The U.S. stock market is flirting with its all-time high on Friday.
The S&P 500 rose 0.1% and was on track earlier in the day to squeak past its record closing level, which was set in October. The Dow Jones Industrial Average was up 69 points, or 0.1%, as of 12:29 p.m. Eastern time, and the Nasdaq composite was 0.1% higher.
If the S&P 500 finishes the day at a record, it would mark the latest time the U.S. stock market has powered past what appeared to be a debilitating set of worries. Most recently, those concerns centered on what the Federal Reserve will do with interest rates, whether too many dollars are flowing into artificial-intelligence technology, and if sharp drops for cryptocurrencies would bleed over into other markets.
Renewed hopes for a cut to interest rates by the Fed at its meeting next week helped stocks recover those losses, which included some of their worst days since their sell-off during April. So did a continuing parade of companies saying they’re making bigger profits than analysts had expected.
Ulta Beauty helped lead the market on Friday and jumped 13.2% after the retailer reported stronger profit and revenue for the latest quarter than expected. CEO Kecia Steelman said its customers are broadly feeling pressure, but Ulta saw growth across its categories, particularly in e-commerce. It raised its forecast for revenue over the full year.
Another encouraging signal for the holiday shopping season came from Victorias Secret & Co. It delivered a milder loss for the latest quarter than analysts expected, and it likewise raised its forecast for sales over the full year. Its stock rallied 11.5%.
Warner Bros. Discovery was also strong and rose 2.3%. Netflix said it would buy Warner Bros. for $72 billion in cash and stock following its pending split from Discovery Global.
The deal for the company behind HBO Max, Casablanca and Harry Potter is not a sure thing, though. It could raise fears at the U.S. government about too much industry power residing at Netflix. Shares of Netflix initially fell more than 5% after the deal was announced, then briefly erased all of the loss before falling again, by 3.2%.
Paramount Skydance, which earlier had been seen as a front-runner to buy Warner Bros., fell 7.6%.
Also on the losing end of Wall Street was SoFi Technologies. The financial technology company fell 7.2% to $27.73 after saying it would add $1.5 billion worth of its stock into the market in order to raise cash. It’s selling the stock at a price of $27.50 per share.
The U.S. stock market broadly has been much quieter this week, a respite following earlier weeks of sharp and scary swings.
After some back and forth, the widespread expectation among traders is that the Fed will cut its main interest rate next week in hopes of shoring up the slowing U.S. job market. If it does, that would be the third cut of the year.
Investors love lower interest rates because they boost prices for investments and can juice the economy. The downside is that they can worsen inflation, which is stubbornly remaining above the Feds 2% target.
Economic reports released on Friday did little to change expectations for a coming cut. One said that an underlying measure of inflation that the Fed prefers to use was at 2.8% in September, exactly as economists expected.
A separate report said U.S. consumers appear to be downgrading their expectations for inflation coming in the near future. They’re now forecasting 4.1% inflation for the year ahead, down from their forecast of 4.5% last month, according to the University of Michigan.
That’s the lowest such reading since January, which is important because heightened expectations for inflation can create a vicious cycle that only worsens inflation.
In the bond market, Treasury yields held relatively steady. The yield on the 10-year Treasury rose to 4.13% from 4.11% late Thursday.
In stock markets abroad, indexes were mixed across much of Europe and rose in Asia Friday.
Germanys DAX returned 0.6%, and South Koreas Kospi jumped 1.8% for two of the worlds bigger gains.
Tokyos Nikkei 225 fell 1.1% after data showed household spending in Japan fell 3.0% in October from a year earlier. It was the sharpest drop since January 2024. Japanese markets have been shaky recently after the Bank of Japan hinted that hikes to interest rates may be coming.
By Stan Choe, AP business writer
AP Writer Teresa Cerojano contributed.
It is a relatively rare phenomenon: While the stock market continues to experience record gains (the S&P 500 is up over 16% this year), Bitcoin and other cryptocurrencies continue to struggle, making it the first time the crypto and stock markets have split since 2014, Bloomberg reported.
That split, with Bitcoin down while stock markets soar, is somewhat unusual. On midday Friday, at the time of this writing, the digital cryptocurrency (BTC) was trading down over 4%, hovering around $88,945far below its record high of over $125,000, but still above a recent low of $85,000 (down almost 30% from the high).
