• After shocking quarter, IBM insists that AI isn’t killing the mainframe• Google justifies its massive AI spending with a booming cloud business• Treasury threatens sanctions after White House claims Moonshot distilled Anthropic’s Fable• How OpenAI’s human mistake led to the AI-powered hack on Hugging Face• Travis Kalanick’s robotics company raises $1.7B, led by a16z• Yope raises $12.3M to build a private social network without algorithms or ads• Monday.com lays off hundreds to focus on AI• Arcee, a US open source AI lab, says Chinese models are not inherently dangerous• Substack’s new tool tells you who’s been writing their newsletters with AI• OpenAI’s AI spending spree has ballooned to $750B• Menlo Ventures’ Matt Murphy explains what AI startups founders must do differently• The browser wars aren’t about search anymore — here are the best alternatives to Chrome and Safari• Passionfroot raises $15M to expand its B2B creator marketplace to the US• Glow emerges from stealth at $1.2B valuation to challenge endpoint security in the AI era• Synthesia’s AI training platform is moving beyond videos into live coaching• 3 Google updates from Galaxy Unpacked 2026• Connect more of your apps to Search• Create, edit and star in videos with two Google Vids updates• Celebrating 25 years of visual search innovation• Expanding Managed Agents in Gemini API: background tasks, remote MCP and more• The latest AI news we announced in June 2026• New York City educators and industry leaders gathered at Google’s offices to shape the future of AI in classrooms.• Unlocking Britain’s next era of productivity: Building a nation of AI trailblazers• Ask an AI expert: What exactly is the full stack?• Our latest Google Finance upgrades, including a new app• New research shows how AMIE, our medical AI, could help manage health conditions.• We’re strengthening our presence in Alabama through new investments and community support.• Our new community investments in Virginia support local jobs and expand energy affordability.• The latest AI news we announced in May 2026• 5 ways Google Search can level up your thrift and vintage shopping• Will your job be replaced by AI? Here are the roles most affected - BBC• Amazon Cuts Jobs in Artificial General Intelligence Unit - WSJ• Amazon cuts jobs in its artificial general intelligence group - Reuters• OpenAI Says Its A.I. Models Hacked Into Hugging Face, a Digital Library - The New York Times• China fires back at Trump administration claims that its AI companies steal U.S. tech - NBC News• China's Moonshot AI stole from Anthropic, Trump tech adviser says - BBC• Google Free Cash Flow Turns Negative Due to Massive AI Spend - Gizmodo• Stocks and the Economy Are Increasingly Relying on the A.I. Boom - The New York Times• This Is My Favorite Artificial Intelligence Stock to Buy Right Now (Hint: Not Nvidia, Broadcom, or Alphabet) - Yahoo Finance• Trump administration steers $5B toward AI research - Politico• Trump’s Plan for Science: More Money for A.I., Less for Universities - The New York Times• 5 projects at UW–Madison aimed at transforming science and energy with AI receive DOE Genesis Mission funding - UW–Madison News• EXCLUSIVE: DOGE alumni launch military cyber startup with $1.4 billion valuation - Reuters• Investigating Religious Bias In Leading Artificial Intelligence Models - Religion Unplugged• Manhattan University Announces Minor in Artificial Intelligence - Manhattan University• Building AI infrastructure with the Effingham County community• How news organizations are using AI to advance their vital missions• Advancing the next era of national science• Introducing OpenAI Presence• NTT DATA Group cuts incident analysis to 30 minutes with Codex• Introducing the ChatGPT for small business program• OpenAI and Hugging Face partner to address security incident during model evaluation• David Vélez and Robin Vince join the boards of the OpenAI Foundation and OpenAI Group PBC• Safety and alignment in an era of long-horizon models• A scorecard for the AI age• Why teens deserve access to safe AI• How Cars24 scales conversations and builds faster with OpenAI• The US is advancing AI safety through state and federal action• GPT-Red: Unlocking Self-Improvement for Robustness• How to manage AI investments in the agentic era• Here’s how to ask Gemini Live for help with anything you see.• 3 Google updates from Galaxy Unpacked 2026• 13 Google tips for a fun, productive summer off from college• Introducing Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber• 5 ways to build a side hustle with Gemini• How Gemini is speaking the language of Southeast Asia• Here’s how to make study notebooks in the Gemini app.• 3 ways this coffee shop is growing with Gemini• The latest AI news we announced in June 2026• Gemini Spark updates: macOS launch, connected apps and more• Start building with Nano Banana 2 Lite and Gemini Omni Flash• The Gemini app is bringing personalized image creation to more users.• Gemini can now take notes in Google Meet for Google AI Pro and Ultra subscribers.• Here's how Gemini can help you avoid jetlag.• Try these 3 Google AI tools to help find your next job.• The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs• The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials• The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix• The agent evaluation gap: Enterprise AI organizations have a reality-alignment problem, not a coverage problem — and most are shipping to production anyway• Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents• Google just redesigned the search box for the first time in 25 years — here’s why it matters more than you think.• Railway secures $100 million to challenge AWS with AI-native cloud infrastructure• Best Universities To Study AI in 2026• 10 top women in AI in 2026• Pope Leo XIV Declares AI a Threat to Human Dignity and Workers’ Rights• ChatGPT Is Making People Think They’re Gods and Their Families Are Terrified• AI May Soon Help You Understand What Your Pet Is Trying to Say• Netflix Adds ChatGPT-Powered AI to Stop You From Scrolling Forever• Murder Victim Speaks from the Grave in Courtroom Through AI• China Unveils World’s First AI Hospital: 14 Virtual Doctors Ready to Treat Thousands Daily• Katy Perry Didn’t Attend the Met Gala, But AI Made Her the Star of the Night• Therapists Too Expensive? Why Thousands of Women Are Spilling Their Deepest Secrets to ChatGPT• AI by Zapier: Add agentic AI steps to your workflows• How Mach 1 uses Zapier MCP to run AI operations across 25 different companies• The 5 best photo editing apps for iPhone and Android (including free options) in 2026• MuleSoft integrations: Capabilities and limitations• Zapier for enterprise orchestration: Scaling automation on a trusted platform• I've tried every automation software: here are the 10 best in 2026• Relay.app is shutting down: How to export your workflows and move to Zapier• Web scraping: A comprehensive guide• The 6 best vibe coding tools in 2026• Turn off your slop cannon• OpenClaw vs. Zapier: What's the difference? [2026]• Agentic AI vs. RPA: Everything you need to know• The best CRM software for real estate agents in 2026• 16 AI prompt templates for better AI agent outputs• Integrately vs. Zapier: Which is best? [2026]
Here’s how to ask Gemini Live for help with anything you see.
Gemini

