OpenAI\u00a0Chief Financial Officer\u00a0Sarah Friar\u00a0said Thursday (April 30) that the company is meeting its objectives.
The post OpenAI CFO Says Company Hits Core Targets Despite Stretch Goals appeared first on PYMNTS.com.
\n", "content_text": "OpenAI\u00a0Chief Financial Officer\u00a0Sarah Friar\u00a0said Thursday (April 30) that the company is meeting its objectives.\r\n\t\r\n\t\t\r\n\t\r\n\r\n\r\n\t\nInterviewed by Bloomberg for a\u00a0report\u00a0published Thursday, Friar said that if anything is slowing OpenAI down at all,\u00a0it\u2019s\u00a0not a lack of demand, but a lack of\u00a0compute.\nFriar\u2019s remarks came three days after the Wall Street Journal reported Monday (April 27) that OpenAI had fallen short of its\u00a0internal goals\u00a0for new users and revenue and that some of the company\u2019s executives, including Friar, were concerned about whether the firm would be able to fund its data center plans if its revenue didn\u2019t grow quickly enough.\nBloomberg reported Tuesday (April 28) that OpenAI described the WSJ report as \u201cprime clickbait\u201d and that the company said its consumer and enterprise\u00a0businesses are \u201cfiring on all cylinders\u201d and \u201cthe mood internally is incredibly positive.\u201d\nFriar told Bloomberg Thursday that OpenAI may have internal \u201cstretch goals\u201d that are more ambitious than its publicly shared goals, but that demand for the company\u2019s products continues to grow.\n\u201cEvery company I\u2019ve ever been inside of in my entire CFO life, and as an analyst, always has stretch goals \u2014 always,\u201d Friar said, per the report.\nThe Information reported that OpenAI is projecting a giant shift in subscription revenue but still sees revenues more than doubling\u00a0to\u00a0$30 billion\u00a0this year and reaching\u00a0$284 billion\u00a0in 2030.\nThe report said that while OpenAI has pulled in the bulk of its revenue from consumers\u2019 $20-per-month ChatGPT subscriptions over the last three years, the company now expects that a cheaper, ad-supported subscription tier will attract\u00a0new users\u00a0but also lead existing subscribers to downgrade. The company hopes to generate more revenue by selling ads to more users than depending on its existing flagship monthly subscription service, ChatGPT Plus.\nIt was reported April 9 that OpenAI expects its nascent\u00a0advertising\u00a0business to generate\u00a0$2.5 billion\u00a0in revenue this year and surge to\u00a0$100 billion\u00a0by the end of the decade. The report said the company\u2019s projections underscore its push to monetize its user base to help fund the soaring costs of developing its AI technology.\n\r\n\r\nThe post OpenAI CFO Says Company Hits Core Targets Despite Stretch Goals appeared first on PYMNTS.com.", "date_published": "2026-05-01T20:00:02-04:00", "date_modified": "2026-05-01T20:00:02-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2025/05/OpenAI-1.jpg", "tags": [ "AI investments", "AI startups", "News", "OpenAI", "PYMNTS News", "What's Hot", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=3700046", "url": "https://www.pymnts.com/artificial-intelligence-2/2026/ai-takes-the-wheel-at-europes-biggest-carmakers/", "title": "AI Takes the Wheel at Europe\u2019s Biggest Carmakers", "content_html": "Artificial intelligence (AI) is running on the production line, inside the vehicle and within the investment thesis. Europe\u2019s premium automakers are moving on all fronts at once.
The post AI Takes the Wheel at Europe\u2019s Biggest Carmakers appeared first on PYMNTS.com.
\n", "content_text": "Artificial intelligence (AI) is running on the production line, inside the vehicle and within the investment thesis. Europe\u2019s premium automakers are moving on all fronts at once.\r\n\t\r\n\t\t\r\n\t\r\n\r\n\r\n\t\nThe pressure behind that movement is specific. Order-to-delivery flows across disconnected systems, multiple suppliers and dozens of handoffs. By the times teams learn about a delay, it has already hit the schedule. Inventory builds in the wrong place, small disruptions cascade and manual tracking fails at scale. AI fixes that by monitoring workflows in real time and triggering interventions before delays reach the customer.\nAI Enters the Factory\nAudi, BMW and Mercedes-Benz are running AI across production operations. Automotive News reported that all three brands use AI-powered image processing to detect welding defects in real time. Issues get flagged before they move down the line. Defect rates fall without slowing throughput.\nBMW has gone further. Nvidia reported that BMW is deploying autonomous mobile robots inside its factories to handle material transport without human guidance. Parts move to the line as needed. The logistics layer coordinates itself.\nBCG documented BMW Group\u2019s generative AI program scaling across engineering, manufacturing and supply chain operations. The program compressed development timelines and reduced manual decision-making across the organization. The outcome was not incremental. It changed how the company moves information and acts on it.\nCapital Follows the Conviction\nBMW i Ventures launched its third fund at $300 million on Wednesday (April 29), bringing total capital under management to $1.1 billion. Fund III targets physical AI, agentic AI, industrial software, manufacturing technologies, supply chain technologies and advanced materials, investing from seed through Series B across North America and Europe.\nManaging partner Marcus Behrendt said the firm focuses on what will actually determine the future, not what is trending. The AI Insider noted that BMW Group is already deploying humanoid robots at its Leipzig plant in Germany as part of a European pilot expanding physical AI in vehicle production, building on a 2025 program at its Spartanburg, South Carolina plant.\nThe fund backs startups early enough to shape how the technology develops. The thesis is direct: AI will define the next generation of automotive suppliers, and BMW wants equity in the companies building that layer now.\nIntelligence Moves Into the Vehicle\nThe investment logic extends from the factory to the car itself. Mercedes-Benz announced a multi-year partnership with Liquid AI to deploy embedded, on-device intelligence across its vehicles in North America.\nLiquid AI stated that the embedded Liquid Foundation Models deliver fast, private AI without cloud dependence, evolving the MBUX Virtual Assistant by integrating voice control, vehicle functionality and contextual understanding into a more capable in-vehicle experience. According to the release, initial production deployment is scheduled for the second half of 2026.