Here’s what to know.
Why is the split between crypto markets and stock markets unusual?
While Bitcoin is known for its volatility, historically, the digital currency and stocks have traditionally risen and fallen together.
So, why has there been a crypto sell off? What is contributing to the drop in investor confidence?
Some of what boosted confidence in the coin was the Trump administration’s early embrace of crypto, ushering in crypto-friendly regulations.
However, as Fast Company has previously reported, a few different micro and macroeconomic factors have started to spook investors, who are pulling back from the more volatile digital currency.
These factors include higher inflation; shifting interest rates; a dampening enthusiasm for AI-related stocks over fears of an AI bubble; and growing concerns over the widening gap between low-income and wealthy Americans, in what is shaping up to be a “K-shaped economy.”
Remind me, what exactly is Bitcoin, anyway?
Bitcoin is a type of cryptocurrency. Unlike a standard currencysuch as the U.S. dollar or the European Union euroit only exists in digital form and operates without government or banking oversight, traded peer-to-peer, making it harder to trace. Instead, Bitcoin uses a decentralized blockchain ledger to verify and securely record transactions.
The U.S. Treasury Department imposed a $7.1 million fine on a New York-based property management firm Thursday, accusing it of violating sanctions by managing luxury real estate properties for oligarch Oleg Deripaska, who has close ties to Russian President Vladimir Putin.
Treasurys Office of Foreign Assets Control said Gracetown Inc. had received 24 payments between April 2018 and May 2020 totaling $31,250 on behalf of a company owned by Deripaska. OFAC says it gave Gracetown notice that dealings with Deripaska were prohibited, but the firm proceeded anyway.
Justice Department filings from 2022 connect Gracetown Inc. with U.K. businessman Graham Bonham-Carter, who was arrested in October 2022 for conspiracy to violate U.S. sanctions imposed on Deripaska as well as for wire fraud connected to funding Deripaskas U.S. properties and efforts to expatriate the oligarchs artwork to New York.
A lawyer who has represented Deripaska previously didn’t immediately respond to a request for comment. Gracetown couldn’t immediately be reached for comment.
Deripaska has faced economic sanctions since 2018, when the Treasury Department accused him of acting for or on behalf of a senior Russian official and operating in the energy sector of the Russian economy. All of his assets subject to U.S. jurisdiction were blocked, and U.S. people and firms are prohibited from dealings related to Deripaska, his properties and his interest in properties.
Deripaska sued The Associated Press in 2017 over a story that March about his business dealings with Paul Manafort, a former campaign chairman for President Donald Trump. Deripaska said the AP article was inaccurate and hurt his career by falsely accusing him of criminal activity. A federal judge dismissed the defamation and libel lawsuit that October.
In 2022, Deripaska and three associates were criminally charged in New York with conspiring to violate U.S. sanctions and plotting to ensure his child was born in the United States.
Treasury says its Thursday enforcement action against Gracetown highlights the importance of following OFAC-issued guidance and the significant consequences that can occur from failing to do so.
John K. Hurley, Treasury’s undersecretary for terrorism and financial Intelligence, said “we will continue to investigate and hold accountable those who enable sanctioned actors.
Gracetown was established in 2006 to manage three luxury real estate properties in New York and Washington, D.C., that Deripaska acquired around the same time through various legal entities.
Fatima Hussein, Associated Press
Its been less than two months since President Trump began his demolition of the White Houses East Wing to make room for his big, beautiful White House Ballroom, and the President is already parting ways with the original architect behind the project.
On December 4, a White House spokesperson confirmed to The Washington Post that the original ballroom architect, McCrery Architects, has been traded in favor of the firm Shalom Baranes Associates. The swap comes after multiple reports that Trump and Jim McCrery, CEO of McCrery Architects, clashed repeatedly over the size and scope of the new ballroom.
A screenshot of Shalom Baranes Associates portfolio site. [Screenshot: sbaranes.com]
The construction of a giant ballroom is only one part of Trumps plan to remake the White House in his image. Over the past several months, hes updated the buildings interiors with his own Rococo-inspired aesthetics, overhauled the Oval Office into a gold-laden spectacle, and turned the Rose Garden patio into a Mar-a-Lago lookalike.