Here’s how to ask Gemini Live for help with anything you see.

Have you ever struggled to describe something you’re looking at? Whether it’s a complex manual, a blinking error code, or a unique object, sometimes you just need an exp…

Google Free Cash Flow Turns Negative Due to Massive AI Spend - Gizmodo
"artificial intelligence" - Google News

Google Free Cash Flow Turns Negative Due to Massive AI Spend - Gizmodo

Google Free Cash Flow Turns Negative Due to Massive AI Spend  Gizmodo

How OpenAI’s human mistake led to the AI-powered hack on Hugging Face
AI News & Artificial Intelligence | TechCrunch

How OpenAI’s human mistake led to the AI-powered hack on Hugging Face

OpenAI made a mistake setting up what it called a “highly isolated” testing environment and sandbox. According to cybersecurity experts, that human mistake is what made the AI-powered attack on Hugging Face possible.

Amazon Cuts Jobs in Artificial General Intelligence Unit - WSJ
"artificial intelligence" - Google News

Amazon Cuts Jobs in Artificial General Intelligence Unit - WSJ

Amazon Cuts Jobs in Artificial General Intelligence Unit  WSJ

Travis Kalanick’s robotics company raises $1.7B, led by a16z
AI News & Artificial Intelligence | TechCrunch

Travis Kalanick’s robotics company raises $1.7B, led by a16z

Uber is also investing in Travis Kalanick's company Atoms, which has made gauzy claims about using industrial AI to modernize the world.

Monday.com lays off hundreds to focus on AI
AI News & Artificial Intelligence | TechCrunch

Monday.com lays off hundreds to focus on AI

The company said it is reducing its headcount by 20%, or about 630 staff, to "support a leaner, more focused operating model" as it focuses on its AI Work Platform.

Building AI infrastructure with the Effingham County community
OpenAI News

Building AI infrastructure with the Effingham County community

OpenAI announces Project Camellia in Effingham County, Georgia, with commitments to responsible energy, community investment, jobs, and access to Codex.

Substack’s new tool tells you who’s been writing their newsletters with AI
AI News & Artificial Intelligence | TechCrunch

Substack’s new tool tells you who’s been writing their newsletters with AI

Substack is giving readers a way to estimate how much of a newsletter was written by AI, signaling a broader shift toward transparency around AI-assisted content.