\nThe architecture matters beyond the in-car experience. On-device AI processes data locally without sending it to a server. That same design principle applies upstream. AI running inside production systems does not wait for a nightly report. It reads the order queue, tracks supplier lead times, monitors assembly progress and flags the gap before it becomes a delay.\nAI is not a feature added to an existing process. It is the coordination layer replacing manual oversight across the full order-to-delivery chain. For European automakers competing with software-native rivals from the United States and China, the window to build that infrastructure is not open indefinitely. BMW, Mercedes-Benz and Audi are treating that deadline as vital.\nFor all PYMNTS AI coverage, subscribe to the daily AI Newsletter.\n\r\n\r\nThe post AI Takes the Wheel at Europe\u2019s Biggest Carmakers appeared first on PYMNTS.com.", "date_published": "2026-05-01T19:05:41-04:00", "date_modified": "2026-05-01T19:05:41-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" }, "tags": [ "AI", "Audi", "automotive", "BMW", "digital transformation", "manufacturing", "Mercedes Benz", "News", "PYMNTS News", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=3699702", "url": "https://www.pymnts.com/artificial-intelligence-2/2026/big-insurance-backs-away-from-ai-risk-and-startups-rush-in/", "title": "Big Insurance Backs Away From AI Risk and Startups Rush In", "content_html": "A company deploys an artificial intelligence (AI) agent. The agent makes a mistake. The insurance policy does not cover it.
The post Big Insurance Backs Away From AI Risk and Startups Rush In appeared first on PYMNTS.com.
\n", "content_text": "A company deploys an artificial intelligence (AI) agent. The agent makes a mistake. The insurance policy does not cover it.\r\n\t\r\n\t\t\r\n\t\r\n\r\n\r\n\t\nThat outcome is no longer hypothetical. Major insurers are carving AI out of standard corporate coverage. State regulators are approving the requests and a new market is already forming to fill the gap.\nCarriers Signal They Cannot Price the Risk\nBerkshire Hathaway, Chubb and Travelers sought state regulatory approval to exclude AI-related damages from general liability policies. State regulators approved more than 80% of those requests, The Information reported. Florida, Connecticut and Maryland approved the highest number of requests. The exclusions began taking effect as early as January.\nThe moves follow two new optional endorsements introduced by the Insurance Services Office, a private body that sets industry standards. Policyholder Pulse reported that some carriers, including Berkley, have introduced absolute AI exclusions across directors and officers, errors and omissions and fiduciary liability policies. The endorsements cover bodily injury, property damage and personal and advertising injury tied to generative AI outputs, including defamatory content, intellectual property infringement and physical damages traceable to AI-driven errors.\nPHL Firm noted that ISO forms underpin roughly 82% of U.S. property and casualty policies. Adoption is expected to be rapid. Many carriers will attach these endorsements at renewal.\nWhat Falls Outside Coverage Now\nPlaintiffs have advanced a wide range of legal theories in AI-related filings. Policyholder Pulse catalogued the categories: copyright and intellectual property claims arising from large language model training, privacy and data-use claims, antitrust claims, discrimination and algorithmic bias claims and AI-related securities class actions. Each now sits in a grayer zone for businesses whose carriers have secured AI exclusions.\nInsurers are also moving to cap AI losses in cybersecurity policies, the Financial Times reported. That narrows options across multiple policy types at once. Policyholder Pulse flagged that courts have not yet settled how broadly these exclusions will be applied and that for some policyholders the effect could render their coverage illusory. PHL Firm found that small to mid-sized firms, often without specialized coverage, face the greatest exposure.\nA New Market Fills the Gap\nSpecialized firms are stepping in. Munich Re and startups including Corgi, Armilla, Mayflower Specialty and Embroker now offer standalone AI liability policies, The Information reported. Coverage limits range from $2 million to $50 million. Premiums range from a few hundred dollars to several hundred thousand dollars annually.\nThe pattern mirrors how insurers handled cybersecurity a decade ago. A wave of attacks triggered corporate claims. Businesses argued successfully that traditional policies covered the losses because the policies did not explicitly exclude them. Insurers carved cyber out of standard coverage and built standalone products. That market matured. Now, the AI liability market is starting the same process.\nThe tension sits inside the industry itself. PYMNTS reported that insurance giants are deploying AI agents to orchestrate entire workflows across claims, underwriting and policy servicing. Those same carriers are simultaneously pulling AI coverage from the policies they sell. PYMNTS also reported that AI is beginning to transform underwriting itself, compressing timelines and changing how risk gets priced. Insurers are betting on AI internally while refusing to absorb AI risk externally.\nPHL Firm advised businesses to review existing policies for new endorsements with their brokers and consider seeking affirmative AI coverage through technology errors and omissions policies, cyber liability insurance, or emerging standalone AI products. Strengthening internal AI governance, conducting bias testing and disclosing AI use can also reduce exposure.\nInsurers are not saying AI is uninsurable. They are saying they do not yet know what it costs. Until they do, the risk sits with the businesses deploying the technology.\n\r\n\r\nThe post Big Insurance Backs Away From AI Risk and Startups Rush In appeared first on PYMNTS.com.", "date_published": "2026-05-01T16:04:27-04:00", "date_modified": "2026-05-01T16:04:27-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2026/05/AI-insurance-risks.jpeg", "tags": [ "AI", "Insurance", "News", "PYMNTS News", "risk management", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=3698888", "url": "https://www.pymnts.com/artificial-intelligence-2/2026/erp-data-can-fuel-enterprise-ai-so-why-wont-vendors-let-it/", "title": "ERP Data Can Fuel Enterprise AI. So Why Wont Vendors Let It?", "content_html": "The tech stack powering the office of the CFO is evolving from a monolith to an ecosystem. And it\u2019s resulting in some growing pains, as corporate customer pushback on new rules around API access from one of the world\u2019s largest enterprise software providers, SAP,\u00a0reveal.
