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We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. If you want a high-quality OLED TV for gaming and movies but the options you’ve been seeing online are out of your price range (they often easily surpass the $1,000 mark), the 55-inch Samsung S85F OLED TV checks most of the necessary boxes and is currently down to $897.99 (originally $1,397.99) thanks to a 36% discount during the Amazon Big Spring Sale. Samsung S85F OLED TV $897.99 at Amazon $1,397.99 Save $500.00 Get Deal Get Deal $897.99 at Amazon $1,397.99 Save $500.00 Despite being labeled an entry-level OLED TV, the picture quality is still impressive, with not just strong HDR performance, color accuracy, and near-infinite contrast, but also perfect blacks and refined shadow detail. That means you’ll get better bang for your buck during dark scenes than you will with LED/QLED displays. The S85F has a very wide viewing angle, allowing for a consistent image from all sides. It uses an AI Gen2 processor and has AI-based enhancements, including 4K AI Upscaling and Real Depth Enhancer, and runs on the Tizen 9.0 smart TV platform. It’s also an underrated choice for gamers that rivals the best gaming TVs, with a highly responsive 9.4ms input lag. It has four HDMI 2.1 ports that support 4K 120Hz, AMD FreeSync Premium, Nvidia G-Sync, ALLM, and HDR10+ gaming, as well as Motion Xcelerator tech to reduce blur in fast scenes and an AI Auto Game Mode to optimize settings. Plus, the Samsung Gaming Hub offers extra perks, including access to a wide range of cloud gaming apps. The two 2-channel, 20W speakers give users decent bass and clear dialogue, but they're not home theater-level. While it may not be the absolute brightest OLED on the market or have top-of-the-line built-in audio, the 55-inch Samsung S85F OLED TV still offers great value and makes a strong choice for gaming and movies, especially at a sub-$900 price point, which is more than fair for an OLED from a top brand. If you want the best of the best, you can upgrade to a model like the S95, but it’ll come with a hefty price bump. For most people, a middle-ground OLED like the S85F is a solid choice. Our Best Editor-Vetted Amazon Big Spring Sale Deals Right Now Apple AirPods Pro 3 Noise Cancelling Heart Rate Wireless Earbuds — $199.00 (List Price $249.00) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $299.00 (List Price $349.00) Samsung Galaxy Tab A11+ 128GB Wi-Fi 11" Tablet (Gray) — $209.99 (List Price $249.99) Sony WH1000XM6- Best Wireless Noise Canceling Headphones — $398.00 (List Price $459.99) Apple Watch Series 11 (GPS, 42mm, S/M Black Sport Band) — $299.00 (List Price $399.00) Blink Video Doorbell Wireless (Newest Model) + Sync Module Core — $35.99 (List Price $69.99) Fire TV Stick 4K Max Streaming Player With Remote — $34.99 (List Price $59.99) Amazon Kindle Colorsoft 16GB 7" eReader (Black) — $169.99 (List Price $249.99) Deals are selected by our commerce team View the full article

Traditional 60-40 portfolio of global equities and fixed income on course for worst month since 2022View the full article

Learn how the agentic web is transforming search into AI-driven action, and why SEOs must adapt beyond traditional optimization. The post Why Google’s New “Google-Agent” Is The Biggest Mindset Shift In SEO History appeared first on Search Engine Journal. View the full article

We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. Amazon’s Big Spring Sale is underway, and one of the more practical big-ticket deals right now is on the Anker Solix F2000 Portable Power Station. It’s down to $799.99 (from $1,999), which is about 60% off and the lowest price tracked so far, according to price tracking tools like Keepa. That kind of drop makes this a very different conversation. At full price, it’s a niche buy. At this price, it starts to feel like a realistic backup option for homes, road trips, or anyone who deals with frequent power cuts and wants something more reliable than a basic inverter setup. Anker Solix F2000 Portable Power Station Backup power for home use, outdoor camping or RVs $799.99 at Amazon $1,999.00 Save $1,199.01 Get Deal Get Deal $799.99 at Amazon $1,999.00 Save $1,199.01 The F2000 is built around a 2,048Wh battery and a 2,300W AC output. In real terms, that’s enough to run a dishwasher through a full cycle or keep essentials like a fridge, lights, and a few devices going during a blackout. It can also handle heavier appliances like a washing machine or oven, just not all at once, since that 2,300W is shared across its three AC outlets. You also get a mix of ports that cover most setups: three AC sockets, three USB-C ports with up to 100W output for laptops, two USB-A ports, and car-style outlets. Plus, there’s a screen that gives you a clear read on battery levels, power usage, and time estimates, and the companion app adds extra control like switching ports on or off and monitoring battery temperature. Charging is flexible, too. You can plug it into a wall for a full recharge in a little over an hour, use a car adapter, or connect up to 1,000W of solar panels (sold separately) for off-grid use. If you want more runtime, there’s also an optional expansion battery that doubles the capacity to 4,048Wh, though the output stays the same at 2,300W. It’s currently bundled with the F2000 for $1,498.99, down from $2999. The main downside here is size and weight. Even with wheels and a telescopic handle, this is not something you casually move around. Our Best Editor-Vetted Amazon Big Spring Sale Deals Right Now Apple AirPods Pro 3 Noise Cancelling Heart Rate Wireless Earbuds — $199.00 (List Price $249.00) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $299.00 (List Price $349.00) Samsung Galaxy Tab A11+ 128GB Wi-Fi 11" Tablet (Gray) — $209.99 (List Price $249.99) Sony WH1000XM6- Best Wireless Noise Canceling Headphones — $398.00 (List Price $459.99) Apple Watch Series 11 (GPS, 42mm, S/M Black Sport Band) — $299.00 (List Price $399.00) Blink Video Doorbell Wireless (Newest Model) + Sync Module Core — $35.99 (List Price $69.99) Fire TV Stick 4K Max Streaming Player With Remote — $34.99 (List Price $59.99) Amazon Kindle Colorsoft 16GB 7" eReader (Black) — $169.99 (List Price $249.99) Deals are selected by our commerce team View the full article