5 ways Google Search can level up your thrift and vintage shopping
AI

5 ways Google Search can level up your thrift and vintage shopping

Uncover second-hand scores with AI tools in Google Search and Shopping.

China fires back at Trump administration claims that its AI companies steal U.S. tech - NBC News
"artificial intelligence" - Google News

China fires back at Trump administration claims that its AI companies steal U.S. tech - NBC News

China fires back at Trump administration claims that its AI companies steal U.S. tech  NBC News

NTT DATA Group cuts incident analysis to 30 minutes with Codex
OpenAI News

NTT DATA Group cuts incident analysis to 30 minutes with Codex

NTT DATA Group uses ChatGPT Enterprise and Codex to help 9,000 employees automate work, cut incident analysis to 30 minutes, and scale secure AI adoption.

Our latest Google Finance upgrades, including a new app
AI

Our latest Google Finance upgrades, including a new app

The new Google Finance is coming out of beta and launching a new Android app.

Amazon cuts jobs in its artificial general intelligence group - Reuters
"artificial intelligence" - Google News

Amazon cuts jobs in its artificial general intelligence group - Reuters

Amazon cuts jobs in its artificial general intelligence group  Reuters

Arcee, a US open source AI lab, says Chinese models are not inherently dangerous
AI News & Artificial Intelligence | TechCrunch

Arcee, a US open source AI lab, says Chinese models are not inherently dangerous

As Chinese AI models grow in capability and popularity among U.S. companies, the arguing over what should be done about them has reached a fever pitch.

Advancing the next era of national science
OpenAI News

Advancing the next era of national science

OpenAI outlines its commitment to advancing American science working with the U.S. Department of Energy and national labs to use frontier AI to accelerate discovery.

The browser wars aren’t about search anymore — here are the best alternatives to Chrome and Safari
AI News & Artificial Intelligence | TechCrunch

The browser wars aren’t about search anymore — here are the best alternatives to Chrome and Safari

We’ve compiled an overview of some of the top alternative browsers available today aiming to challenge Chrome and Safari.

Expanding Managed Agents in Gemini API:  background tasks, remote MCP and more
AI

Expanding Managed Agents in Gemini API: background tasks, remote MCP and more

We’re announcing new capabilities in Managed Agents in Gemini API so developers can build reliable, production-ready agents.

Introducing OpenAI Presence
OpenAI News

Introducing OpenAI Presence

Introducing OpenAI Presence, a proven enterprise AI agent platform that helps organizations deploy trusted voice and chat agents for customer and internal workflows.

Connect more of your apps to Search
AI

Connect more of your apps to Search

You’ll be able to securely link and interact with your go-to services directly in AI Mode.

5 projects at UW–Madison aimed at transforming science and energy with AI receive DOE Genesis Mission funding - UW–Madison News
"artificial intelligence" - Google News

5 projects at UW–Madison aimed at transforming science and energy with AI receive DOE Genesis Mission funding - UW–Madison News

5 projects at UW–Madison aimed at transforming science and energy with AI receive DOE Genesis Mission funding  UW–Madison News

Unlocking Britain’s next era of productivity: Building a nation of AI trailblazers
AI

Unlocking Britain’s next era of productivity: Building a nation of AI trailblazers

Google UK shares its latest Economic Impact Report and how to enable more people to unlock the benefits of AI-powered technologies.

New York City educators and industry leaders gathered at Google’s offices to shape the future of AI in classrooms.
AI

New York City educators and industry leaders gathered at Google’s offices to shape the future of AI in classrooms.

Google, the New York Jobs CEO Council and Urban Assembly hosted an AI summit for 150 education and industry leaders.

Trump’s Plan for Science: More Money for A.I., Less for Universities - The New York Times
"artificial intelligence" - Google News

Trump’s Plan for Science: More Money for A.I., Less for Universities - The New York Times

Trump’s Plan for Science: More Money for A.I., Less for Universities  The New York Times

This Is My Favorite Artificial Intelligence Stock to Buy Right Now (Hint: Not Nvidia, Broadcom, or Alphabet) - Yahoo Finance
"artificial intelligence" - Google News

This Is My Favorite Artificial Intelligence Stock to Buy Right Now (Hint: Not Nvidia, Broadcom, or Alphabet) - Yahoo Finance

This Is My Favorite Artificial Intelligence Stock to Buy Right Now (Hint: Not Nvidia, Broadcom, or Alphabet)  Yahoo Finance

Treasury threatens sanctions after White House claims Moonshot distilled Anthropic’s Fable
AI News & Artificial Intelligence | TechCrunch

Treasury threatens sanctions after White House claims Moonshot distilled Anthropic’s Fable

The episode has also intensified a broader debate in Washington over the influx of Chinese open models.