Still, his plans to tear down the White Houses East Wing to build a $250 million, 90,000-square-foot ballrooma process thats already underwayis by far his most extreme renovation. And now, it seems hes opting for a new architect whos more willing to bend to his personal vision for the project.
Heres everything you need to know about the shake-up, in a handy timeline:
July 31
Late this summer, the Trump administration officially announced its plans to construct a White House ballroom. At the time, the administration named McCrery Architects as the team heading up the project.
McCrery himself has been a vocal supporter of President Trumps push to make classical architecture a federal standard, once stating, Americans love classical architecture because it is our nations formative architecture and we love our nations formation. His firm is most known for designing Catholic churches and academic buildings.
[Rendering: whitehouse.gov/McCrery Architects]
October 20
In October, the Trump administration began tearing down major sections of the East Wing to make way for the massive ballroom. The move came despite both Trump and White House Press Secretary Karoline Leavitts earlier assurances that the project would not interfere with the existing structure.
November 26
The Washington Post was the first to report tensions between McCrery and Trump. According to the publication, four people close to the project reported that McCrery repeatedly advised Trump to bring down the proposed size of the ballroom, pointing out that a 90,000-square-foot addition would overshadow the original White House.
In a later report from The New York Times, further details about the disagreement emerged. Several sources told the publication that Trumps plans for the ballrooms size have grown dramatically since the plan was first proposed. In addition, Trump reportedly told people working on the ballroom that they did not need to follow permitting, zoning, or code requirements, and encouraged contractors to work quickly to meet the tight timetable of completion before 2029.
It appears that McCrery may have always been doomed to exit the project at some point. One source told The Post that the small size of his workforce made it difficult to meet such intense deadlines. On top of that, McCrery Architects’ relative inexperience with a project of such massive scale and inherent public scrutiny likely set the stage for problems down the line.
Construction continues on the White House grounds in Washington, D.C., in late October 2025. [Photo: Celal Gunes/Anadolu/Getty Images]
December 4
Trumps split with McCrery Architects was officially confirmed to The Washington Post via a statement from White House spokesperson Davis Ingle, who named Shalom Baranes as the next in line to head up the project. Per The Post, McCrery will remain tied to the effort on a consulting basis.
Baranes, who runs the firm Shalom Baranes Associates, is most known for leading a $1 billion renovation of the Pentagon back in 2001, though his firm has worked on other large-scale projects throughout D.C. Unlike McCrery, hes embraced a neo-traditionalist style. Back in 2017, he subtly spoke out against Trumpsimmigration ban in an op-ed for The Washington Post, wherein he described himself as a refugee and argued that his own success would be impossible without his fellow immigrants.
My hope is that the Trump administration will take actions to ensure that the travel ban is indeed temporary, so that good, hard-working individuals fleeing tyranny can find a new home as I didand that each of them will be given the same opportunity to help build this great nation that I had, Baranes wrote at the time.
The year is quickly coming to an end, and that means tech platforms are tripping over themselves to roll out their year-end recapsall hoping to capture the virality that Spotifys Wrapped year-in-review recap commands each year.
Already in December, weve seen Spotify Wrapped, Apple Music Replay, Amazon Music Delivered, and YouTube Recap, with more, like the popular Snapchat Recap, set to debut in the coming weeks. One of those debuts has occurred today, as well. Popular chat platform Discord has now released its personalized Wrapped-like recap: Discord Checkpoint. Heres what to know about it and how to view yours.
Discord announced Discord Checkpoint 2025
Discord has announced that its personalized Discord Checkpoint recap will be rolling out to its users over the next few days. In previous years, Discord has announced a Checkpoint recap, but the start it released for it encompassed its global user base.
Discord Checkpoint 2025 is the first time the platform is offering a year-in-review personalized for each of its individual users, provided they were active on the service enough to generate a Checkpoint recap, and that their privacy settings allowed the use of their data.
What’s included in my Discord Checkpoint 2025?
[Art: Discord]
There are two main components of your Discord Checkpoint 2025. The first is a recap of your usage and interactions on the platform.