We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. Hisense’s mid-range TVs tend to land in that sweet spot of good features at a not-astronomical price. That certainly describes the 2025 U7 Series right now, as the 65-inch model is discounted by $800 at Best Buy, dropping to just $699. It's one of Lifehacker's picks for the best 65-inch TVs in 2026, especially at this price. The sale price is good through April 19, and Best Buy is sweetening the deal with a discount on mounting and free haul-away for members, which will make upgrading your older TV a bit less of a chore. 65-inch Hisense 65U75QG TV MiniLED Smart 4K TV (2025) $699.00 at Best Buy $1,499.00 Save $800.00 Get Deal Get Deal $699.00 at Best Buy $1,499.00 Save $800.00 The Mini-LED backlighting and QLED panel of the 65U75QG deliver deep blacks with minimal blooming, and displays punchy HDR content with support for Dolby Vision and HDR10+, so watching movies or sports feels lively. It gets bright enough to handle sunlit rooms without looking washed out, though if your room has a lot of light, reflections can show up during darker scenes. There’s a built-in speaker setup with a subwoofer and upward-firing speakers, which adds some height to the soundstage, though it won’t replace a dedicated soundbar. As Google TV runs the interface, apps, casting, and voice control are all baked in. On the downside, this TV doesn’t track brightness levels as precisely as higher-end models, so scenes can look slightly off without careful calibration. Also, the viewing angle is narrow enough that colors and contrast shift if you’re sitting too far to the side. While gaming works well overall, with smooth performance and plenty of support for high refresh rates, fast-moving scenes may blur more than expected. None of these factors will be a dealbreaker for casual use, but they matter if you’re picky about image accuracy or plan to use this in a wide seating setup. For most people, though, this is a bright, capable TV that covers a lot of ground, especially for this price. Our Best Editor-Vetted Amazon Big Spring Sale Deals Right Now Apple AirPods Pro 3 Noise Cancelling Heart Rate Wireless Earbuds — $199.00 (List Price $249.00) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $299.00 (List Price $349.00) Samsung Galaxy Tab A11+ 128GB Wi-Fi 11" Tablet (Gray) — $209.99 (List Price $249.99) Sony WH1000XM6- Best Wireless Noise Canceling Headphones — $398.00 (List Price $459.99) Apple Watch Series 11 (GPS, 42mm, S/M Black Sport Band) — $299.00 (List Price $399.00) Blink Video Doorbell Wireless (Newest Model) + Sync Module Core — $35.99 (List Price $69.99) Fire TV Stick 4K Max Streaming Player With Remote — $34.99 (List Price $59.99) Amazon Kindle Colorsoft 16GB 7" eReader (Black) — $169.99 (List Price $249.99) Deals are selected by our commerce team View the full article

We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. If your wifi is too damn slow (and I bet it is), the bottleneck is probably the router. This TP-Link Archer AXE75 might be the solution, and it's 44% off for Amazon’s Big Spring Sale, bringing it down to $112.99—and it's already a good deal at the full price. TP-Link Archer AXE75 $112.99 at Amazon $199.99 Save $87.00 Get Deal Get Deal $112.99 at Amazon $199.99 Save $87.00 This is a Wi-Fi 6E router, which unlocks the 6GHz band, so it's a serious router for the price of a bargain one. It features a 1.7 GHz Quad-Core CPU, so it won't freeze up when you're gaming while someone else is streaming 4K in the next room, and it has six high-gain antennas that are built to kill dead zones in medium-to-large homes. Check out PCMag's review for more details. That's the good news. The bad news is the FCC regulations regarding foreign-made routers going into effect. Like most routers, AXE75 is "foreign made"—but the regulations only affect the future authorization of brand-new models. Since the Archer AXE75 is already an authorized, existing model, you can legally buy and use it without worry. But there's a caveat: The FCC has allowed security updates for these models through March 1, 2027. After that, it's not certain it will be supported. TP Link says it's planning to move manufacturing to the U.S. If that happens, the FCC is expected to extend its waiver, and the device will be supported. But no one can say for sure. Our Best Editor-Vetted Amazon Big Spring Sale Deals Right Now Apple AirPods Pro 3 Noise Cancelling Heart Rate Wireless Earbuds — $199.00 (List Price $249.00) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $299.00 (List Price $349.00) Samsung Galaxy Tab A11+ 128GB Wi-Fi 11" Tablet (Gray) — $209.99 (List Price $249.99) Sony WH1000XM6- Best Wireless Noise Canceling Headphones — $398.00 (List Price $459.99) Apple Watch Series 11 (GPS, 42mm, S/M Black Sport Band) — $299.00 (List Price $399.00) Blink Video Doorbell Wireless (Newest Model) + Sync Module Core — $35.99 (List Price $69.99) Fire TV Stick 4K Max Streaming Player With Remote — $34.99 (List Price $59.99) Amazon Kindle Colorsoft 16GB 7" eReader (Black) — $169.99 (List Price $249.99) Deals are selected by our commerce team View the full article

If your entire Google Ads strategy consists of targeting brand and non-brand keywords, you’re limiting growth. If performance is declining, it’s not the platform — it’s the strategy. People don’t discover you through non-brand search. They research on Reddit, ChatGPT, Facebook, LinkedIn, and YouTube. They watch demos, read testimonials, and learn about your brand long before they ever search for it. If you have a complex sales process and a long customer journey, this shift is critical and requires a different approach. Here’s what you need to know to make this work in B2B. AI-forward campaigns: A cost-effective growth gold mine Google has been developing multi-channel, multi-asset campaigns for years — first with Performance Max, then with Demand Gen. These campaigns reach your audience across the web as they research and evaluate. Your brand is front and center while your audience builds their shortlist. By the time they’re ready to pick vendors to take the next step, you’ve already built trust. Then they’ll find you by searching for your brand. A Performance Max campaign with a variety of ad types, like image and video ads, can showcase demos or customer testimonials on YouTube. They can appear across the web via the Display Network. They can follow (retarget) your target audience as they research. That’s what drives the branded search that converts later. These campaigns let you do all of this cost-effectively. In a Performance Max campaign, you can use keywords alongside your own customer data as signals. You’re not abandoning keywords. You’re using them smarter. Dig deeper: Why B2B brands are shifting from keywords to Performance Max Your customers search everywhere. Make sure your brand shows up. The SEO toolkit you know, plus the AI visibility data you need. Start Free Trial Get started with The search experience is changing. Your strategy should, too. Google’s search results pages have evolved with AI Overviews and AI Mode. If this experience is changing so dramatically, isn’t it time to rethink your ad strategy as well? I’m a fan of the 4S framework: search, scroll, stream, and shop. I’d add “ask” to reflect how people now engage across AI tools. They ask ChatGPT or Gemini, search Google, scroll LinkedIn, stream YouTube videos, and shop across platforms. If your strategy only covers one or two of those behaviors, you’re missing how growth actually happens. Focusing only on keyword targeting means you’re missing the bigger picture. Yes, brand keywords will convert better than non-brand keywords. But how do people even know to search for your brand in the first place? (The answer is that you’ve been showing up in their feed the whole time.) Get the newsletter search marketers rely on. See terms. Test, learn, and be patient This approach takes time, especially for B2B companies with long sales cycles. It took us nearly a year to realize the value Performance Max was driving for a life science client. Most of their deals take months to close. Our account manager was about to pause the campaign at one point because the ad platform data didn’t look good. But as we began piping in sales data, things started clicking. Once we got over the sales cycle hump and started seeing revenue data, Performance Max proved its value. If you can sync data beyond MQLs — like Proposal Sent — that provides more data and signals to Google, and more peace of mind until you can add sales data. Be patient, feed the system better data, and don’t give up too early. B2B sales cycles are complex. You might have 100 people at an event that you promoted through a LinkedIn ad strategy. Some of those people caught an email promoting a webinar. Months later, they searched for you on Google and asked for a proposal. Still months later, they became a customer. Even with the best-recorded data, you won’t see this happening right away in a long sales cycle. Dig deeper: How to optimize B2B PPC spend when budgets and confidence are low Start small, then scale what works If you don’t have a test-and-learn budget, reallocate 5% to 10% to introduce AI-forward campaign types. Test strategically. Don’t go all in, and don’t launch major tests during a busier time of year. Give yourself breathing room while the system learns. This approach takes time. But it drives sustainable growth if you commit to the process. The advertisers who figure this out are building sustainable growth, while others are still stuck optimizing for a shrinking slice of demand. View the full article

