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VentureBeat

Anthropic says it hit a $30 billion revenue run rate after 'crazy' 80x growth OpenAI voice models get GPT-5-class reasoning AI agent identity: how to govern agentic AI in 6 stages Anthropic wants to own your agent's memory, evals, and orchestration — and that should make enterprises nervous Enterprise GPU utilization: why 95% of AI infrastructure spend is wasted Governance, not gatekeeping: How SAP brings enterprise‑grade safety to AI connectivity Anthropic introduces "dreaming," a system that lets AI agents learn from their own mistakes RL orchestration: how a 7B model routes tasks across GPT-5, Claude, and Gemini Meet ZAYA1-8B, a super efficient open reasoning model trained on AMD Instinct MI300 GPUs Anthropic Skill scanners passed every check. The malicious code rode in on a test file. Why AI breaks without context — and how to fix it Market research is too slow for the AI era, so Brox built 60,000 identical 'digital twins' of real people you can survey instantly, repeatedly The app store for robots has arrived: Hugging Face launches open-source Reachy Mini App Store with 200+ apps Scaling AI into production is forcing a rethink of enterprise infrastructure Miami startup Subquadratic claims 1,000x AI efficiency gain with SubQ model; researchers demand independent proof. GPT-5.5 Instant shows you what it remembered — just not all of it One command turns any open-source repo into an AI agent backdoor. OpenClaw proved no supply-chain scanner has a detection category for it AI agents are missing all the discussions your team is having. SageOX has an answer: agentic context infrastructure OpenAI turns its sold-out GPT-5.5 party into a monthlong Codex giveaway for 8,000 developers Inside AMEX’s agentic commerce stack: How intent contracts and single-use tokens enforce AI transactions Microsoft takes Agent 365 out of preview as shadow AI becomes an enterprise threat The RAG era is ending for agentic AI — a new compilation-stage knowledge layer is what comes next Salesforce Agentforce Operations fixes workflows breaking enterprise AI MCP command execution flaw: what security teams need to know The scaffolding era is over. LlamaIndex says context is the new moat xAI launches Grok 4.3 at an aggressively low price and a new, fast, powerful voice cloning suite Hidden IT problems are quietly creating risk, shadow IT, and lost productivity Alibaba's HDPO cuts AI agent tool overuse from 98% to 2% One tool call to rule them all? New open source Python tool Runpod Flash eliminates containers for faster AI dev Why OpenAI's 'goblin' problem matters — and how you can release the goblins on your own AI coding agents breached: attackers targeted credentials, not models | VentureBeat Writer launches AI agents that can act without prompts, taking on Amazon, Microsoft and Salesforce Netomi raises $110 million as Accenture and Adobe bet on AI for customer service Cheaper tokens, bigger bills: The new math of AI infrastructure Amazon’s OpenAI gambit signals a new phase in the cloud wars — one where exclusivity no longer applies Enterprise RAG rebuild: hybrid retrieval adoption tripled in Q1 2026 IBM launches Bob with multi-model routing and human checkpoints to turn AI coding into a secure production system AWS Quick's knowledge graph creates an orchestration blind spot Why enterprise GPU utilization is stuck at 5% — and why the fix makes it worse Definity embeds agents inside Spark pipelines to catch failures before they reach agentic AI systems How to build custom reasoning agents with a fraction of the compute American AI startup Poolside launches free, high-performing open model Laguna XS.2 for local agentic coding Mistral AI launches Workflows, a Temporal-powered orchestration engine already running millions of daily executions Microsoft and OpenAI gut their exclusive deal, freeing OpenAI to sell on AWS and Google Cloud Open source Xiaomi MiMo-V2.5 and V2.5-Pro are among the most efficient (and affordable) at agentic 'claw' tasks AI framework autonomously outperforms human-designed R&D baselines Why supply chains are the proving ground for automation‑led iPaaS RAG precision tuning can quietly cut retrieval accuracy by 40%, putting agentic pipelines at risk Enterprises are obsessing over model accuracy while ignoring the infrastructure layer where AI systems actually break. Monitoring LLM behavior: Drift, retries, and refusal patterns CVSS vulnerability triage: 5 failures, 5 fixes DeepSeek-V4 arrives with near state-of-the-art intelligence at fraction of the cost of Opus 4.7, GPT-5.5 85% of enterprises are running AI agents. Only 5% trust them enough to ship. AI synthetic audiences are already here and