Heres some of what your Discord Checkpoint 2025 will show you:
How many messages you sent
How many minutes in voice chat you spent
How many emojis you posted
What other Discord users you spent the most time with
The servers you used the most
But Discord 2025 Checkpoint will also display one of 10 Checkpoint cards. These cards represent 10 different types of Discord users. Your card will come with a matching avatar you can choose to display on your profile so other Discord users can see if youre in the same group.
How can I access my Discord Checkpoint 2025?
To access your Discord Checkpoint 2025, make sure you have the latest version of the desktop or mobile app.
If you are using the desktop app:
Click the flag option in the top-right corner. Your Checkpoint will be displayed.
If you are using the mobile app:
Tap the You tab in the bottom-right corner.
Tap the Checkpoint banner. Your Checkpoint will be displayed.
Can I share my Discord Checkpoint 2025?
Yes, users can choose to share their Discord Checkpoint 2025.
To share your Discrod Checkpoint, tap the Share button on the Summary page and then choose where youd like to share it.
Discord Checkpoint 2025 will be available to Discord users until January 15, 2026.
Being tired is practically a personality trait in corporate Americaespecially in 2025. Everybody is exhausted, it seems. Folks are doing fiftyleven jobs. Youre always juggling tasks, always late for the next meeting because the last one ran long. But when youre one of the few Black employees at the gig, theres a subconscious fear of looking like youre in over your head, especially with the looming fear of layoffs. So you push through, even when youre running on fumes. You go harder, telling yourself youll rest once you get through the busy patch. But thats a lie. The job is a perpetual busy patch.For months, I kept telling myself I was just tired. Regular tired. The kind of tired you fix with a good nights sleep and maybe a WFH power nap between meetings. But one random Tuesday, as I stared blankly at my laptop trying to decipher a three-sentence Slack message like it was hieroglyphics, it hit me: This wasnt normal fatigue. My mind was cooked.
The exhaustion hit back in the spring, but it was nothing like the dramatics you see in movies. There were no panic attacks in the bathroom or conference room crashouts on Kyle. It showed up subtly, in little ways that I dismissed. Id reread emails multiple times because the words refused to connect in my mind. I had the attention span of a goldfish. Id get irrationally annoyed by people asking me perfectly reasonable questions. I was just . . . over it. I chalked it up to adulting, the natural byproduct of ambition and bills. This too shall pass, I thought.The breaking point wasnt cinematic. I was in a brainstorming session when I realized my mind felt blank. I managed to offer a few contributions to the meeting, but they were all cliché rehashes, none of the outside-of-the-box ideas Id usually bring to the table. I felt like Charles Barkley in Space Jam after the Monstars stole the NBA players skillslike a whole scrub.
Shortly after, I took a week off. Booked a trip. But a change of scenery didnt fix anything. I came back just as fried, which was more depressing. I tried damn-near all of the things Solange sings about in Cranes in the Sky. Then I realized I required a factory reset.
I began to make some real changes to improve my work-life balance. It wasnt just that I needed time away from the office; I needed better boundaries and mental-health maintenance. I began closing my laptop at a designated time, and keeping it closed until it was time to clock in the next day. I blocked off meeting-free focus time during workdays. I got a biweekly gym routine going. I stopped thinking of myself as a machine that could operate nonstop.
Somewhere along my come up, I had convinced myself that I needed to treat my job like I was back in college. In those undergrad days, I felt the need to pile on electives and explore diverse fields of study. I wanted to be well-rounded and sure of my career path. But once I was in the workplace, it became about being marketable. I took on fringe projects outside of my job description to open myself up to new opportunities and, ideally, more moola. The game plan served me well until it didnt.
Ive been taking it easy since then. I have nothing to prove to anyone else, or to myself. So I stay in my lane. I delegate more. I turn down things that arent my responsibility. Ive unlearned the foolish idea that rest is a reward, something I had to earn by pushing myself to the brink. Doing the most is a thing of the past.
It took burning out for me to learn a simple truth: Nothing at work is worth losing yourself over. Not the project, not the promotion, not the pat on the back. Protect your energy like its finite, because it is. If youre feeling the kind of tiredness that sleep cant fix, follow the sage guidance of Ice Cube: Check yourself before you wreck yourself.