A new version of the Google Ads API is out, bringing a handful of targeted updates across video, app campaigns, and audience planning tools. Key changes in this release. A new VideoEnhancement resource that surfaces whether a video ad is Google-generated or advertiser-provided — giving developers clearer visibility into auto-enhanced creative A new AppTopCombinationView resource providing read-only insights into top-performing asset combinations in App campaigns The ability to disable the hotel feed in Demand Gen campaigns via HotelSettingInfo.disable_hotel_setting A new conversion metric for indirect first in-app installs across Campaign, Customer, and AdGroup resources Several enhancements to ContentCreatorInsightsService and ReachPlanService What to do. Upgrading to v23.2 requires updating both client libraries and client code — all updated libraries and code examples are already published. Catch the walkthrough. Google is hosting a live release walkthrough on March 26 at 11am ET on Discord and YouTube Live, with a recorded version to follow for those who can’t attend. Why we care. The VideoEnhancement gives developers the ability to programmatically identify whether a video ad is Google-generated or advertiser-provided, which has been a notable blind spot in Performance Max reporting. For agencies and teams building custom reporting tools, this is a meaningful step toward greater creative visibility. The bottom line. A routine but useful release — the VideoEnhancement resource in particular is worth attention for any developer building tools around Performance Max creative reporting. View the full article

Designers love intention. Architects draw immaculate plans; curators craft pristine galleries; developers imagine carefully choreographed public experiences. But once the general population shows up, those spaces tend to change. Sometimes there’s an instinct among designers to fight against it; it’s hard to let go of an aesthetic goal. But—more often than not—the public makes spaces and designs better. It’s the people, not solely the place, who spark true imagination and inevitably shape its character. It’s the people who have the power to turn a design into something more welcoming and relevant, and push designers to think outside the box in creativity and problem-solving. This January in New York City, at a small placemaking summit hosted by Journey, experts across art, infrastructure, food, and civic design converged around this idea: Spaces come to life once the public makes them their own. DESIGN FOR VISITORS At the Summit, Katherine Fleming, CEO of the J. Paul Getty Trust, for example, described how visitors reshaped the Getty Museum’s iconic steps and lawns. Even though they had been designed as merely aesthetic transitional spaces, they soon became gathering spots: places for picnics, sketching, conversation, or quiet reflection. And instead of correcting that behavior to keep the grounds’ original function, the Getty embraced it. The result was longer museum visits and more positive discourse among the broader Los Angeles community—not, it’s important to note, diminished prestige. That same flexibility manifests in Antwaun Sargent’s work as the Gagosian director, where he curates galleries informed by the public. His Social Works exhibition highlighted artists embedded in their communities, including an installation from Linda Goode Bryant that displayed a fully functioning aeroponic farm in the gallery to demonstrate its use as a community space, challenging traditional notions of what “art” is and how it serves communities. This approach turned the gallery into a community, making it a place for the public to gather and learn instead of simply observing. This notion goes beyond art institutions and appears in everyday spaces, like retail communities. As Claire Bernard, senior food & beverage manager for Chelsea Market and Market 57, shared, the design at New York City’s iconic Chelsea Market didn’t stay fixed for long. Shop owners regularly shifted displays, reworked lines, and pulled seating in or out depending on the crowd. What started as clearly defined footprints, where one retailer ended and another began, quickly blurred once real people entered the mix. Those small, practical adjustments weren’t part of some grand plan, but they created a truly organic market that could respond to crowd patterns in real time. In many ways, that flexibility is what made it feel authentic and alive, it is another reminder that adaptation can serve the community, the vendors, and the space itself. Perhaps the most obvious example is public infrastructure. Tina Vaz, director of arts and design at the Metropolitan Transportation Authority (MTA), spoke about the MTA’s evolving arts and design efforts, where around 4.3 million daily riders turn transit stations into artistic interactions. Whether it’s poetry installations, live performances, permanent artworks, or occasional uncommissioned graffiti art, the MTA is continually adapting and responding to riders’ lived experiences. Meanwhile, initiatives from the Times Square Alliance embrace the constant flow of one of the world’s busiest crossroads, commissioning installations and digital art pieces designed specifically for visiting multilingual audiences. In many ways, these programs succeed precisely because they accept unpredictability and embrace the variety of the people they’re trying to reach. 4 DESIGN TIPS FOR PUBLIC SPACES So, what should developers and designers take from this? 1. Design for participation. Spaces aren’t finished when they open. They may never be finished. So, build in flexibility, whether it’s movable seating, adaptable signage, multi-use zones or timely installations, and learn from what your communities demand. 2. Measure engagement differently. Metrics tend to prioritize aesthetic loyalty or operational efficiency. But the real signs of success are more often how long people spend in a place, how often they revisit, and how willing the community is to engage spontaneously in them. 3. Invite collaboration. Artists, residents, commuters, and visitors all bring contexts you may not anticipate. Structured programs like residencies, community groups, public feedback discussions, and community-oriented designs make those contexts productive. In turn, your spaces become more thoughtful and more engaging. 4. Let go of perfection. Some of the most beloved public spaces look “messier” and function differently than their initial designs. But that’s the beauty of designing for the public: The unforeseen transformations are signs of life. A space that can absorb that humanness, rather than resist it, allows a design to step outside itself and become truly communal. And community, by definition, is always a collaboration. Andrew Zimmerman is the CEO at Journey. View the full article

This week we covered the release of the Google March 2026 core update that rolled out this morning and will take about two weeks to finish. We also covered Google March 2026 spam update that launched on March 24th and finished 19.5 hours later on March 25th...View the full article

Refreshing creatives for every seasonal moment just got significantly faster — Google has quietly launched Asset Group Theming inside Performance Max, letting advertisers apply seasonal themes to existing asset groups without rebuilding from scratch. How it works. Advertisers can clone a high-performing asset group and apply a theme — Google then generates themed image variations and suggests aligned headlines and descriptions, while leaving the original asset group completely untouched for safe testing. Available themes cover. Promotional: Sale, Studio/Editorial Seasons: Winter, Spring, Summer, Fall Cultural moments: Christmas, Black Friday/Cyber Monday, Halloween, Valentine’s Day, Easter, Mother’s Day, Father’s Day, Hanukkah, New Year, Lunar New Year, and Back to School Where to find it. Look for the prompt inside Asset Groups ahead of major holidays, or via “Apply theme to existing asset group” when creating a new one. Important caveat. This is a starting point, not a finished product. The tool uses existing images as a base and adds themed backgrounds — it does not replace videos, and typically only updates a handful of headlines to match the theme. Everything still needs to be reviewed and sense-checked before going live. Why we care. Seasonal creative refresh has always been one of the more time-consuming parts of campaign management — requiring design resources, rebuilding asset groups, and risking performance drops on proven setups. This feature removes most of that friction, letting teams adapt their best performers to key moments in minutes rather than days. The bottom line. Think of it as a creative assistant, not a replacement for a designer — but for advertisers managing multiple seasonal peaks across the year, the time savings alone make it worth exploring. First spotted. This update was spotted by Google Ads specialist Bia Camargo who shared a screenshot on LinkedIn. View the full article