poised to upend the consulting industry Mystery solved: Anthropic reveals changes to Claude's harnesses and operating instructions likely caused degradation OpenAI's GPT-5.5 is here, and it's no potato: narrowly beats Anthropic's Claude Mythos Preview on Terminal-Bench 2.0 New startup BAND debuts agentic mesh with deterministic routing to govern multiple enterprise AI agents across model providers, channels OpenAI unveils Workspace Agents, a successor to custom GPTs for enterprises that can plug directly into Slack, Salesforce and more Google and AWS split the AI agent stack between control and execution Are you paying an AI ‘swarm tax’? Why single agents often beat complex systems OpenAI launches Privacy Filter, an open source, on-device data sanitization model that removes personal information from enterprise datasets Google doesn't pay the Nvidia tax. Its new TPUs explain why. Salesforce’s Agentforce Vibes 2.0 targets a hidden failure: context overload in AI agents Google’s Gemini can now run on a single air-gapped server — and vanish when you pull the plug The modern data stack was built for humans asking questions. Google just rebuilt its for agents taking action. Google’s new Deep Research and Deep Research Max agents can search the web and your private data Vercel breach exposes the OAuth gap most security teams cannot detect, scope or contain The AI governance mirage: Why 72% of enterprises don’t have the control and security they think they do OpenAI's ChatGPT Images 2.0 is here and it does multilingual text, full infographics, slides, maps, even manga — seemingly flawlessly Kimi K2.6 runs agents for days — and exposes the limits of enterprise orchestration What AI model should you use for revenue intelligence? Von says all the big ones, and it will automate mixing and matching for you Three AI coding agents leaked secrets through a single prompt injection. One vendor's system card predicted it Train-to-Test scaling explained: How to optimize your end-to-end AI compute budget for inference AI agent security maturity audit: enterprises funded stage one, stage-three threats arrived anyway Anthropic just launched Claude Design, an AI tool that turns prompts into prototypes and challenges Figma Should my enterprise AI agent do that? NanoClaw and Vercel launch easier agentic policy setting, approval dialogs for messaging apps Salesforce launches Headless 360 to turn its entire platform into infrastructure for AI agents Are we getting what we paid for? How to turn AI momentum into measurable value OpenAI debuts GPT-Rosalind, a new limited access model for life sciences, and broader Codex plugin on Github OpenAI drastically updates Codex desktop app to use all other apps on your computer, generate images, preview webpages Anthropic releases Claude Opus 4.7, narrowly retaking lead for most powerful generally available LLM AI lowered the cost of building software. Enterprise governance hasn’t caught up Microsoft patched a Copilot Studio prompt injection. The data exfiltrated anyway Frontier models are failing one in three production attempts — and getting harder to audit Meta researchers introduce 'hyperagents' to unlock self-improving AI for non-coding tasks We tested Anthropic’s redesigned Claude Code desktop app and 'Routines' -- here's what enterprises should know AI's next bottleneck isn't the models — it's whether agents can think together Adobe’s new Firefly AI Assistant wants to run Photoshop, Premiere, Illustrator and more from one prompt Traza raises $2.1 million led by Base10 to automate procurement workflows with AI Agentic coding at enterprise scale demands spec-driven development Designing the agentic AI enterprise for measurable performance Five signs data drift is already undermining your security models Your developers are already running AI locally: Why on-device inference is the CISO’s new blind spot AI agent credentials live in the same box as untrusted code. Two new architectures show where the blast radius actually stops. Intuit compressed months of tax code implementation into hours — and built a workflow any regulated-industry team can adapt OpenAI introduces ChatGPT Pro $100 tier with 5X usage limits for Codex compared to Plus Mythos autonomously exploited vulnerabilities that survived 27 years of human review. Security teams need a new detection playbook Claude, OpenClaw and the new reality: AI agents are here — and so is the chaos Goodbye, Llama? Meta launches new proprietary AI model Muse Spark — first since Superintelligence Labs' formation LLM-referred traffic converts at 30-40% — and most enterprises aren't optimizing for it
85% of IT teams claim every AI agent is under control
Louis Columbus · 2026-06-16 · via VentureBeat

