significant ROI if done right. Companies are now identifying use cases that rely heavily on things like troubleshooting, summarizations, and recommendations to automate conversations with virtual agents or make their employees more efficient via copilots, says ates. With agentic AI, we can finally address a long-standing tradeoff between business-first models that prioritize operational efficiency but erode consumer loyalty, and people-first approaches that delight customers but are too costly to sustain. Imagine a virtual agent that doesnt just answer a billing question, but also updates backend systems, checks inventory, and reschedules a delivery, all without human intervention. That is the future Genesys is betting on. Bates believes this potential will be especially transformative for industries with complex customer interactions such as healthcare, finance, and public services. These sectors struggle with agility because of compliance and operational complexity, he says. Genesys Cloud also integrates with proprietary and open-source models like Amazon Bedrock so customers have extensibility to innovate with AI for their specific needs without compromising safety, oversight, or performance. While the efficiency gains from agentic AI will be significant, Bates stresses that enterprise leaders must view this transformation as a long-term journey that drives experience-led growth. Ultimately, its about how we use AI within the rules we define while driving significant new business value, says Bates. Would you rather lead your industry taking advantage of transformational technologies early and create new differentiation, or choose to wait longer, risking being pushed aside by new and old competitors? Those who embrace agentic AI early will be the winners of the future, delivering empathetic experiences at the lowest cost possible.
Category:
E-Commerce
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