Start building with Nano Banana 2 Lite and Gemini Omni Flash
Gemini

Start building with Nano Banana 2 Lite and Gemini Omni Flash

Scale your ideas with Nano Banana 2 Lite, our fastest, most cost-efficient Gemini Image model, and Gemini Omni Flash for high-quality video and conversational editing.

Pope Leo XIV Declares AI a Threat to Human Dignity and Workers’ Rights
DailyAI

Pope Leo XIV Declares AI a Threat to Human Dignity and Workers’ Rights

Pope Leo XIV is taking a bold stance on artificial intelligence, calling it “a challenge to human dignity, justice and labour” in his first major address since being elected leader of the Catholic Church. The new pontiff is placing AI at the center of the Church’s moral agenda, warning that we’re entering a new industrial revolution with the same threats to workers and human rights seen over a century ago. “In our own day… developments in the field of artificial intelligence pose new challenges,” Leo said, addressing the College of Cardinals on Saturday in the New Synod Hall. He echoed The post Pope Leo XIV Declares AI a Threat to Human Dignity and Workers’ Rights appeared first on DailyAI.

The latest AI news we announced in June 2026
AI

The latest AI news we announced in June 2026

Here are Google’s latest AI updates from June 2026.

Google justifies its massive AI spending with a booming cloud business
AI News & Artificial Intelligence | TechCrunch

Google justifies its massive AI spending with a booming cloud business

Google's cloud business is thriving, as companies adopting its AI and AI infrastructure services help the tech giant to report record profits.

Synthesia’s AI training platform is moving beyond videos into live coaching
AI News & Artificial Intelligence | TechCrunch

Synthesia’s AI training platform is moving beyond videos into live coaching

Synthesia launched AI Roleplay Sessions, an interactive enterprise training platform where employees practice workplace conversations with AI avatars that provide feedback, scoring, and analytics to help companies measure training effectiveness.

Gemini can now take notes in Google Meet for Google AI Pro and Ultra subscribers.
Gemini

Gemini can now take notes in Google Meet for Google AI Pro and Ultra subscribers.

Google Meet's "Take notes for me" feature is available to Google AI Pro and Ultra subscribers in select languages.

5 ways to build a side hustle with Gemini
Gemini

5 ways to build a side hustle with Gemini

Launching a side business? Use Gemini to design your side hustle, conduct market research and automate logistics.

Therapists Too Expensive? Why Thousands of Women Are Spilling Their Deepest Secrets to ChatGPT
DailyAI

Therapists Too Expensive? Why Thousands of Women Are Spilling Their Deepest Secrets to ChatGPT

More women are turning to ChatGPT for emotional support, using the AI chatbot as a stand-in therapist as mental health systems buckle under pressure. With long wait times and soaring costs, AI is filling a growing gap. Mental health care is harder to access than ever. In the UK, NHS data shows patients are eight times more likely to wait over 18 months for mental health treatment than for physical health. Private therapy isn’t always an option either, with sessions costing £60 or more. In that vacuum, ChatGPT has become a surprising outlet. Real voices, real feelings Charly, 29, from The post Therapists Too Expensive? Why Thousands of Women Are Spilling Their Deepest Secrets to ChatGPT appeared first on DailyAI.

New research shows how AMIE, our medical AI, could help manage health conditions.
AI

New research shows how AMIE, our medical AI, could help manage health conditions.

Research in “Nature” shows our conversational AI system matches primary care physicians in complex disease management.

The best CRM software for real estate agents in 2026
The Zapier Blog

The best CRM software for real estate agents in 2026

A CRM is your prized possession in real estate. You need something to keep things straight when juggling client management, property listings, and the looming threat of being upstaged by that insufferably smug agent from the office across the street. But with countless options on the market, how do you know which software is right for you? ​​I looked into dozens of options, read approximately a million reviews, watched demos narrated by people way too cheerful for 9 a.m., and gathered insights

3 Google updates from Galaxy Unpacked 2026
AI

3 Google updates from Galaxy Unpacked 2026

We shared how Samsung users can boost productivity and get time back on new foldables, watches, and glasses coming soon.

The Gemini app is bringing personalized image creation to more users.
Gemini

The Gemini app is bringing personalized image creation to more users.