Google tests AI headline rewrites in Search, completes the March spam update in under 20 hours, and adds AI content labeling to structured data docs. The post Google Tests AI Headlines, Rolls Out Spam Update – SEO Pulse appeared first on Search Engine Journal. View the full article

We may earn a commission from links on this page. Deal pricing and availability subject to change after time of publication. This week is Amazon's Big Spring Sale, and I can think of no better way to celebrate the end of this interminable winter than a backyard film festival. Amazon has just the thing for it: this Onoayo digital projector. It's currently $219.98 from a list price of $439.99, and that's for a projector with a 4.6/5 rating with over 1000 reviews on Amazon. Onoayo Digital Projector $219.98 at Amazon $439.99 Save $220.01 Get Deal Get Deal $219.98 at Amazon $439.99 Save $220.01 This isn't one of those projectors where you need to figure out how to connect it with something else, either. While you can stream from other devices, you don't have to; major streaming apps are built in, as are a pair of Dolby-tuned speakers. It features automatic focus, keystone correction, obstacle avoidance, screen-fit, and projection orientation detection right out of the box. The picture is great, too: 3200 ANSI brightness and 4K video decoding means a very defined, bright image. It weighs less than three pounds, so you can take it anywhere you need to project anything. But it's seriously good enough to replace a TV in your house. Our Best Editor-Vetted Amazon Big Spring Sale Deals Right Now Apple AirPods Pro 3 Noise Cancelling Heart Rate Wireless Earbuds — $199.00 (List Price $249.00) Apple iPad 11" 128GB A16 WiFi Tablet (Blue, 2025) — $299.00 (List Price $349.00) Samsung Galaxy Tab A11+ 128GB Wi-Fi 11" Tablet (Gray) — $209.99 (List Price $249.99) Sony WH1000XM6- Best Wireless Noise Canceling Headphones — $398.00 (List Price $459.99) Apple Watch Series 11 (GPS, 42mm, S/M Black Sport Band) — $299.00 (List Price $399.00) Blink Video Doorbell Wireless (Newest Model) + Sync Module Core — $35.99 (List Price $69.99) Fire TV Stick 4K Max Streaming Player With Remote — $34.99 (List Price $59.99) Amazon Kindle Colorsoft 16GB 7" eReader (Black) — $169.99 (List Price $249.99) Deals are selected by our commerce team View the full article