The post ERP Data Can Fuel Enterprise AI. So Why Wont Vendors Let It? appeared first on PYMNTS.com.
\n", "content_text": "The tech stack powering the office of the CFO is evolving from a monolith to an ecosystem. And it\u2019s resulting in some growing pains, as corporate customer pushback on new rules around API access from one of the world\u2019s largest enterprise software providers, SAP,\u00a0reveal.\r\n\t\r\n\t\t\r\n\t\r\n\r\n\r\n\t\nCustomers want clearer guidance on what they can and cannot build using SAP data and interfaces. At first glance, the issue may appear procedural. But beneath that request lies a deeper concern about risk. Enterprises operating at scale cannot afford to invest in artificial intelligence (AI)-driven workflows or integrations that may later run afoul of compliance rules. In an environment where regulatory scrutiny is already high, this degree of ambiguity can function as a deterrent.\nThe complaint itself is not unusual; large enterprise customers often push back on licensing or technical constraints. What makes this moment different is the context of accelerating AI adoption and intensifying integration demands.\nStrategic issues, not purely technological ones, are at the center of the debate, which reflects a broader shift across enterprise software as vendors are tighten control over data and interfaces just as customers start to seek greater flexibility to deploy AI tools and cross-platform workflows.\nMore here: The Classic ERP Model Is Dying. What Comes Next?\u00a0\nWhen Policy Friction Turns to Innovation Risk\nFor years, enterprise software vendors have walked a careful line between openness and control. Too much openness risks security gaps and lost revenue; too much control can risk suffocating the very ecosystem that makes a platform valuable.\nWhile policies like SAP\u2019s are not new, what has changed is the level of scrutiny being applied to them. Customers and user groups argue that the latest iteration of API rules introduces uncertainty around what constitutes permissible use, particularly when APIs are leveraged for AI training, automation or cross-platform data orchestration.\nIn the pre-AI era, ambiguity-driven delays might have been absorbed into normal enterprise timelines. Today, they can carry competitive consequences.\nThe PYMNTS Intelligence report \u201cSmart Spending: How AI Is Transforming Financial Decision Making\u201d found that more than 8 in 10 CFOs at large companies are either already using AI or considering adopting it.\nAnd as\u00a0FIS\u00a0Head of Product Management, Payment Networks\u00a0Mladen Vladic\u00a0wrote in a new PYMNTS eBook, \u201cAI Runs Payments. Governance Decides What Happens Next,\u201d integration is key to ensuring effective AI governance.\nUnlike traditional enterprise applications, AI systems are inherently integrative. They require access to multiple data sources, often in real time, and they derive value from connecting previously siloed systems. In this context, APIs are not optional but foundational.\nSAP did not immediately reply to PYMNTS request for comment.\nSee also: CFOs Turn to AI Harnesses as Agentic Capabilities Scale\u00a0\nCFOs See ERP Data as Key Unlock For AI \nEnterprise resource planning (ERP) systems sit at the core of corporate data infrastructure. They contain financial records, supply chain data, procurement workflows and operational metrics. These are the very datasets that AI systems rely on to generate insights and automate decisions.\n\u201cThere\u2019s a continuous evolution and \u2026 dynamic disruption in finance that requires\u00a0CFOs\u00a0to harness data and AI to make finance more efficient, more effective and substantially more strategic,\u201d\u00a0Raj Seshadri,\u202fchief commercial payments officer at Mastercard, told PYMNTS in an earlier interview.\nAs companies race to embed AI into everything from forecasting to customer service, ERP data has become a strategic asset. But unlocking that asset requires seamless integration across platforms, including cloud data warehouses, third-party analytics tools, and increasingly, generative AI models.\nSee also:\u00a0Agentic B2B Is Here. Are Your Contracts and Invoices Ready?\n\u201cWe see challenges around\u00a0legacy ERP systems\u00a0with limited AR API capabilities,\u201d\u00a0Michael Younkie, vice president of product management at\u00a0Billtrust, told PYMNTS in an earlier interview. \u201cWe like to tie clear measurable KPIs to upfront things like DSO reduction, straight-through processing, digital invoice adoption.\u201d\nThe technology stack for AI is advancing rapidly, with new models, tools and platforms emerging at a relentless pace. If access to data cannot keep up, the entire ecosystem may slow down.\nThe irony is that ERP vendors themselves are heavily investing in AI capabilities. SAP, like its peers, is embedding AI into its own products, positioning itself as a central platform for intelligent enterprise operations. PYMNTS covered earlier how SAP\u00a0is pushing\u00a0agentic AI\u00a0deeper into its ERP suite.\nUltimately, just as reliable systems enable business operations, reliable rules can enable innovation. When customers understand the boundaries, they can push up against them confidently. When they do not, they stay well within them or even step away entirely.\n\r\n\r\nThe post ERP Data Can Fuel Enterprise AI. So Why Wont Vendors Let It? appeared first on PYMNTS.com.", "date_published": "2026-05-01T12:05:52-04:00", "date_modified": "2026-05-01T12:05:52-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2026/05/B2B-ERP-AI.jpeg", "tags": [ "AI", "API", "B2B", "digital transformation", "ERP", "News", "PYMNTS News", "SAP", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=3698100", "url": "https://www.pymnts.com/artificial-intelligence-2/2026/pentagon-links-with-7-ai-giants-after-anthropic-dispute/", "title": "Pentagon Links With 7 AI Giants After Anthropic Dispute", "content_html": "The Defense Department has signed agreements with seven frontier artificial intelligence (AI) companies, saying these deals will provide it with flexibility and prevent \u201cAI vendor lock.\u201d
The post Pentagon Links With 7 AI Giants After Anthropic Dispute appeared first on PYMNTS.com.