Every year, open enrollment forces Americans to confront a familiar dilemma: Pay more for coverage that delivers less, or gamble on going without it. This year, that choice has become even starker.
Employers are shifting more costs to workers, marketplace premiums are poised to rise, fewer prescription drugs are covered by insurance, and 3.8 million people could lose insurance annually if Affordable Care Act subsidies arent extended.
Together, these developments represent a structural break in the U.S. healthcare system. Its a perfect storm that will price many Americans out of health insurance altogethermany involuntarily, but some voluntarily. Fed up with skyrocketing premiums and deductibles that offer little protection, they’ll instead pay out-of-pocket for medical needs, hoping that they won’t face catastrophic expenses.
Whats emerging is not a temporary coverage gap. Its a permanent coverage squeeze. One that will fundamentally reorder consumer behavior and redefine what access means. The implications for healthcare organizations are profound, and those who fail to adapt will struggle to stay relevant.
SHIFT FROM COVERAGE TO CONTROL
For decades, the U.S. healthcare model has been built on the assumption that insurance is the gateway to care. But when premiums and deductibles reach levels that rival a second mortgage, consumers start to ask a different question: What am I actually getting for this?
Increasingly, the answer feels out of step with consumer expectations. High deductibles mean many people pay full price for most of their care anyway. Network limitations constrain choice. Surprise bills erode trust. And the complexity of benefits makes it nearly impossible to be an informed consumer.
As a result, were seeing a quiet but significant reorientation. Consumers are moving from a coverage-first mindset to a control-first mindset. They want to understand costs upfront. They want to choose where they go for treatment. They want the ability to pay in ways that fit their budgets. And when the value equation breaks, theyre willing to bypass the system entirely.
THE CONSUMER HEALTHCARE MARKET WILL EXPAND
If current trends hold, 2026 could mark one of the largest expansions of the uninsured and underinsured population in more than a decade. But instead of disengaging from the healthcare system, these consumers are building a parallel path through it. They are demanding the same things they expect from the best retail and digital experiences: clarity, predictability, immediacy, and trust.
This creates a massive opportunity, and a significant responsibility, for the industry. Companies that can simplify access, make pricing transparent, and deliver affordable pathways to care will become essential partners. Those that cling to legacy models built around opaque reimbursement flows will watch consumers go elsewhere.
We already see evidence of this shift. People are embracing subscription-based care for predictable costs, using telehealth for speed and convenience, and relying on platforms like GoodRx to access lower prescription prices. Services like my company GoodRxs newly-launched telemedicine subscriptions for erectile dysfunction, hair loss, and weight loss are examples of how companies are meeting this demand, offering affordable, accessible healthcare options outside traditional insurance frameworks.
WHAT HEALTHCARE LEADERS MUST DO NOW
Healthcare has historically been built around the needs of institutions, not individuals. That era is ending. The organizations that thrive in the next phase will redesign around consumer agency and economic reality.
Three shifts are essential:
Make cash pricing a standard, not a contingency. If people are paying out-of-pocket, they need to see the cost clearly, consistently, and upfront. Transparent pricing should be a baseline expectation across providers, pharmacies, and manufacturers.
Embed affordability into clinical decision making. Cost isnt a back office issue. It should be integrated into prescribing tools, clinical workflows, and patient conversations. Providers need real-time insights into cash prices and savings options so they can help patients make informed choices before they reach the pharmacy counter.
Build care models that meet consumers where they are. Telehealth, retail clinics, asynchronous care, and hybrid models represent the way consumers want to access routine, preventive, and even chronic care. Healthcare companies must expand their presence in these channels or risk losing relevance.
BUILD A CONSUMER-CENTRIC FUTURE
The coverage squeeze is exposing something important: Consumers are demanding value, not just benefits. They want care that feels intuitive and affordable. They want to make decisions with clear information rather than insurance complexity. And they want healthcare that adapts to their lives.
If we meet that demand, we have a chance to rebuild trust and deliver a healthcare experience that works for more people, regardless of their coverage status. If we dont, consumers will continue to chart their own path, with or without the traditional system.