The local SEO community remains locked in a permanent debate over the “hide address” toggle for service area businesses (SABs). Most owners view this switch as a simple privacy setting. In reality, it’s a high-stakes decision that dictates how Google’s algorithm interprets your physical relevance. Does your defined service area influence where you rank? Does hiding your street address suppress your visibility in the local pack? Most importantly, does Google purge that data from its system, or does your map pin simply become an invisible anchor? These are fundamental and relevant questions of how proximity functions when you choose to go off the grid. How Google actually places your map pin To be clear, the address and the map pin aren’t the same thing. When you enter an address into your Google Business Profile, Google doesn’t simply drop a pin. It runs the address through its geocoding engine to resolve the text string against its internal database. To understand why a map pin ends up in a highway median or a city center, you must examine Google’s internal data models: GeostoreAddressProto: How Google stores and parses a business address. GeostorePointProto: How Google stores the actual map pin location. GeostoreServiceAreaProto: How Google stores the regions a business serves. Google is looking for a match it can trust. When it finds a high-confidence match, it places the pin specifically at the rooftop of your building. Once you understand how these three work together, you can get some clarity on why Google appears to rank SABs differently in the local map pack. Is your map pin placement a bug or the default? Make no mistake: this isn’t a bug. It’s a fundamental breakdown in how Google translates a text string into a physical coordinate. When this translation fails, your business ends up with a misplaced map pin, which directly misplaces your local proximity authority. When Google can’t find a high-confidence match at the building level, it doesn’t just leave your pin floating. Instead, it falls back to the most reliable geographic feature it can confidently resolve. In most cases, that fallback is the city centroid (the geographic center of the municipality tied to your address). Google’s own Geocoding API documentation outlines this fallback logic, explaining why pins for businesses with perfectly visible, verified addresses sometimes end up dumped in the middle of a city. Simply put, if your address isn’t recognized by Google’s internal systems, the geocoding process lacks the confidence to place the pin precisely. If Google can’t reconcile your GeostoreAddressProto with a high level of certainty, it may not anchor your GeostorePointProto to your building’s rooftop. Dig deeper: The proximity paradox: Beating local SEO’s distance bias When does geocoding lose confidence? Geocoding loses confidence when a business shares a generic building footprint, lacks a distinct suite number, or is placed in a newly developed zone that Google’s Street View API hasn’t yet mapped. A building that’s newly constructed or recently added to a commercial complex may not yet exist in Google’s geographic database with enough detail for a rooftop-level match. The street and city exist, but the specific parcel hasn’t accumulated enough mapping data for Google to confidently place a pin. To understand why, it helps to know how Google’s geocoding data actually gets populated. Google’s own developer documentation states that data collection is a periodic process, and new construction data can take time to be reflected in Google Maps. The address hierarchy Google geocodes against is built from a combination of sources, including satellite imagery updates, municipal records, and USPS address data, none of which updates in real time. When the API resolves an address, it returns one of four location types: ROOFTOP, RANGE_INTERPOLATED, GEOMETRIC_CENTER, or APPROXIMATE. The suite number problem I’ve said this to clients more times than I can count. It seems like a minor formatting detail. It isn’t. When a business enters something like 1234 Main Street, Suite 200, in Address line 1, Google’s geocoding engine attempts to resolve that entire string as a street address. Suite numbers are unit identifiers. They exist within buildings. They aren’t street-level geographic data, and Google’s geocoding process doesn’t use them to identify rooftop locations. Embedding a suite number in Address line 1 introduces a conflict into the geocoding query that the system can’t cleanly resolve against a physical coordinate. Instead of anchoring the pin to your building, the geocoding process encounters a string it can’t fully parse at the street level, loses confidence, and falls back, often all the way to the city centroid. This may cause clients to drive to another location or the middle of the highway. Proximity at the pin vs. proximity at the address A profile verified at a physical address doesn’t rank based on the visible address. I recently managed a new listing where a geocoding conflict forced the map pin to the city center of Houston, miles from the actual office. While the text on the profile showed the correct street address, the ranking was anchored entirely to a misplaced coordinate in the downtown centroid. In this instance, a suite number was embedded directly into the primary address field. When Google’s system can’t cleanly parse a street number and name, it often defaults to the city centroid as the best available data point. This isn’t an edge case. Whether it’s a suite number on the wrong line or a new construction site, these formatting errors trigger geocoding failures that are notoriously difficult to unwind. The client’s ranking data confirmed the technical reality. For high-competition terms like “water damage restoration,” the business didn’t rank based on its physical office. It ranked based on where the pin was dropped. If your pin is in a highway median or a city center due to a formatting error, that is where your proximity authority lives. Map ranking in downtown Houston Map ranking at the office Get the newsletter search marketers rely on. See terms. What this means for service area businesses If you have a service-area business, the stakes are higher, and the scenarios are more complex. When Google reprocesses that address, and the geocoding fails to anchor cleanly from the beginning, the business owner has no easy way to know. A storefront owner can open Google Maps, pull up driving directions to their location, and immediately see where the pin landed. An SAB with a hidden address can’t do the same quick check. The address isn’t visible on the profile, and the pin placement isn’t clearly surfaced in the dashboard or on Maps. The business is left with poor ranking reports and no obvious explanation. They may never realize the pin drifted at all. Their verified address may be a home office or a shared workspace, and if it’s a shared workspace, the geocoding problem gets worse. Regus locations and similar co-working buildings are among the most geocoding-hostile addresses an SAB can use. These are large commercial buildings with dozens or hundreds of unit numbers, multiple tenants, and high address turnover. My hypothesis is that Google’s geocoding engine assigns lower confidence to these addresses precisely because the unit-level data is so dense and inconsistently mapped. The result is a pin that may never anchor properly to begin with, and an SAB operator who has no easy way to verify where Google actually thinks they’re located. Dig deeper: The local SEO gatekeeper: How Google defines your entity The Farmington Hills fallback My business’s GBP functioned as a verified storefront in Farmington Hills for years. Three years ago, I moved the operation to a new office in Pontiac and updated the address accordingly. The listing appeared as a storefront until I triggered a reverification while testing a separate case study. Because I work primarily from home, and hadn’t invested in signage at the new Pontiac location, Google forced the profile into service area business status. Even though the dashboard displayed a Pontiac address for several months, the map pin reverted to Farmington Hills as soon as I toggled to hide the address. This fallback exists behind the scenes, effectively anchoring the business to a location it hasn’t occupied in over a thousand days. This is a ranking disaster for any business owner. I struggle to rank in my city for the “marketing agency” category because Google is calculating my proximity from an old office. If a business transitions from a storefront to an SAB after changing addresses, editing the existing listing is a risk. I was set up as a storefront at the new address for several months. The most effective path forward is to create a new listing for the business and request a review transfer. This can’t be fixed by Google support. Supporting evidence: What Google’s own patents say Google has filed and been granted multiple patents that describe the underlying systems at work. These patents are directly relevant to how geocoding, pin placement, and local ranking interact. Patent IDTitleImpact on Local SEOUS8312010B1Local Business Ranking Using Mapping InformationOutlines the core pipeline connecting an address to a map pin, establishing that the inputted address and the resolved geocode are two separate entities.US8046371B2Scoring Local Search Results Based on Location ProminenceDescribes a dual scoring system: documents within a geographic area are scored by location prominence factors (authoritative document score, citation volume, review count, and mention count), while documents outside the area are scored by distance from a defined center point such as a postal code centroid or the midpoint of the active map window.US20090177643Geocoding Multi-Feature AddressesExplains how ambiguous or improperly parsed address components produce lower-confidence geocode outputs, resulting in broader map pin placements rather than rooftop-level matches.US7894984B2Digital Mapping SystemDescribes the geocoding/geomap server that converts a street address into a single latitude/longitude coordinate and overlays it as a location marker on a map image. Establishes the mechanical basis for map pin placement and documents that pin position is derived from the resolved coordinate, not the inputted address. Best practices for properly anchoring your map pin A well-geocoded address with a narrow service radius gives Google the most confident, stable picture of where your business operates. Check your Address line 1: Suite numbers, unit numbers, floor numbers, and building names belong in Address line 2. Line 1 should contain only the street number and street name. Check whether your building geocodes cleanly: You can test this in Google Maps directly, or search your address in the developer’s geocoding page and see where the pin lands. Or more importantly, see how Google is parsing the address, and enter it the same exact way. Be prepared for verification: Correcting a geocoding conflict in an existing profile almost always triggers a new verification request. This is expected. Work through it. Don’t make additional edits until verification is complete, as multiple pending changes can restart the cycle. Why geocoding confidence is your local ranking foundation The friction between an address string and Google’s geocoding confidence isn’t a minor technical glitch. It’s a fundamental ranking blocker. Google values data stability and confidence over your recent dashboard edits. If you’re struggling with a pin that refuses to anchor, or an SAB that won’t rank, you’re likely fighting a geocoding pin placement issue that can’t be solved with standard optimizations or Google support, for that matter. Stop trying to out-content a broken map pin. It’s the ultimate proximity indicator that Google needs to confidently rank your business. The underlying issue isn’t complicated. Google needs a clean, parseable address string to anchor your pin at the building level. View the full article

You’ve spent years building a robust professional network. You’ve cultivated relationships with peers, mentors, and industry leaders. So when you signal that you’re exploring new opportunities, you expect your network to perform. Yet too often, promising conversations dissolve into silence. Warm introductions never materialize. Emails go unanswered. This isn’t a reflection of your professional standing. It’s a design problem: you’re making it too hard for people to help you. The fix is straightforward. Make it easy. Here are three ways to do so. Ask To Write to Their Contact Directly When you reach out to a contact seeking an introduction to a decision-maker, a common response goes something like this: “Absolutely — send me your résumé and I’ll forward it to see if there’s interest.” It sounds helpful, but rarely is. The fundamental problem: you’ve just handed over control of your own job search to someone with a dozen other priorities. Even the most well-intentioned contact may not follow through—because the timing isn’t right for their colleague (the chances they need your résumé at any given moment are small), because it slipped off their radar, or because the introduction they made on your behalf didn’t do you justice. The solution is to reclaim the driver’s seat. When a contact offers to pass your résumé along, respond with something like: “I really appreciate it. To save you time, could I reach out to your colleague directly and simply mention that I was referred by you? I’m also looking to build a relationship for opportunities now or down the road, so I would rather not forward a resume that implies I need a job quickly. Would this work?” This proposal removes the burden from your contact while giving you control over the pitch. It also avoids the résumé-forward trap—a résumé implies “please hire me now,” when your real goal is to get an informational meeting with a decision-maker and then keep in touch for future opportunities or get additional referrals. Half of your networking contacts will agree, and now you can use their name to gain attention: “Subject: Referred by [Contact], re: [Topic].” But what about the contacts who want to make the introduction themselves? Send a Forward-Friendly Email Many contacts will respond with something along the lines of “Let me reach out to my colleague first to see if they’d be interested in speaking with you.” In that case, offer to send them a forward-friendly email. This move dramatically improves the likelihood that they will actually follow through, because you’ve reduced their effort from 15 minutes spent figuring out how to pitch you to just 2 minutes of forwarding. You’re also improving the odds that their contact will want to meet with you, since you can include a field-tested pitch explaining why a conversation could be mutually beneficial. The content is virtually the same as the “Referred by …” email; just start it differently: “Subject: Introduction to Katherine Johnson, re: BigCo Dear Rosalind, Thanks for offering to forward my information to Katherine. As discussed, below I’ve shared my background and why I believe a meeting could be mutually beneficial.” One important note on content: resist the urge to attach your résumé unless there’s a specific opening you’re pursuing. Instead, use your LinkedIn profile as your “low-key résumé.” The impressive content in your thoroughly filled-out profile will drive credibility without signaling desperation. Have a Clear Job Target Too many executives prolong their searches because they position themselves too broadly, not wanting to miss an opportunity. The problem: your network finds it harder to advocate for you when your message is watered down across multiple job targets. Worse, you may be asking your contacts to do the heavy lifting of translating your varied background into specific opportunities. That is your job, not theirs. One client came to me after a long, frustrating search. I quickly saw the issue: she was pitching herself to her network as open to Partnerships leadership roles at Fortune 500 companies, COO roles at startups, or Commercialization roles at any company. Three quite varied targets, not connected by a strong theme, led to ineffective messaging. Once we prioritized, she re-launched her outreach with a focused, powerful pitch for COO roles at startups. Within weeks, the interviews began to materialize. A narrow pitch may feel counterintuitive—but it’s what makes your networking more effective, since people can refer you more easily when they see you clearly in a specific role. The Bottom Line Your network wants to help. Your job is to make that help feel effortless—not like a second job. Write the emails they can forward, or email their contacts directly. Do the targeting they shouldn’t have to. And keep yourself in the driver’s seat. The opportunities will follow. View the full article