\n", "content_text": "The Defense Department has signed agreements with seven frontier artificial intelligence (AI) companies, saying these deals will provide it with flexibility and prevent \u201cAI vendor lock.\u201d\r\n\t\r\n\t\t\r\n\t\r\n\r\n\r\n\t\nThe agreements with Amazon Web Services (AWS), Google, OpenAI, Microsoft, Nvidia, Reflection and SpaceX enable the deployment of the companies\u2019 AI capabilities on the Department\u2019s classified networks, the Department said in a Friday (May 1) press release.\n\u201cThe Department will continue to build an architecture that prevents AI vendor lock and ensures long-term flexibility for the Joint Force,\u201d the release said. \u201cAccess to a diverse suite of AI capabilities from across the resilient American technology stack will give warfighters the tools they need to act with confidence and safeguard the nation against any threat.\u201d\nThis announcement came about two months after the White House told federal agencies to stop using Anthropic\u2019s AI products, escalating a dispute that started inside the Defense Department but later touched the broader government.\nIt was reported at the time that the White House\u2019s decision came just ahead of a Pentagon deadline for Anthropic to agree that the military can use its models in \u201call lawful use cases,\u201d a concession the company refused. Anthropic reportedly wanted contract language that would prohibit use of its models for autonomous weapons and mass domestic surveillance.\nAccording to the Defense Department\u2019s Friday press release, its agreements with the seven AI companies enable the deployment of their AI capabilities \u201cfor lawful operational use.\u201d\nThese capabilities will help the Pentagon streamline data synthesis, elevate situational understanding and augment warfighter decision-making, supporting warfighting, intelligence and enterprise operations, according to the release.\nThe Department said in a Friday post on X that the agreements are \u201cthe latest initiative in our mandate to create an AI-FIRST WAR DEPARTMENT.\u201d\nMichael Kratsios, director of the White House Office of Science and Technology Policy and assistant to the President for science and technology, said in a Friday post on X: \u201cWe are committed to ensuring our warfighters have the best tools at their disposal.\u201d\nThe Defense Department\u2019s official AI platform, GenAI.mil, has been used by 1.3 million Department personnel who have generated tens of millions of prompts and deployed hundreds of thousands of agents over the past five months, per the Friday press release.\n\u201cWarfighters, civilians and contractors are putting these capabilities to practical use right now, cutting many tasks from months to days,\u201d the release said.\nThe Defense Department announced in December 2025 that GenAI.mil was its \u201cnew bespoke AI platform\u201d and that Google Cloud\u2019s Gemini was the first of several frontier AI capabilities to be housed on the platform.\nGoogle Cloud said at the time in a blog post that on GenAI.mil, the company\u2019s Gemini for Government AI platform would support unclassified business processes for 3 million civilian and military personnel.\nThe Department said in its Friday press release that AI is \u201cindispensable to national security\u201d and that American leadership in the technology requires \u201ca thriving domestic ecosystem of capable model developers that enable the full and effective use of their capabilities in support of Department missions.\u201d\n\r\n\r\nThe post Pentagon Links With 7 AI Giants After Anthropic Dispute appeared first on PYMNTS.com.", "date_published": "2026-05-01T10:28:44-04:00", "date_modified": "2026-05-01T10:28:44-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2026/05/Defense-Department-AI.jpeg", "tags": [ "AI", "artificial intelligence", "Department of Defense", "Government", "News", "PYMNTS News", "What's Hot", "white house", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=3697382", "url": "https://www.pymnts.com/artificial-intelligence-2/2026/chargebacks911-prevents-false-declines-as-agentic-commerce-scales/", "title": "Chargebacks911 Prevents False Declines as Agentic Commerce Scales", "content_html": "Chargebacks911 offers tools that solve a growing challenge for merchants: legitimate artificial intelligence shopping agents getting turned away by fraud detection systems, resulting in merchants losing potential revenue, the company said in a Thursday (April 30) press release emailed to PYMNTS.
The post Chargebacks911 Prevents False Declines as Agentic Commerce Scales appeared first on PYMNTS.com.