Personal Intelligence makes the Gemini app feel tailored to you. With your permission, it pulls from Google tools like Gmail, Google Photos, YouTube and Search to provid…

Katy Perry Didn’t Attend the Met Gala, But AI Made Her the Star of the Night
DailyAI

Katy Perry Didn’t Attend the Met Gala, But AI Made Her the Star of the Night

Another year, another viral deepfake of Katy Perry at the Met Gala and once again, she wasn’t even there. Photos showing the pop star in a sleek black designer gown circulated widely on social media during Monday night’s event, matching the “Superfine: Tailoring Black Style” theme. But the images were AI-generated. Perry quickly clarified she was not at the Met; she was on tour. Perry’s reaction “Couldn’t make it to the MET, I’m on The Lifetimes Tour (see you in Houston tomorrow IRL),” she posted to Instagram alongside the fake images. She added a jab at AI confusion: “P.s. this The post Katy Perry Didn’t Attend the Met Gala, But AI Made Her the Star of the Night appeared first on DailyAI.

The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs
AI | VentureBeat

The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs

Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics. Most organizations run their AI on a familiar base of hyperscalers and model-provider APIs, yet the next dollar is aimed at specialized compute almost none of them use today; a majority intend to switch or add providers within the year, many within a quarter. Buying decisions turn on integration and total cost of ownership rather than headline token price — which is fortunate, because most enterprises cannot yet see their unit economics clearly: GPUs sit at half utilization or less, and fewer than half rigorously track what their compute actually costs. The result is a compute gap — heavy, fast-moving investment running ahead of the visibility needed to control it. This wave of VentureBeat Pulse Research examines enterprise AI infrastructure and compute: where organizations are in their deployment journey, what they run AI on today, how satisfied they are, what would make them switch, where they plan to evaluate their investments, and — most revealingly — how well they can measure and control the economics of the compute underneath it all. The central finding is a compute gap — the distance between how aggressively enterprises are investing in AI infrastructure and how little of its economics they can see. Only about one in five (21%) run AI in production at scale, yet spending intentions are outrunning that maturity: the single largest planned area enterprises plan to evaluate over the next year is AI-specialized clouds (45%), a layer almost none of these enterprises use today. Meanwhile the compute already in place runs cold — 83% report GPU utilization of 50% or less — and fewer than half (44%) can rigorously track what their AI compute costs. Enterprises are buying more infrastructure faster than they can account for what they already own. Enterprises are not settled on their infrastructure vendors, either: A clear majority (64%) plan to switch or add an infrastructure provider within twelve months, and 38% within the next quarter — unusually high churn intent for a category this foundational. When they choose, they choose on integration with the existing stack (41%) and total cost of ownership (35%), not on headline price: cost per million tokens is the deciding factor for just 8%. And the frontier constraint that will shape the next round of decisions — the shift from GPU compute to memory bandwidth as inference scales — is barely on the radar, with roughly one in five enterprises either unaware of it or yet to address it. Methodology VentureBeat fielded this survey as part of its ongoing Pulse Research series, this survey focused on enterprise AI infrastructure, compute, and inference economics. Responses are filtered to organizations with more than 100 employees (n=107; the survey’s smallest size band, 1–100 employees, is excluded), drawn from a single Q2 2026 (June) wave. Because this is one wave rather than a pooled multi-month sample, the report reads cross-sectionally and does not infer month-over-month trends. Several questions were multiple-select, so those shares can sum to more than 100%. By organization size the sample concentrates in the mid-market: 101–250 employees (36%) and 251–1,000 (27%) lead, with 1,001–5,000 (22%), 5,001–10,000 (8%), and 10,001+ (7%) above them. By role it spans managers (38%), individual contributors (28%), VPs and directors (19%), and the C-suite (13%); on purchasing authority it is buyer-credible, with 45% final decision-makers and another 30% recommenders or influencers for AI solutions. Technology/Software is the largest industry at 26%, followed by Healthcare/Life Sciences (15%), Financial Services (13%), and Retail/E-commerce (12%). At 107 respondents the sample is large enough to read directionally but should be treated as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It also skews toward the mid-market and toward earlier-stage adopters, so it is best read as the view from organizations actively building out AI infrastructure rather than from the largest hyperscale operators. Finding 1: Ambition outpaces production Only one in five run AI in production at scale We asked where organizations sit in their AI deployment journey. Most are still building toward production rather than operating at scale. The maturity curve is front-loaded. Three-quarters of enterprises (76%) are either experimenting or running only some workloads in production, and just 21% describe AI in production at scale. This matters for everything that follows: the