Google announced Search Live has launched globally, for all languages and locations where AI Mode is available. Google said this is possible by its "new audio and voice model, Gemini 3.1 Flash Live, which delivers even more natural and intuitive conversations."View the full article

As part of a strategic move to optimize its store footprint, Noodles & Company closed 33 company-owned restaurants in 2025. In January, the chain said it would close dozens more stores this year. However, despite the shrinking restaurant count, sales have grown. The fast-casual eatery held its fourth-quarter and full-year 2025 earnings call on Wednesday, March 25. It reported that comparable store sales increased 6.6% in the final quarter of 2025. Sales growth and traffic are also up as of early 2026. Following the strong earnings report, shares of Noodles & Company (Nasdaq: NDLS) soared over 50% on Thursday. The stock is up almost 60% year to date as of premarket trading on Friday. That’s a significant contrast to the broader Nasdaq Composite, which is down 7.78% for 2026 so far. How store closures have helped same-store sales Despite having closed more than 30 stores in 2025, Noodles & Company reported system-wide comparable store sales growth of nearly 7% in the fourth quarter of 2025. On Wednesday’s earnings call, CEO Joe Christina told investors that the restaurant closures “resulted in a material transfer of sales to nearby locations . . . which also favorably impacted margins.” And store closures haven’t stopped customers from spending money. CFO Mike Hynes explained during the call that a significant portion of Noodles & Company customers place takeout or delivery orders, so they’ve continued to order from nearby locations that remain open. “The most meaningful impact is the post-closure transfer of sales to nearby Noodles & Company restaurants, which is driving a significant increase to our company-wide restaurant-level profits.” New menu items also drove traffic Menu changes and limited-time offerings have also played a significant role in driving sales and traffic growth, Christina said on the call. “A great example is chili garlic ramen, which we introduced as a limited time offer in October,” he said. “Inspired by trending ramen hacks, this brothless bowl delivered the buttery, spicy, umami-packed flavors guests were already craving. It quickly became one of the strongest [limited-time offers] in our history.” He noted that the trendy dish resonated well with loyalty program members and also brought in new customers. Because of its success, Noodles & Company is evaluating other ramen recipes. Christina also credits the fast-casual noodle chain’s value-focused messaging, “giving guests compelling meal combinations and an attractive price point that delivered balance, variety, and everyday affordability without compromising quality, while also raising consumer awareness to our new menu offerings.” Hourly workers have been most impacted by the store closures While an optimized physical footprint may be producing results for the company, store closures have come at a real cost to employees, primarily hourly workers. According to Noodles & Company’s year-end 2025 10-K filing with the Securities and Exchange Commission (SEC), the fast-casual eatery employed approximately 6,000 hourly workers as of December 30, 2025, down from 6,800 a year prior. That’s a net loss of roughly 800 hourly jobs in one year. Meanwhile, the company’s salaried worker headcount remained unchanged during that same period, with 500 salaried workers reported for both years. View the full article

Google announced that it will begin to highlight data quality account issues related to Vehicle ads within Google Merchant Center. This will begin in mid-April 2026.View the full article

Google Ads and Merchant Center is expanding the Loyalty program features to highlight key perks, expand local and regional visibility, expand internationally and within AI Mode and Gemini.View the full article

This week’s PPC Pulse covers Performance Max reporting updates, GA4 budget planning tools, and Veo AI video in Google Ads. The post Google Adds Scenario Planner, Performance Max Updates, And Veo – PPC Pulse appeared first on Search Engine Journal. View the full article