\n", "content_text": "Chargebacks911 offers tools that solve a growing challenge for merchants: legitimate artificial intelligence shopping agents getting turned away by fraud detection systems, resulting in merchants losing potential revenue, the company said in a Thursday (April 30) press release emailed to PYMNTS.\r\n\t\r\n\t\t\r\n\t\r\n\r\n\r\n\t\nThis challenge has arisen because even as agentic commerce scales with the support of major corporations, fraud systems designed around earlier technologies have not kept pace and are misclassifying legitimate agents as malicious bots, according to the release.\n\u201cAs agentic commerce scales, merchants face a clear choice: adapt their detection and evidence infrastructure now, or watch a growing share of legitimate revenue get declined by their own systems,\u201d Chargebacks911 Founder and CEO Monica Eaton said in the release.\nChargebacks911, a provider of chargeback prevention and remediation technology, offers solutions for agentic commerce in the form of the Unified Dispute Management System (UDMS) and ResolveLab platforms, according to the release.\nThese tools use AI and machine learning to handle agentic transactions by capturing the full consent and permission trail and then giving merchants and financial institutions the visibility they need to distinguish between legitimate agent transactions and malicious automated activity, per the release.\n\u201cThe organizations that build that capability now will not only reduce false declines; they will have a structural advantage as AI-driven purchasing becomes the norm,\u201d Chargebacks911 Chief Technology Officer Donald Kossmann said in the release.\nThe PYMNTS Intelligence report \u201cAgents of Change: How Agentic AI Is Redefining Commerce\u201d found that agentic AI is reshaping commerce with autonomous transactions, redefining customer trust and creating a $1.7 trillion opportunity for those ready to lead.\nAmong retailers, 43% are piloting autonomous AI and 81% trust the technology\u2019s ability to operate autonomously if the right guardrails are in place.\n\u201cAgentic AI-driven retail is no longer theoretical \u2014 it\u2019s here and already beginning to transform commerce,\u201d the report said. \u201cBusinesses that act now will set the benchmarks for trust, speed and customer experience. Those that delay risk being eclipsed by early adopters defining the next digital economy.\u201d\nAnother PYMNTS Intelligence report, \u201cThe Hidden Costs of \u2018Good Enough\u2019: Identity Verification in the Age of Bots and Agents,\u201d found that inadequate digital identity systems are a revenue trap that slows onboarding, alienates customers and curbs expansion into new markets.\nFor all PYMNTS AI coverage, subscribe to the daily AI\u00a0Newsletter.\n\r\n\r\nThe post Chargebacks911 Prevents False Declines as Agentic Commerce Scales appeared first on PYMNTS.com.", "date_published": "2026-04-30T21:17:33-04:00", "date_modified": "2026-04-30T21:17:33-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2026/04/chargebacks-1.jpg", "tags": [ "Agentic AI", "agentic commerce", "AI", "chargeback", "Chargebacks911", "News", "PYMNTS News", "What's Hot", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=3697193", "url": "https://www.pymnts.com/artificial-intelligence-2/2026/cancer-never-saw-the-algorithm-coming/", "title": "Cancer Never Saw the Algorithm Coming", "content_html": "Pancreatic cancer kills most of its patients because there is nothing to find by the time they feel sick. Colorectal cancer kills roughly 53,000 Americans a year for the same reason.
The post Cancer Never Saw the Algorithm Coming appeared first on PYMNTS.com.
\n", "content_text": "Pancreatic cancer kills most of its patients because there is nothing to find by the time they feel sick. Colorectal cancer kills roughly 53,000 Americans a year for the same reason.\r\n\t\r\n\t\t\r\n\t\r\n\r\n\r\n\t\nThe same week that a new philanthropic push pledged $500 million to build artificial intelligence (AI) systems that model disease at the cellular level, two separate research teams published evidence that AI can already see what radiologists cannot.\nMayo Clinic\u2019s Model Reads a Normal Scan Differently\nThe numbers behind Mayo Clinic\u2019s new AI are striking.\nA Mayo Clinic-developed model called REDMOD can detect pancreatic cancer on routine abdominal CT scans up to three years before a clinical diagnosis, identifying subtle signs of disease before tumors are visible, when curative treatment may still be possible, Mayo Clinic News Network reported Wednesday (April 29).\nResearchers analyzed nearly 2,000 CT scans, including scans from patients later diagnosed with pancreatic cancer that were originally interpreted as normal. REDMOD identified 73% of those prediagnostic cancers at a median of about 16 months before diagnosis, nearly double the detection rate of specialists reviewing the same scans without AI assistance.\nThe advantage compounded over time. In scans obtained more than two years before diagnosis, the AI identified nearly three times as many early cancers that would otherwise go undetected, Mayo Clinic News Network reported.\nThe stakes are real. More than 85% of pancreatic cancer patients receive a diagnosis after the disease has already spread, and five-year survival rates remain below 15%, according to the National Cancer Institute. Projections show pancreatic cancer will become the second-leading cause of cancer-related death in the U.S. by 2030.\nREDMOD works by measuring quantitative imaging features that describe tissue texture and structure, capturing faint biological changes before any visible mass forms. The model runs automatically without time-intensive manual preparation and was validated across CT scans from multiple institutions, imaging systems and protocols, Mayo Clinic News Network reported. It is designed to analyze scans already obtained for other reasons, particularly in high-risk patients such as those with new-onset diabetes.