infrastructure decisions in this report are being made largely by organizations still early in deployment, whose compute footprint — and whose costs — are about to grow. The evaluation and switching intentions in Findings 3 and 4 are the leading edge of that build-out, not the settled preferences of operators who have already found what works. Finding 2: Enterprises run on hyperscalers and model APIs The specialized GPU clouds barely register — today We asked which providers and platforms enterprises currently use to run their AI. The answer is a familiar one: the incumbents. The current stack is hyperscaler-and-API. Google Cloud leads at 48%, and the general-purpose clouds (Google, Microsoft, AWS, Oracle) together with the major model APIs (Gemini, OpenAI, Anthropic) account for essentially all current deployment. The specialized “neocloud” GPU providers that dominate AI-infrastructure headlines — CoreWeave, Lambda, Crusoe, Nebius and peers — register at or near zero among these enterprises today. Only 6% run their own on-prem GPU clusters and 4% a custom open-source stack. Enterprises are, for now, running AI on the providers they already buy from — which makes the evaluation intentions in Finding 3 all the more striking. (A note on reading these shares. As described in the methodology section, this sample is self-selected and skews mid-market, and this question counted every provider a respondent uses — an average of 2.1 selections each — so the figures measure presence in the stack rather than spending or primary status. A sample built this way will show a different provider mix than a spend-weighted census of the broader market; Google's strength here, for example, is consistent with its long-standing position among smaller enterprises building on AI. Read these shares as a portrait of what this AI-active cohort runs today, and treat gaps between these figures and industry-wide market share estimates as a property of the sample rather than a contradiction of either.) Finding 3: The next dollar goes to infrastructure they don’t yet run AI-specialized clouds top the evaluations list We asked where enterprises planned to evaluate AI infrastructure over the next 12 months. Their answers point away from the stack they run today. Here is the report’s sharpest tension. The single most-cited planned evaluation area — AI-specialized clouds, at 45% — is the very category almost none of these enterprises use today (Finding 2). Nearly a third (32%) intend to evaluate non-Nvidia accelerators, and 28% in next-generation Nvidia silicon; even decentralized compute networks (16%) and sovereign compute (11%) draw meaningful interest. Read against current usage, this is not incremental — it is the leading edge of a re-platforming. The direction-of-travel question tells the same story: every infrastructure approach is net-expanding, but specialized AI clouds carry the highest net momentum (+24), edging out even the hyperscalers (+22). Enterprises are preparing to move a meaningful share of AI compute off the general-purpose cloud. This continues a trend we saw in our April-May survey wave. Back then, usage of the AI-specialized clouds was equally marginal — CoreWeave at 3%, Lambda at 4%, Crusoe at 2% of enterprises. When we asked enterprises what change they planned in their AI infrastructure strategy over the next twelve months, the most-cited answer was moving workloads to specialized AI clouds, at 33%. Asked in April-May which emerging compute option they were most likely to evaluate AI-specialized clouds again drew the most responses. Two waves, two differently worded questions, one consistent picture: the type of cloud enterprises are most eager to assess is the type they have barely begun to use. Finding 4: A switching wave is building Six in 10 plan to change providers within a year — many within a quarter We asked whether and when enterprises plan to switch or add an infrastructure provider. Very few intend to stand still. For a category as foundational as compute, this is a remarkable amount of intended movement. Only 36% have no plans to change, meaning a clear majority (64%) intend to switch or add a provider within twelve months — and 38% within the next quarter alone. Where that interest points is telling: the providers drawing the most switching consideration are again the incumbents — Microsoft Azure and Google Cloud (33% each), OpenAI (30%), and Gemini (22%) — which suggests much of the near-term movement is reshuffling among the majors and consolidating spend rather than defecting to new entrants. The neocloud interest in Finding 3 is a 12-month evaluation thesis; the switching in the next quarter is mostly incumbents trading share. (Method note: Respondents who selected both "no plans to change" and a specific switching window are counted as switchers, on the logic that naming a timeframe is the more specific answer; three respondents were reclassified under this rule.) Finding 5: Nobody buys on token price Integration and total cost of ownership decide — not sticker price We asked what matters most when enterprises select an AI infrastructure provider. Headline price finished last. Enterprises do not buy AI infrastructure on pricing, which is the place vendors compete on hardest. Integration with the existing stack (41%) and total cost of ownership (35%) dominate, while the headline metric — cost per million tokens — is the deciding factor for just 8%, dead last. The pattern is coherent: buyers are optimizing for how a provider fits and what it truly costs to operate, not for the advertised unit rate. It also foreshadows Finding 7 — enterprises say TCO matters most, yet most cannot yet measure it