The next chapter of American healthcare wont be defined by the rise or fall of insurance premiums. It will be defined by whether we, as industry leaders, embrace a radically simple idea: When we design for the consumer first, everyone benefits.
Wendy Barnes is president and CEO of GoodRx.
Weve been here before.
At so many pivotal moments in our adoption of digital technology, people and businesses mistake a companys walled garden for the broader, more powerful network underneath. In the 1990s, many people genuinely believed AOL was the internet. When I left Facebook in 2013, hundreds of people asked how I would function without the web. Over and over, packaged productsoperating systems, app stores, streaming serviceseclipse quieter, less expensive, bottom-up alternatives like Linux or torrents. We forget they exist.
Today were making the same mistake with large language models.
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To many of us, AI now means choosing among a handful of commercial LLMs such as ChatGPT, Claude, Gemini, or Grokand perhaps even choosing the one that matches our cultural or political sensibilities. But these systems share important structural limitations: they are centralized, expensive, energy-intensive operations that depend on massive data centers, rare chips, and proprietary data stores. Because theyre trained on roughly the same public internet, they also tend to generate the same generalized, flattened results. Companies using them wholesale often end up substituting their own expertise with recombinations of whatever is already out there.
This is how AI will do to businesses what social media did to publications, and what the early web did to retailers who went online without a strategy. Using the same generic tools as everyone else produces the same generic results. Worse, outsourcing core knowledge processes to a black-box service replaces the long-term development of internal capacityespecially junior employees learning through real practicewith cheaper but future-eroding automation.
The limits of centralized AI
Commercial language models are optimized for generality and scale. That scale is impressive, but it creates real constraints for organizations. Centralized LLMs require:
Large volumes of training data scraped from the open web
Expensive server infrastructure and power consumption
Constant external connectivity
Business models built around subscription, token fees, or upselling
For many companies, these models become another outsourced dependency. Every time a commercial LLM updates itselfwhich can happen weeklyyour workflows change underneath you. Your proprietary data may be exposed to third-party APIs. And your differentiation erodes, because the models knowledge is drawn from the same public corpus available to your competitors.
Meanwhile, the narrative surrounding AI has encouraged businesses to believe that this centralized path is the only viable onethat achieving meaningful AI capability requires enormous data centers, billion-dollar training runs, and participation in a global race toward Artificial General Intelligence.
But none of this is a requirement for using AI productively.
A practical alternative already exists
You do not need frontier-scale models to benefit from AI. A growing ecosystem of open-source, locally deployable language models provides organizations with far more autonomy, privacy, and control.
A $100 Raspberry Pior any modest home or office servercan run a compact open-source model using tools like Ollama or GPT4All. These models dont learn on the fly the way people do, but they can produce high-quality responses while remaining completely contained within your own environment. More importantly, they can be paired with a private knowledge base using retrieval systems. That means the model can reference your own research library, internal documentation, or curated public resources like Wikipediawithout training on the entire internet, and without sending your data to an external provider.
These systems build on your own data instead of extracting it, strengthen your institutional memory instead of commoditizing it, and run at a fraction of the cost.
This approach allows an organization to create an AI system aligned with its actual priorities, values, and domain expertise. It becomes a private assistant rather than a generalized product shaped by the incentives of a trillion-dollar platform. And the alternative doesnt have to be a solitary effort.
Neighborhoods, campuses, or company departments can form a mesh networka set of devices connected directly through Wi-Fi or cables rather than through the public internet. One node can host a local model; others can contribute or withhold their own data stores. Instead of a single company owning the infrastructure and the knowledge, you get something closer to a community data commons or a digital library system.
Projects like the High Desert Institutes LoreKeepers Guild are already experimenting with this approach. Their Librarian initiative envisions local libraries acting as the data hubs for mesh-networked AI systemsresilient enough to function even during connectivity disruptions. But their deeper innovation is architectural. These systems give organizations access to powerful language capabilities without subscription costs, lock-in, data extraction, or exposure of proprietary information.
Local or community models enable organizations to:
Curate their own data
Maintain complete privacy by keeping computation on-site
Reduce latency to near zero
Preserve and strengthen internal expertise
Avoid recurring token or API costs
And they do so using energy and computing resources that are orders of magnitude lower than those required by frontier-scale models.