\nAlibaba\u2019s Tool Outpaces Radiologists on a Different Cancer\nThe same week, Alibaba\u2019s research arm Damo Academy published results for a parallel effort targeting colorectal cancer. Its Coca AI model accurately identified five previously missed cases of colorectal cancer from the non-contrast CT scans of more than 27,000 people, achieving a sensitivity of 86.6% and a specificity of 99.8%.\nDamo Academy said Coca outperformed 10 radiologists of varying experience levels by 20.4% on sensitivity, the South China Morning Post reported. The research was developed with Chinese institutions including Guangdong General Hospital and published in the Annals of Oncology. Current diagnostic methods for colorectal cancer, including colonoscopy and CT colonography, are invasive and create discomfort for patients, whereas Coca has the potential to be a non-invasive, cost-effective and scalable tool, according to Damo researchers.\nBiohub Bets $500 Million on the Deeper Problem\nThe detection breakthroughs matter. But the infrastructure bet announced the same week signals where the field is heading.\nThe Chan Zuckerberg Biohub committed $500 million over five years to AI-driven biology, with $400 million going toward its own work and $100 million aimed at spurring others, Axios reported Wednesday. According to the report, Zuckerberg said last year that Biohub\u2019s long-term goal is to cure all human disease through the intersection of AI and biology.\nThe stated goal is not incremental. Biohub chief Alex Rives told Axios that the usefulness of an AI model\u2019s prediction increases exponentially as the scale of the data grows. Most current datasets cover about a billion cells. The aim is to reach an order of magnitude or more beyond that, Rives said.\nBiohub is focused on frontier AI and frontier biology, using large-scale models for virtual cells, immune reprogramming and disease prediction, Fortune reported. The ambition sits upstream of what REDMOD and Coca are doing. Scan-reading AI catches disease once the body has already started changing. A virtual cell model, if it works as theorized, could predict which patients will reach that point at all.\nFor all PYMNTS AI coverage, subscribe to the daily AI Newsletter.\n\r\n\r\nThe post Cancer Never Saw the Algorithm Coming appeared first on PYMNTS.com.", "date_published": "2026-04-30T19:18:09-04:00", "date_modified": "2026-04-30T19:18:09-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2026/04/AI-cancer-detection-healthcare.jpeg", "tags": [ "AI", "AI investments", "Healthcare", "News", "PYMNTS News", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=3696868", "url": "https://www.pymnts.com/artificial-intelligence-2/2026/anthropic-outage-shows-digital-reliability-cracking-under-ais-weight/", "title": "Anthropic Outage Shows AI Is Straining the Digital Stack", "content_html": "The five nines gold standard of digital reliability is cracking in 2026.
The post Anthropic Outage Shows AI Is Straining the Digital Stack appeared first on PYMNTS.com.
\n", "content_text": "The five nines gold standard of digital reliability is cracking in 2026.\r\n\t\r\n\t\t\r\n\t\r\n\r\n\r\n\t\nThe benchmark of 99.999% uptime availability, or the \u201cfive nines\u201d that represent just over five minutes of downtime per year, has long reassured executives, underpinned service-level agreements and shaped capital allocation decisions. In today\u2019s hyperconnected, compute-intensive economy, that promise is starting to look more like a relic than a reality.\nAnthropic\u2019s Claude AI model, for example, had slipped below the threshold as of Thursday (April 30) to around 98% uptime for the past 90 days. In China, the government reportedly suspended its issuance of new licenses for robotaxis and other autonomous connected electric vehicles, which are typically dependent on cloud-linked systems, after dozens of Baidu\u2019s vehicles temporarily lost their functionality mid-use.\nApple\u2019s weather app suffered an hourslong outage this week, a relative rarity across the tech giant\u2019s typically airtight ecosystem, and even Microsoft\u2019s code hosting platform, Github, on Tuesday (April 28) posted an apology to its software developer base for recent downtime issues. The platform flagged AI\u2019s power-hungry needs as a key factor.\n\u201cThe main driver is a rapid change in how software is being built. Since the second half of December 2025, agentic development workflows have accelerated sharply,\u201d wrote Vladimir Fedorov, GitHub\u2019s chief technology officer.\nAnd Fedorov is right. The modern digital stack bears little resemblance to the monolithic architectures of the past. Today\u2019s systems are composable, distributed and deeply layered. A single enterprise workflow might rely on a large language model, a cloud provider, multiple APIs, and a network backbone spanning continents and satellites.\nSee also: Smart Firms Treat Vendor Risk Like Their Own\u00a0\nComplexity Is the New Risk\nIndividually, the recent downtime incidents might be dismissed as routine hiccups. Collectively, they point to a deeper structural shift: the systems underpinning modern commerce are more powerful than ever, but also more fragile, more interdependent, and more prone to cascading failure.\n\u201cFor the past month I\u2019ve kept a journal where I put an \u2018X\u2019 next to every date where a GitHub outage has negatively impacted my ability to work. Almost every day has an \u2018X.\u2019 On the day I am writing this post, I\u2019ve been unable to do any PR review for ~2 hours because there is a\u00a0GitHub Actions outage,\u201d \u00a0wrote Hashicorp Co-Founder Mitchell Hashimoto in a Tuesday post.\nElsewhere, on April 25, an AI coding agent managed to delete the production database and \u201call volume-level backups\u201d belonging to the startup PocketOS.