Hello again, and welcome back to Fast Company’s Plugged In. Before we get underway, a little self-promotion: Apple’s 50th anniversary is on April 1. As the big day approached, I realized that many people present at the company’s creation were still very much with us. So I interviewed 23 of them for an oral history, “How Apple Became Apple: The Definitive Oral History of its Earliest Years.” It’s chock-full of great tales as told by everyone from cofounder Steve Wozniak to Liza Loop, the first Apple user. Hearing these pioneers reminisce, I felt like I had been there, too—and so will you, I think. Here’s the article. When OpenAI launched its Sora app last September, the video-centric social network arrived on a tide of buzzy goodwill. Its feed of 10-second video clips had a TikTok-esque vibe—except that it was filled with AI-generated stuff instead of anything remotely real. In less than a minute, Sora users could create digital doppelgängers of themselves that were eerily convincing for use in their own clips and, optionally, those created by others. The result was playful, goofy fun, and far more intriguing than Meta’s theoretically similar but painfully bland Vibes. But if Sora ends up being remembered for anything, it won’t be for existing. Instead, it will have made its mark by going away. On March 25, OpenAI announced that it was killing the app, along with the Sora API that let developers generate their own videos using the company’s technology. The decision appeared hasty: OpenAI still hasn’t shared details on when, exactly, Sora will cease to exist, or how users can download their videos for preservation. Most of the insta-reaction I’ve seen to Sora’s demise amounts to grave tap-dancing of one sort or another. People are helpfully explaining that the app was a stupid idea from the start, or assailing it as a slop machine that deserved its fate. But I’m not ashamed to admit that I will miss it. For reasons I wrote about shortly after its debut, escaping to Sora’s weird little world always brightened my day. For one thing, I found the app to be a genuine canvas for creativity, albeit in brief, inherently inconsequential bursts. My feed was full of fake commercials, fabricated vintage news clips, and other snippets of fantasy content that were like glimpses of bizarre alternate realities. An oddball crew of deceased celebrities—Larry King, Richard Nixon, Queen Elizabeth II—often starred in them, sometimes in uncannily convincing form and sometimes as vague approximations. On an internet that can feel unrelentingly grim, Sora’s essential absurdity made me laugh. Counterintuitively, I also found comfort in the fact that the app was all AI, all the time. Conventional social media such as Facebook, Instagram, and TikTok is now befouled by true AI slop, generated solely to try and attract eyeballs without working very hard. Being exposed to it always feels like an imposition. On Sora, however, I never had to wonder if something was real or not. It wasn’t, and that was the point. I do acknowledge that the app peaked early. The world needs only so many silly imaginary gadget commercials and clips of unlikely celebrities rapping—both my feed and my own ideas for prompts grew repetitive over time. If OpenAI had added more features, or let us create videos longer than 10 seconds, it might have helped the platform develop more substance. Now we’ll never know. Still, I’m not going to make the case that OpenAI’s seemingly abrupt decision to shutter Sora is a terrible mistake. It might actually be a commendable, responsible act—or even the beginning of a trend for the entire AI industry. On March 16, before that move was public, The Wall Street Journal’s Berber Jin reported that Fidji Simo, OpenAI’s CEO of applications, had sent a memo to employees declaring that it was time to get down to business. She sent it at a time when archrival Anthropic had made enormous inroads with its Claude Code software-generation tool, the hottest product in AI’s hottest category. “We cannot miss this moment because we are distracted by side quests,” Simo wrote. “We really have to nail productivity in general and particularly productivity on the business front.” One element of this strategy recalibration involves OpenAI releasing a “super app” that rolls ChatGPT, Codex, and the Atlas web browser into one piece of software, roughly akin to what Anthropic has already done with the Claude desktop app. As excerpted by Jin, Simo’s memo did not name-check Sora. In retrospect, though, her call to action left it a dead app walking. Rather than facilitating productivity, Sora was frivolous to its core. I certainly got sucked into it any number of times when I had better things to do. But OpenAI isn’t terminating Sora because it might divert users from more productive tasks. It’s doing it because it’s a pricey distraction for the company itself. That OpenAI is suddenly interested in self-discipline is news in itself. Until now, after all, its strategy has seemingly been to do, well, everything. ChatGPT in its current form is just the beginning. The company is also into enterprise agents! Health advice! Epoch-shifting gadgets! Browsers! Chips! Smut, though it’s been delayed! That’s before you get to the unprecedented investment in data center infrastructure it will have to build out to generate all that AI. Maybe a huge, wildly profitable company could reasonably attempt to digest such a sprawling menu of projects simultaneously. OpenAI is not that company. Like much of the AI in our lives, Sora has been running on a gigantic subsidy provided by venture-capital dollars. In November, Forbes’s Phoebe Liu guesstimated that OpenAI might be spending $15 million per day spitting out Sora videos. No analysis performed by an outsider stands a chance of nailing the precise cost, but this we know: Video generation is among the most computationally expensive AI tasks, and OpenAI had yet to book its first nickel of Sora user revenue. (It had inked a “landmark agreement” with Disney to use that company’s characters inside Sora, but that $1 billion deal is now off.) If Sora stood a chance of being a profit machine someday, absorbing its current losses—which, over the course of a year, would have likely been in the billions—might not have been wholly irrational. But substantial profit would have come only if the app’s user base had grown gigantic and OpenAI figured out a brilliant way to weave ads into the experience. Though not impossible, that feat would have required vast intellectual capital and tolerance for risk. By comparison, OpenAI focusing on ensuring that its Codex AI software-generation tool is a compelling alternative to Claude Code—one companies are happy to pay for—sounds dead easy. Who can blame Simo for opting not to pursue “side quests” when it’s imperative to get the core ones right? As rational as OpenAI giving up on Sora may be, I hope that it doesn’t represent an end to the theory that a rewarding social network might someday be built around AI-fueled content. The evidence that AI can make social experiences much, much worse is all around us. Given that the technology isn’t going anywhere, I choose to cling to the possibility that someone will figure out how to adopt it in a constructive manner. Maybe even one that won’t bankrupt the company that offers it. You’ve been reading Plugged In, Fast Company’s weekly tech newsletter from me, global technology editor Harry McCracken. If a friend or colleague forwarded this edition to you—or if you’re reading it on fastcompany.com—you can check out previous issues and sign up to get it yourself every Friday morning. I love hearing from you: Ping me at hmccracken@fastcompany.com with your feedback and ideas for future newsletters. I’m also on Bluesky, Mastodon, and Threads, and you can follow Plugged In on Flipboard. More top tech stories from Fast Company This Microsoft security team stress-tests AI for its worst-case scenarios The company’s Red Team simulates attacks to uncover risks before bad actors do. Read More → A top AI researcher explains the limitations of current modelsFrançois Chollet talks about his deceptively simple new benchmark test for AI models. Read More → Manus AI cleaned up my computer—for a price The desktop app can automate all kinds of tedious computing tasks, but the costs can quickly get out of hand. Read More → Exclusive: This new benchmark could expose AI’s biggest weakness ARC-AGI-3 tests whether models can reason through novel problems, not just recall patterns, a task even top systems still struggle to do. Read More → Writer wants to be the go-to AI tool kit for the enterprise With customizable ‘skills’ and step-by-step ‘playbooks,’ the company aims to help employees automate workflows without touching code. Read More → This brilliant browser tool purposely makes AI chatbots worseThe extension’s designer calls it a ‘tiny tool of digital sabotage.’ Read More → View the full article

Google officially announced the rollout of the March 2026 core update early Friday morning at around 5:14 ET. This core update is expected to take up to 2 weeks to roll out. Google said this "is a regular update designed to better surface relevant, satisfying content for searchers from all types of sites."View the full article

Google announced several new steering updates for Google Ads Performance Max including first-party audience exclusions, budget reporting, full audience reporting and network segmentation in placement reporting.View the full article

Microsoft Bing is testing using rounded corners on short videos and normal videos within the Bing search results interface. Bing used to show these as squared-off edges.View the full article