Why decentralized AI matters now
The more institutions adopt localized or mesh-based AI, the less they are compelled to fund the centralized companies racing toward AGI. Those companies have made an effective argument: that sophisticated AI is only possible through their services. But much of what organizations pay for is not their own productivityit is the constrution of massive server farms, procurement of rare chips, and long-term bets on energy-intensive infrastructure.
By contrast, in-house or community-run systems can be deployed once and maintained indefinitely. A week of setup can eliminate a decade of subscription payments. A small rural library has already demonstrated the feasibility of operating a self-hosted LLM node; a Fortune 500 company should have no trouble doing the same.
Still, history suggests that most organizations will choose the convenient option rather than the autonomous one. Few people accessed the early Internet directly; they chose AOL. Today, many will continue to choose centralized AI services, even when they offer the least control. But what social media companies did to businesses that mistook them for the Internet will be mild compared to what comes when companies mistake these proprietary interfaces for AI itself.
Decentralized AI already exists. The question now is whether well choose to use it.
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The way consumers search is changing faster than the industry expected. This holiday season, many shoppers are looking for gifts inside AI platforms, rather than retailer sites or traditional search. They are asking natural questions like:
Find me a cruelty-free skincare gift for sensitive skin under $100. What are good gift ideas for a three-year-old that are safe and durable? What are the safest, nontoxic treats for my Golden Retriever?
This shift is already measurable. Adobe Digital Insights reports a 4,700% year-over-year increase in retail visits driven by AI assistants between July 2024 and July 2025. At the same time, click-through rates from SEO have dropped 34% as users bypass the search results page entirely. eMarketer reports 47% of brands have no idea whether they appear in AI-driven discovery at all.
The platforms know this shift is accelerating. Googles recent decision to add conversational shopping and AI-mode ads just weeks before the holidays shows how quickly consumer behavior is moving. Brands must adjust too.
Despite the complexity behind AI systems, three simple signals determine which products get recommended: trust, relevance, and extractability. These signals are the backbone of how AI decides what to surface, and matter as much as packaging, price, or placement.
1. Trust: The models instinct about which information is dependable
AI systems develop a sense of which sources to believe during training. Domains with consistent verification signals gain more weight because the model has learned they usually publish accurate information.
This is why leading retailers, including Ulta, Sephora, Target, Amazon, and Bloomingdales, rely on independent verification partners for the claims displayed on their digital shelves. Verified domains act as trust anchors. When a model must choose, it selects the product backed by clearer and more reliable sources.
Trust often determines whether you are included in the answer at all.
2. Relevance: How well your product matches the shoppers question
AI assistants answer based on meaning, not keywords. When a shopper asks for eczema-safe moisturizer or gluten-free protein bars, the system retrieves products whose attributes clearly map to those concepts.
Relevance depends on using consistent claims across every channel you sell inconsistency is heavily prioritized. When multiple sources concur, this repeated confirmation strongly reinforces your product is the right choice.
Missing or inconsistent attributes keep your product of the candidate pool.
3. Extractability: How easy it is for AI to read and use your product data
Even accurate information gets ignored if its hard for AI to parse. Clean structure, consistent formatting, and machine readability significantly increase the likelihood your product will be selected.
Brands improve extractability by adding structured markup for details like ingredients, materials, and benefits so retrieval systems can interpret it without ambiguity.
Clear structure anchors the attention of the large language model, giving your product an advantage. Extractability is often the deciding factor when competing products meet the same need.
AI RECOMMENDATIONS SHAPE BEHAVIOR
Algorithms do more than respond to consumers. They influence them.
We see this in language, where content moderation has led millions of people to adopt new vocabulary. The same pattern is emerging in commerce. If AI consistently recommends a certain moisturizer, probiotic, or baby product, shoppers begin to trust those recommendations and carry those preferences into stores.
Optimizing for trust, relevance and extractability goes beyond improving digital performance. It shapes real-world buying behavior.
A PRACTICAL PLAYBOOK FOR THE HOLIDAY WINDOW
Even with peak season here, brands can still make meaningful progress with these four steps:
1. Structure your data for machine and human audiences
Fix blocked pages or missing product schemas, and use standard formats like JSON-LD that AI can parse reliably.