rigorously. The stated priority and the measured capability are out of step. Finding 6: Expensive GPUs, idle most of the time 83% report GPU utilization of 50% or less We asked what share of their GPU capacity enterprises actually utilize. The answer is a well-known but rarely quantified inefficiency. Disclosure: Band percentages count every selection against all 107 qualified respondents; 14 respondents selected more than one band, so bands overlap. At the respondent level, 83 of the 100 GPU-operating enterprises reported utilization at or below 50% The compute already in place runs cold. Adding the bands at or below half capacity, 83% of enterprises that operate GPUs report utilization of 50% or less, and nearly half (49%) run at 25% or below. Only 12% clear the 50% mark, and a further 8% do not measure utilization at all. Idle accelerators are expensive accelerators, and this is the clearest single measure of the compute gap: enterprises are planning to buy more GPUs and specialized compute (Finding 3) while the capacity they already own sits substantially unused. The efficiency headroom in the current fleet is large — and largely unmeasured. Finding 7: Spending fast, measuring slowly Fewer than half rigorously track what their compute costs We asked whether enterprises can quantify the cost and return of their AI infrastructure spend, and how satisfied they are with what they run. Confidence in the ledger lags the spending. Measurement trails money. Fewer than half of enterprises (44%) rigorously track the cost and return of their AI compute; the majority track only partially (39%), cannot quantify it yet (20%), or have not prioritized it (6%). That gap is consequential given Finding 5, where total cost of ownership was the second-ranked buying criterion — enterprises are choosing providers on an economic basis they mostly cannot yet measure. Satisfaction with current infrastructure is moderately positive but not enthusiastic: on a five-point scale, overall satisfaction averages 4.0, with ease of implementation (3.8) and value for money (3.9) trailing slightly — the softness landing, tellingly, on cost. Enterprises are spending quickly and accounting slowly. Finding 8: The next bottleneck few are watching As inference shifts from compute to memory, the field scatters Finally, we asked how enterprises would address the emerging constraint in large-scale inference — the shift from GPU compute to memory, specifically KV-cache capacity. The responses reveal a frontier that is not yet a priority. The memory frontier is real but barely governed. Asked which approach they would rely on as the binding constraint in inference shifts from compute to memory bandwidth, enterprises scatter: Dell leads at 31%, Nvidia follows at 16%, and the rest fragments across storage vendors, open-source tooling, and model-level efficiency techniques. Most telling is that roughly one in five (18%) either do not recognize the constraint or have not begun to address it. For a shift that will reshape inference cost and architecture, this is an early and unsettled market — and, consistent with the measurement gap in Finding 7, one where many enterprises simply do not yet have a view. It is the next chapter of the compute gap, arriving before most have closed the current one. The bottom line: A compute gap that faster spending will widen, not close Organizations with more than 100 employees are investing in AI infrastructure faster than they can measure it. Most are still early in deployment, yet their spending intentions point past their current stack — toward specialized clouds and alternative accelerators almost none of them run today — and a clear majority intend to change providers within the year. They buy on integration and total cost of ownership rather than headline price, which is rational; the difficulty is that most cannot yet see those economics clearly. The visibility gap is concrete. The GPUs enterprises already own run at half utilization or less for the overwhelming majority, and fewer than half can rigorously track what their compute costs or returns. Satisfaction is decent but unenthusiastic, softest on value for money — the dimension hardest to judge without measurement. And the next constraint, the shift from compute to memory in large-scale inference, is arriving while most enterprises are still unaware of it. At 107 respondents in a single Q2 wave this is a directional read, skewed toward the mid-market and earlier-stage adopters — but the direction is consistent: the appetite to spend is running well ahead of the instrumentation to spend well. The compute gap is not a capacity problem that more hardware will solve on its own; it is, first, a problem of seeing what the hardware already costs. The open question for later waves is whether enterprises build that visibility before the re-platforming arrives — or buy the next layer of infrastructure as blind to its economics as the last. Based on survey responses from 107 qualified enterprise respondents (100+ employees), drawn from a single Q2 2026 (June) wave. Because this is one wave rather than a pooled multi-month sample, the results read cross-sectionally rather than as a month-over-month trend, and at 107 respondents this is a directional signal rather than a precise measurement — the sample is self-selected, skews mid-market, and leans toward earlier-stage adopters rather than the largest hyperscale operators. Respondents include managers, individual contributors, VPs/directors, and the C-suite, with buyer-credible purchasing authority, across Technology/Software, Healthcare/Life Sciences, Financial Services, Retail/E-commerce, and other industries.