Organizational leaders are nearly twice as likely to hide their AI use compared to all other employees, at 42% versus 23%, according to new Ivanti research surveying 3,900 employees across six countries. Among leaders who conceal that usage, 52% say they do it for a "secret advantage." The same research found 85% of IT professionals claim a named owner exists for every AI agent. Only 42% say ownership is actually clear — a 43-point gap that no governance framework was designed to close.

Sam Evans, CISO of Clearwater Analytics, stood before his board and laid out the risk to the $8.8 trillion in assets his firm's platform supports. "The worst possible thing would be one of our employees taking customer data and putting it into an AI engine that we don't manage," Evans told VentureBeat. He brought a solution, not just a problem. Many CISOs VentureBeat interviewed did not.

Menlo Security CEO Bill Robbins relayed a conversation with a Top 3 U.S. bank CISO who called shadow AI discovery "a bit of a fool's errand": AI is embedded in every application and browser employees touch. The bank governs from containment, not discovery.

The scale justifies that posture. "We see 50 new AI apps a day, and we've already cataloged over 12,000," Prompt Security CEO Itamar Golan told VentureBeat. "Around 40% of these default to training on any data you feed them, meaning your intellectual property can become part of their models." CrowdStrike has detected 1,800 AI applications operating across 160 million endpoint instances. Those are vendor-reported numbers from proprietary telemetry. No independent party can verify them. The directional signal matters more than the exact count.

CrowdStrike CTO Elia Zaitsev described what makes the surface so hard to govern. "It looks indistinguishable if an agent runs your web browser versus if you run your browser," Zaitsev told VentureBeat at RSAC 2026. "Observing actual kinetic actions is a structured, solvable problem. Intent is not." The shadow AI surface is no longer a list security teams can maintain. It is an environment they have to assume.

The Ivanti survey was administered independently by Ravn Research and MSI Advanced Customer Insights across 1,500 IT professionals. Among companies with AI policies, just 24% of employees say those policies are followed "very consistently" in day-to-day work.

Kayne McGladrey, IEEE senior member, told VentureBeat why that governance gap persists. "Anything that seems to have a cybersecurity flavor is generally put into the cybersecurity risk category, which is a complete fiction. They should be focused on business risks, because if it doesn't affect the business, like a financial loss, then nobody's going to pay attention to it, and they will not budget it appropriately, nor will they adequately put in controls to prevent it," McGladrey told VentureBeat previously.

Brokerage partners at major consulting firms shared over Signal that they build shadow AI applications in Google Colab and store them in S3 buckets to compress a week of financial analysis into an hour. The approval process takes too long, so they route around it.

Governance at deploy time, failure at runtime

Reviews check functional requirements when a model ships, but they never check model provenance, behavioral drift, or whether the agent expanded its own permissions after launch.

CrowdStrike CEO George Kurtz disclosed at RSA Conference 2026 that a Fortune 50 CEO's AI agent rewrote the company's security policy to expand its own autonomy. The company caught it by accident. Every credential check had passed. "In the agentic era, defending against AI-accelerated adversaries and securing AI systems themselves require operating at machine speed," Kurtz said. Quarterly governance reviews do not operate at machine speed.

Mike Riemer, Field CISO at Ivanti, built that lesson into his own team's AI agent development. "It's great at what I intended it for, but it's also great at what I didn't intend it for, and what I didn't intend it for is dangerous," Riemer told VentureBeat.

Hallucination data compounds the problem. Sixty-eight percent of IT professionals have personally witnessed AI generate hallucinations with potential operational impact, according to Ivanti. More than half caught the errors before damage, but 16% did not. Yet among the most advanced users of AI, 49% fully trust AI-generated outputs that influence IT decisions.

Riemer described the pattern in an exclusive interview with VentureBeat. "There are people that are just accepting what's been given to them without any full understanding of what it is doing, which we've found in the tech industry for decades," Riemer said. "They don't question how it's doing it. They just start gauging it by its outcome."

Qualtrics CSO Assaf Keren identified the core tension in an exclusive interview with VentureBeat. Organizations are introducing "non-deterministic decisioning into environments built for deterministic." Keren cited internal Qualtrics data showing that 22% of SOC triage is now AI-driven. No codified threshold separates what an agent can auto-execute from what requires a human in the loop.

The 18-month window

The window for fixing this is closing. IT organizations expect AI to automate 46% of their operations within 18 months, according to Ivanti. U.S. companies project 52%. Governance is already the most commonly cited barrier to faster deployment, ahead of skills, technology, and data challenges.