Keep consumer-facing PDPs simple while storing deeper technical details, ingredients, and safety information in underlying schemas.
Clean up formatting and refresh retailer feeds weekly, since AI systems prioritize recency.
Example: A candle brand can keep the PDP simple for shoppers while storing allergen, VOC, and material data in structured markup that AI can read.
2. Align product claims everywhere you sell
Match titles, claims and benefits across DTC sites, retailer PDPs, and marketplaces.
Remove conflicting or outdated language that can weaken trust.
Example: If one PDP says cruelty-free and another says not tested on animals, unify the phrasing so AI sees one consistent claim.
3. Map your data to real shopper intent
Identify the attributes consumers care about most in your category.
Encode those attributes in machine readable fields; add supporting evidence where possible.
Example: For baby toys, encode safety standards like ASTM or CPSC in your structured data so AI can confirm the claim.
4. Build machine-readable authority with credible certifications and verification signals
Encode ingredients, materials, certifications, and testing outcomes in structured fields so AI can verify your caims without guessing.
Keep claim language consistent across channels to strengthen authority.
Use references to third-party standards, testing, or retailer badges. AI gives more weight to claims it can trace back to trusted sources.
Example: A sensitive skin serum should encode fragrance-free, eczema-safe, dermatologist testing details, and any third-party certifications directly in schema.
5. Use a tool that monitors, optimizes, and implements the work end-to-end
Choose a tool that goes beyond generic visibility tracking, looks at each SKU individually, and helps you implement structured data improvements.
Prioritize systems that strengthen your authority signals product by product, not just surface-level optimizations.
Look for tools that measure real outcomes, like increased visibility in AI or higher conversion, so you can measure ROI.
Consumer discovery is changing faster than most brands are prepared for. But there is still time. By reinforcing trust, relevance, and extractability now, brands can stay visible in AI-driven search this season and build a long-term foundation for every channel where AI shapes consumer decisions.
Kimberly Shenk is cofounder and CEO of Novi.
European Union regulators on Friday fined Elon Musk’s social media platform X 120 million euros ($140 million) for breaches of the bloc’s digital regulations that they said could leave users exposed to scams and manipulation.The European Commission issued its decision following an investigation it opened two years ago into X under the 27-nation bloc’s Digital Services Act, also known as the DSA.It’s the first time that the EU has issued a so-called non-compliance decision since rolling out the DSA. The sweeping rulebook requires platforms to take more responsibility for protecting European users and cleaning up harmful or illegal content and products on their sites, under threat of hefty fines.The Commission said it was punishing X, previously known as Twitter, because of three different breaches of the DSA’s transparency requirements. The decision could rile President Donald Trump, whose administration has lashed out at digital regulations, complaining that Brussels was targeting U.S. tech companies and vowing to retaliate.The company did not respond immediately to an email request for comment.EU regulators had already outlined their accusations in mid-2024 when they released preliminary findings of their investigation into X.Regulators said X’s blue checkmarks broke the rules because on “deceptive design practices” and could expose users to scams and manipulation.Before Musk acquired X, when it was previously known as Twitter, the checkmarks mirrored verification badges common on social media and were largely reserved for celebrities, politicians and other influential accounts.After he bought it in 2022, the site started issuing the badges to anyone who wanted to pay $8 per month for one.The means X does not meaningfully verify who’s behind the account, “making it difficult for users to judge the authenticity of accounts and content they engage with,” the Commission said in its announcement.X also fell short of the transparency requirements for its ad database, regulators said.Platforms in the EU are required to provide a database of all the digital advertisements they have carried, with details such as who paid for them and the intended audience, to help researches detect scams, fake ads and coordinated influence campaigns. But X’s database, the Commission said, is undermined by design features and access barriers such as “excessive delays in processing.”Regulators also said X also puts up “unnecessary barriers” for researchers trying to access public data, which stymies research into systemic risks that European users face.“Deceiving users with blue checkmarks, obscuring information on ads and shutting out researchers have no place online in the EU. The DSA protects users,” Henna Virkkunen, the EU’s executive vice-president for tech sovereignty, security and democracy, said in a prepared statement.
Kelvin Chan, AP Business Writer