\n\u201cI serve rental businesses. They use our software to manage reservations, payments, vehicle assignments, customer profiles, the works. This morning \u2014 Saturday \u2014 those businesses have customers physically arriving at their locations to pick up vehicles, and my customers don\u2019t have records of who those customers are,\u201d Jer Crane, founder of PocketOS, wrote in a lengthy article on X, noting that this incident caused a cascading series of issues that persisted for more than 30 hours.\nIt\u2019s not just corporations, or software and AI startups, that are being impacted. The U.S. military ran into trouble in mid-April when a global outage of the Starlink satellite network disrupted several autonomous operations.\nOutages are no longer isolated events; they are becoming networked disruptions with unpredictable blast radii. For CFOs, this can change the calculus. Reliability can no longer be assessed solely vendor by vendor. It instead is more and more being evaluated as a portfolio of interdependencies.\n\u201cPlatform resiliency and\u00a0business continuity planning,\u00a0in my opinion, has been our number one unsung hero,\u201d\u00a0Rinku Sharma, chief technology officer at\u00a0Boost Payment Solutions, told PYMNTS in an earlier interview.\nRead also:\u00a0PYMNTS Execs Say Resilience Isn\u2019t a Buzzword. It\u2019s Their Business Model\nBudgeting for Failure\nThe paradox of modern operations is that as digital systems become more advanced, they also become more sensitive to disruption.\nPart of the challenge lies in the sheer scale of modern compute demands. AI workloads, in particular, are pushing infrastructure to its limits. Training and inference require vast amounts of processing power, memory bandwidth, and energy, often concentrated in specific regions or clusters.\nMeanwhile, physical infrastructure, ranging from data centers to satellite networks and beyond, remains subject to real-world constraints. Weather, power supply, hardware failures and geopolitical factors all play a role. Achieving near-perfect uptime across complex, distributed ecosystem may require exponential investment in redundancy, monitoring and failover mechanisms.\nFor finance teams, then, the question may no longer be one of whether to invest in reliability, but instead how to balance cost, risk and performance. The challenge for organizations is to adapt their operating models accordingly. This may mean embracing uncertainty, designing for resilience, and aligning financial planning with the realities of modern infrastructure.\nFor all PYMNTS AI coverage, subscribe to the daily AI\u00a0Newsletter.\n\r\n\r\nThe post Anthropic Outage Shows AI Is Straining the Digital Stack appeared first on PYMNTS.com.", "date_published": "2026-04-30T17:09:10-04:00", "date_modified": "2026-04-30T21:29:56-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2026/04/AI-cracking-1.jpg", "tags": [ "AI", "AI infrastructure", "Anthropic", "github", "News", "PYMNTS News", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=3696752", "url": "https://www.pymnts.com/artificial-intelligence-2/2026/elevenlabs-opened-a-music-store-while-taylor-swift-lawyered-up/", "title": "ElevenLabs\u00a0Opened a Music Store While Taylor Swift Lawyered Up\u00a0", "content_html": "Generative artificial intelligence (AI) changed the economics of music fast. The harder questions about authorship, ownership, what a song is worth and who it belongs to are still unanswered. ElevenLabs built a platform anyway.
The post ElevenLabs\u00a0Opened a Music Store While Taylor Swift Lawyered Up\u00a0 appeared first on PYMNTS.com.
\n", "content_text": "Generative artificial intelligence (AI) changed the economics of music fast. The harder questions about authorship, ownership, what a song is worth and who it belongs to are still unanswered. ElevenLabs built a platform anyway.\r\n\t\r\n\t\t\r\n\t\r\n\r\n\r\n\t\nThe voice AI company, valued at $11 billion after a $500 million Series C in February, relaunched Eleven Music as a consumer platform for AI music. Billboard reported that users can now stream, create and remix music directly on the platform. A free tier covers seven songs per day; a Pro tier at $9.99 per month raises that ceiling to 500 tracks monthly.\nThe relaunch marks a pivot. When ElevenLabs first launched Eleven Music in August, it was a production library tool aimed at brands, agencies and studios. Now it\u2019s going after consumers.\nFrom Tool to Platform: Controlling the Full Stack\nSuno and Udio, two popular AI music generators, let users make songs. Eleven Music is trying to do something structurally different: wrap generation, distribution and revenue into one closed loop. The platform opens with a catalog of more than 4,000 independent and emerging artists, built to surface music outside mainstream recommendation algorithms. From there, users can take any track and shift its genre, tempo or style through a remix prompt. Those who want to start from scratch can build a composition from a lyric, mood or melody and publish it directly to the platform.\nMonetization is the pitch. ElevenLabs has already paid out over $11 million to creators through its voice library, and it\u2019s applying a similar model to music. Royalties are tied to listener engagement and platform revenue, as OfficeChai noted. The specific payout structure for the revamped consumer platform hasn\u2019t been disclosed, but Billboard reported that under the original 2025 licensing deals with Kobalt and Merlin, artists received a pro-rata share of a royalty pool weighted by how popular their songs were on other digital platforms. Whether that carries over is unconfirmed.\nSupply Becomes Infinite\nThe launch arrives as AI music tools have made recorded audio a commodity. Eleven Music holds licensing deals with Kobalt and Merlin, two independent music rights organizations, as Billboard reported. The licensing posture is a direct response to the legal backlash that reshaped the sector.\nAs Bloomberg reported, Sony Music, Universal Music Group and Warner Records sued both Suno and Udio in 2024 over the use of copyrighted recordings in their training data. Most of those cases have since been settled, with Suno reaching a licensing deal with Warner Music Group late last year. ElevenLabs says its model was trained on cleared content from the start.