Alex Balazs has spent more than two decades inside Intuit, starting as an engineer working on early versions of QuickBooks Online, when moving financial workflows to the internet still felt experimental. Now, as CTO, he is helping lead a more radical shift: turning financial software into systems that can think and act on a user’s behalf. “This combines the speed and scale of AI with human judgment and accountability,” he tells Fast Company. For decades, financial software has functioned as a ledger, categorizing transactions and generating reports about what has already happened. That model is beginning to break. Advances in AI are pushing the category toward real-time interpretation and action, with software that can execute tasks and manage workflows rather than simply record them. The shift introduces a core tension. Financial systems demand precision, accountability, and auditability. AI systems operate probabilistically, producing outputs based on likelihood rather than certainty. As the stakes rise, so does the challenge of trusting machines with financial decisions. Intuit is pushing aggressively into that gap. The company, which controls more than 60% of the SMB accounting software market, is working to turn finance into what it calls a “system of intelligence,” a continuously operating layer that understands financial context and acts on it in real time. Its platform processes roughly 60 billion machine learning predictions per day across a data infrastructure spanning 180 petabytes, serving nearly 100 million consumers and 10 million small and midmarket businesses. The strategy is already translating into growth. In its most recent quarter, Intuit reported $4.7 billion in revenue, up 17% year over year, with operating income rising 44% on a GAAP basis. The company says its platform facilitates close to $890 billion in money movement and $336 billion in payroll annually. Under Balazs, Intuit has built what it calls its Generative AI Operating System, or GenOS, designed to coordinate models, data, and workflows into task-specific agents that can execute complex financial operations. Through partnerships with OpenAI and Anthropic, the company is also embedding those capabilities into external AI ecosystems while maintaining control over customer data. Still, the central question remains: If AI begins to function like an autonomous CFO, who is responsible when something goes wrong? Speaking with Fast Company, Balazs argues the answer is not full automation, but a new architecture of trust, and a rethinking of how human expertise fits into increasingly autonomous financial systems. This conversation has been edited for length and clarity. When AI agents are autonomously handling accounting, tax preparation, and cash flow, where do you draw the line between assistance and authority? And should businesses be comfortable handing over that level of decision-making to systems that are, at their core, probabilistic? The customer is always in ultimate control of critical decision-making and is provided with the needed data to help make those decisions. As we continue to build “done-for-you” experiences for customers on the Intuit platform, we’re creating capabilities and experiences where work is done for the customer on our AI-driven expert platform, with their permission. We’ve always put the power in our customers’ hands. This gives us a durable competitive advantage because it’s what matters most to customers when it comes to financial tasks is instilling complete confidence in their high-stakes financial decisions. Leveraging proprietary data, domain-specific AI platform capabilities and human intelligence, our system of intelligence uses deterministic domain-specific models built on decades of trusted proprietary data. Intuit Intelligence provides answers grounded in its own proprietary data and will take action on the user’s behalf, through automation and with a handoff to a trusted AI-enabled human expert. This is intelligence rooted in lived financial reality, not generic large language models. As the industry pushes toward full automation, why keep humans so deeply embedded in financial workflows? Where does that handoff actually happen, and what ensures the human layer remains a real safeguard, not just a symbolic one as AI improves? We’ve learned that for financial workflows, AI alone is not enough for confidence. Customers have a psychological need for a “data trail” back to the balance sheet. Our QuickBooks Live offering is growing alongside AI because human experts provide a “domain expert check,” showcasing the power of human intelligence. While AI handles the high-volume categorization, humans provide the “final mile” of context to ensure accuracy. Queries in our system of intelligence aren’t just searches. They hit a “conversational front door” that triggers our Generative AI Operating System (GenOS) to query proprietary data against live transaction data. We address the “confidence gap” through a “show your work” approach, providing a data trail back to the balance sheet and ensuring there are “no dead ends” by handing off complex tasks to live experts (e.g., tax, bookkeeping). One of the surprises we’ve seen in our system of intelligence: We expected accounting questions, but new-to-QuickBooks users are using AI to architect their entire business, even asking about warehouse organization and employee handbooks, for example. Rather than relying on automation alone, we are utilizing human review, oversight, and feedback to validate high-impact outputs, catch errors, refine model performance, and improve decisions over time. Intuit has marketed GenOS as the orchestration layer. But as the industry moves toward model-agnostic architectures, with partners like OpenAI and Anthropic, is the real moat shifting away from models to orchestration and data ownership? And if so, what stops that layer from becoming standardized or commoditized as competitors and cloud platforms build similar capabilities? We built our Generative AI Operating System (GenOS) to solve an enormous challenge: making generative AI broadly available for all product teams to develop solutions that integrate the technology safely and responsibly into applications on our platform. In today’s rapidly evolving tech world, our LLM-agnostic strategy gives Intuit technologists the freedom to choose from a catalog of best-in-class commercial LLMs (15+ LLMs, 70+ versions) and our own proprietary custom-trained Intuit Financial LLMs. GenOS includes embedded guardrails for security with protections designed to address risks such as prompt injection, data leakage, and harmful outputs, all within a broader responsible AI governance framework. The platform also uses standardized runtime and user-experience layers so teams can build, monitor, and improve AI features consistently, helping deliver more reliable performance and a stable experience at scale across products. Intuit operates across consumers, SMBs, and now the mid-market, while ERP vendors, fintechs, and cloud providers all push to own the enterprise AI layer. What is the platform’s key differentiator and real moat in this race? And as incumbents embed AI into their stacks and hyperscalers control the infrastructure, what prevents Intuit from getting squeezed in the middle as the market consolidates? We’re at the beginning of a new era of agent-led growth in financial services that represents a massive tailwind for Intuit in our next chapter. Service-as-software built on data, AI, and human intelligence is delivering solid double-digit revenue growth for Intuit with expanding margins and massive customer impact. This plays to Intuit’s platform advantage—and why we’re built for this moment. Our AI and human intelligence platform innovation is fueling Intuit’s growth and delivering significant customer benefits. We enable businesses to operate from lead to cash, and help consumers from credit building to wealth building, all in a regulated environment. We aren’t just “using data,” we are grounding queries in 625,000 financial attributes per business and 24,000 bank connections on our platform. And as we scale, the business model strengthens: the more customers we engage, the more insights we gain, which improve recommendations, outcomes, and value for every customer. This creates a powerful network effect that reinforces our competitive advantage. You’re running 60 billion predictions a day on deeply sensitive financial data, yet even the best models can hallucinate or make errors. How do you reconcile that tension between near-perfect accuracy requirements and inherently imperfect systems? Who is ultimately accountable when an agentic AI-driven financial decision goes wrong? Our platform deploys multiple advanced technologies that draw on our large and relevant data sets designed to help ensure we’re delivering accurate answers to customers and mitigating the risk of hallucination or other types of inaccurate or inappropriate answers. When our AI provides an answer or gives guidance to a customer, it’s drawing on the deep expertise that Intuit has developed over many years, plus the data that gives us a 360-degree view of the customer. This helps make sure the answer given is relevant and grounded in the customer’s own data. The company has taken a firm stance on data sovereignty, keeping customer data within Intuit while still embedding capabilities into ecosystems like OpenAI and Anthropic. How do you balance that openness with control? And if models increasingly become the primary interface, is there a risk that the platform layer gets abstracted away despite those safeguards? Customers are establishing relationships with AI tools such as ChatGPT and Claude, and we want to show up at their point of need. Consumers and businesses using Intuit capabilities within these tools get personalized insights and recommendations powered by the platform to take certain actions. We want to be where our customers are and continue to own the customer relationship and data. Security and privacy are within our platform, and we selectively apply user data at the user’s request to power trusted, accurate responses in ChatGPT and Claude when a user is logged into their Intuit account. If AI agents take over execution, finance teams inevitably shift from doing the work to supervising it. In your view, what does the future finance organization actually look like? Are we heading toward a world of AI auditors and system overseers, or is there a risk that over-automation erodes financial intuition and literacy in ways we don’t yet fully understand? AI is already contributing to significant growth in the finance industry. This is especially apparent with data-driven digital brands—approximately 92% of companies that use AI in finance say they’ve either met or exceeded ROI expectations. AI is redefining how teams and organizations run and compete. As the role of AI in finance evolves, there’s a clear shift toward intelligence-driven finance operations. Long-term success, though, will depend on balance. Industry leaders must still find ways to leverage human talent if they want to thrive. At the same time, they’ll need to build internal systems that emphasize accountability and responsibility. View the full article