China's Moonshot AI stole from Anthropic, Trump tech adviser says - BBC
"artificial intelligence" - Google News

China's Moonshot AI stole from Anthropic, Trump tech adviser says - BBC

China's Moonshot AI stole from Anthropic, Trump tech adviser says  BBC

EXCLUSIVE: DOGE alumni launch military cyber startup with $1.4 billion valuation - Reuters
"artificial intelligence" - Google News

EXCLUSIVE: DOGE alumni launch military cyber startup with $1.4 billion valuation - Reuters

EXCLUSIVE: DOGE alumni launch military cyber startup with $1.4 billion valuation  Reuters

OpenAI’s AI spending spree has ballooned to $750B
AI News & Artificial Intelligence | TechCrunch

OpenAI’s AI spending spree has ballooned to $750B

OpenAI will spend the equivalent of Sweden's GDP on infrastructure through 2030.

Web scraping: A comprehensive guide
The Zapier Blog

Web scraping: A comprehensive guide

There are two ways to catch a price drop on that obnoxiously priced all-terrain dog stroller you've been eyeing (but won't admit out loud to the general public—which, smart). You could check the product page every morning and hope today's the day for good boy Professor Waffles. Or you could let a price tracker like camelcamelcamel watch the listing for you and send an alert the moment it dips below a set price. That second option is web scraping at work: an automated tool visits the page, reads

Safety and alignment in an era of long-horizon models
OpenAI News

Safety and alignment in an era of long-horizon models

OpenAI shares lessons from deploying long-running AI models, highlighting new safety risks, observed failures, and improved safeguards through iterative deployment.

Zapier for enterprise orchestration: Scaling automation on a trusted platform
The Zapier Blog

Zapier for enterprise orchestration: Scaling automation on a trusted platform

Zapier is easy to use—and sometimes ease of use gets conflated with simplicity. But at Zapier, we know that being easy to use and being enterprise-ready aren't mutually exclusive. Any enterprise tool should prioritize ease of use. If you want your entire organization to adopt software, there can't be barriers to entry. Zapier helps your entire company operate more efficiently and achieve mission-critical goals at scale. And it goes beyond workflows: Zapier is an AI orchestration platform where y

Introducing the ChatGPT for small business program
OpenAI News

Introducing the ChatGPT for small business program

OpenAI launches the ChatGPT for Small Businesses program, helping entrepreneurs build AI skills, automate work, and grow with ChatGPT Work.

David Vélez and Robin Vince join the boards of the OpenAI Foundation and OpenAI Group PBC
OpenAI News

David Vélez and Robin Vince join the boards of the OpenAI Foundation and OpenAI Group PBC

David Vélez and Robin Vince join the boards of the OpenAI Foundation and OpenAI Group PBC, bringing global leadership in finance, technology, and governance.

10 top women in AI in 2026
DailyAI

10 top women in AI in 2026

AI is changing our world, but the stories of who build it often get lost in the noise. Behind the headlines and hype, a group of women are solving AI’s fundamental challenges – despite working in an industry persisently impacted by gender inequality. Women make up just 22% of AI professionals worldwide and only 12% of AI researchers. In academic publishing, female researchers account for just 29% of first authors on AI papers, a number that hasn’t increased since the mid-2000s.  This is a story about ten leaders who have influenced AI despite the odds being stacked against them.  Their The post 10 top women in AI in 2026 appeared first on DailyAI.

How to manage AI investments in the agentic era
OpenAI News

How to manage AI investments in the agentic era

Learn how enterprises can manage AI investments in the agentic era by measuring useful work per dollar, improving efficiency, and scaling high-value workflows.

OpenAI Says Its A.I. Models Hacked Into Hugging Face, a Digital Library - The New York Times
"artificial intelligence" - Google News

OpenAI Says Its A.I. Models Hacked Into Hugging Face, a Digital Library - The New York Times

OpenAI Says Its A.I. Models Hacked Into Hugging Face, a Digital Library  The New York Times OpenAI says its technology, on its own, carried out "unprecedented" hack of another AI company  CBS News OpenAI says its AI went rogue and launched 'unprecedented' cyber-attack  BBC