\nElevenLabs is pushing into enterprise licensing deals and artist partnerships on the strength of that position. When a platform can generate a commercially cleared track in seconds, the scarce resource in music stops being production and becomes trust: that a song is authentic, that an artist is real, that a voice belongs to the person it sounds like.\nArtists Lock Down What AI Can Copy\nTaylor Swift\u2019s company TAS Rights Management filed three trademark applications with the U.S. Patent and Trademark Office, two covering audio clips of her voice and one covering a stage photograph, according to Reuters. The trademarks are designed to protect Swift\u2019s voice and likeness from AI replication and deepfake misuse.\nSwift\u2019s voice has been used without consent in AI-generated content across advertising, political campaigns and explicit material. Actor Matthew McConaughey made similar filings earlier this year; he told The Wall Street Journal that the goal is to \u201ccreate a clear perimeter around ownership with consent and attribution the norm in an AI world.\u201d\nThe legal theory is novel. Audio trademarks do exist; the NBC chimes and MGM\u2019s lion roar are registered. But trademarking a celebrity\u2019s spoken voice as a defense against AI replication has no established precedent in U.S. courts.\n\r\n\r\nThe post ElevenLabs\u00a0Opened a Music Store While Taylor Swift Lawyered Up\u00a0 appeared first on PYMNTS.com.", "date_published": "2026-04-30T16:58:59-04:00", "date_modified": "2026-04-30T16:58:59-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2026/04/ElevenLabs-AI-music.jpeg", "tags": [ "AI", "entertainment", "generative AI", "Music", "News", "PYMNTS News", "Streaming", "artificial intelligence" ] }, { "id": "https://www.pymnts.com/?p=3696617", "url": "https://www.pymnts.com/artificial-intelligence-2/2026/netomi-raises-110-million-to-power-agentic-customer-experience/", "title": "Netomi Raises $110 Million to Power Agentic Customer Experience", "content_html": "Agentic artificial intelligence platform Netomi says it has secured $110 million in new financing.
The post Netomi Raises $110 Million to Power Agentic Customer Experience appeared first on PYMNTS.com.
\n", "content_text": "Agentic artificial intelligence platform Netomi says it has secured $110 million in new financing.\r\n\t\r\n\t\t\r\n\t\r\n\r\n\r\n\t\nThe funding round, announced Thursday (April 30) was led by Accenture Ventures, which will team with Netomi to bring the company\u2019s agentic customer experience (CX) offering to its enterprise clients.\n\u201cAgentic AI is opening an entirely new chapter for customer experience,\u201d Ndidi Oteh, CEO of Accenture Song, said in a news release.\n\u201cOne where brands can respond with greater empathy, consistency and intelligence at every touchpoint. Netomi\u2019s platform doesn\u2019t just make service faster; it strengthens the connection between people and the brands they trust.\u201d\nNetomi provides agentic CX systems for \u201clarge-scale, high-stakes environments\u201d operating under strict regulatory scrutiny. Clients including Delta Air Lines, MetLife, DraftKings, and the NBA use its services to manage customer interactions over email, chat and voice channels.\nPYMNTS explored the rise of AI as a CX tool last year in a conversation with Vinod Muthukrishnan, chief operating officer of Webex Customer Experience Solutions at Cisco. He explained that many financial institutions are moving past pilots and into deployment.\n\u201cThese firms are increasingly leveraging their AI focus on hyper-personalized CX such as personal financial advice or dynamic credit limit adjustments and offers, all enabled via real-time analytics,\u201d he told PYMNTS.\u00a0\nRetailers and service providers can enjoy similar opportunities, that report added, as long as they align strategy with measurable ROI. Projects that fail to provide lower handle times, better satisfaction scores, or reduced churn tend not to scale.\u00a0\n\u201cAI as with any new technology risks adoption and integration without a clear strategic alignment,\u201d Muthukrishnan warned. \u201cToo many pilots or implementations can lead to a fragmented focus.\u201d\nIn related news, PYMNTS wrote this week about the way agentic AI had begun to shift from \u201cconference-room promise to operating-room reality\u201d in the financial services space, with banks, insurers and asset managers now testing software agents on the manual work that can slow down decisions.\nThat report cites recent articles from Snowflake, KPMG and The Economist all touching upon the same theme: The first major gains are likely to result from giving AI agents tightly controlled tasks such as data gathering, checking documents, monitoring signals, routing approvals and preparing recommendations.\n\u201cThe larger shift is not simply faster automation,\u201d the report added. \u201cIt is a new model for financial work, one in which firms use stronger data foundations, clearer governance and human oversight to turn fragmented processes into more continuous workflows.\u201d\nFor all PYMNTS AI coverage, subscribe to the daily AI\u00a0Newsletter.\n\r\n\r\nThe post Netomi Raises $110 Million to Power Agentic Customer Experience appeared first on PYMNTS.com.", "date_published": "2026-04-30T16:23:21-04:00", "date_modified": "2026-04-30T16:24:59-04:00", "authors": [ { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" } ], "author": { "name": "PYMNTS", "url": "https://www.pymnts.com/author/pymnts/", "avatar": "https://secure.gravatar.com/avatar/679fcf5c2ed5358e99e8e23b22e3b5d761e37bdb76fa7b0e13d8ecd9ff01bf88?s=512&d=blank&r=g" }, "image": "https://www.pymnts.com/wp-content/uploads/2026/04/Netomi-AI-agents-1.jpg", "tags": [ "Agentic AI", "customer experience", "Netomi", "News", "PYMNTS News", "What's Hot", "artificial intelligence" ] } ] }