The maturity divide makes the governance gap more dangerous. IT professionals at AI-mature organizations save six hours per week, double the three hours saved at the least mature level. Nearly 9 in 10 IT professionals at scaled organizations say AI frequently helps detect or resolve issues before employees are affected. At early experimentation organizations, that number drops to four in ten. Sixty-nine percent of scaled organizations report fully embedded governance, compared to 15% at early experimentation.

42% of IT leaders hid their own AI use. 52% said it gave them a secret advantage. 6 questions that catch what governance missed

Source: Ivanti, Scaling AI in IT Operations: The Path to Maturity in 2026. Responses from IT professionals (n=1,500). Responses rounded to the nearest percent.

Cisco President Jeetu Patel walked through a hypothetical scenario in an interview at RSAC 2026: an agent that charges $40,000, invites competitors to a Slack channel, and publishes home addresses. "The apology is not a guardrail," Patel told VentureBeat.

Cato Networks VP of Threat Intelligence Etay Maor framed the accountability problem in a separate RSAC interview. "They're closer to humans. Why are we not doing background checks on agents?"

"AI is compressing the time between intent and execution while turning enterprise AI systems into targets," CrowdStrike VP of Intelligence Operations Adam Meyers told VentureBeat.

"Proceed on one action does not mean proceed on the next," Cisco SVP of AI Software and Platform DJ Sampath said in a separate interview.

McGladrey described the root cause. Organizations default to cloning human user profiles for agents, and permission sprawl starts on day one. "It uses far more permissions than it should have, more than a human would, because of the speed of scale and intent," he said.

Riemer's team built governance into Ivanti's own development process. "We have AI check on top of AI to make sure that it is fixed. Two different models, two different manufacturers," Riemer said. "If one AI believes the other AI fixed it appropriately, then it passes it off to a human being."

Riemer put the vendor question in terms every CISO can use at the negotiating table. "If that vendor doesn't have a way to show you what they've done from a development perspective in order to improve their development processes, you really need to question why you're working with that vendor," he said.

The six questions below target governance dimensions where enforcement collapses at runtime. CISOs can use them during Q3 vendor renewals to separate vendors shipping runtime enforcement from vendors shipping documentation.

Six governance questions for Q3 renewals

Governance dimension

What the data proved

Why governance misses it

Q3 renewal question

Proof artifact to demand

Executive shadow AI

Leaders hide AI at 42% vs. 23% all employees. 52% hide for "secret advantage." Regulated industries have the highest unsanctioned rates.

Governance assumes policy writers follow policy. Leaders sit above the controls they wrote.

Can your DLP, browser, SSE, and endpoint telemetry detect AI data movement at the executive layer with the same coverage as all other users?

Executive-layer DLP, browser, SSE, and endpoint telemetry logs showing identical coverage to all other users.

Named agent ownership

85% claim a named owner. Only 42% say ownership is clear. 43-point gap.

Owner on a spreadsheet. Agent at runtime. Nobody tested whether the owner can kill the agent under load.

Can you name the owner for every AI agent? Can that owner revoke access in 60 seconds?

Live demo of 60-second agent access revocation under production load.

Pre-deployment review

65% have pre-deployment risk review. Separately, only 24% say any AI policy is followed "very consistently." Review exists. Enforcement does not.

Review checks functional requirements at deploy. Never checks model provenance or behavioral drift at runtime.

Does your review cover model provenance? Is it enforced or advisory?

Model provenance certificate with enforcement log showing blocked deployments.

Policy enforcement

58% have acceptable-use policies. 24% followed "very consistently." Documented. Not practiced.

Agent pursued its goal past every boundary. Goal-seeking does not stop at a document the model never reads.

Are policies enforced by server-side gates or by agent compliance? What percentage of actions are gated?

Server-side gate audit trail with percentage of agent actions gated vs. ungated.

Trust thresholds

68% have seen hallucinations with operational impact. 49% of advanced users fully trust outputs.

No codified threshold separates auto-execute from human-review.

Which agent actions auto-execute versus require human review? Is that enforced in policy or in the platform?

Documented threshold matrix classifying every agent action as auto-execute or human-review.

Per-action authorization

Governance is the #1 barrier at 27%. Skills 20%. Tech 17%. Data 14%.

Oversight reviews quarterly. Agents act per-second.

Is per-action authorization enforced at runtime or only at deploy-time review? Can agents accumulate permissions without re-authorization?

Runtime authorization log showing per-action gate events and permission re-authorization timestamps.

Source data from Ivanti, Scaling AI in IT Operations: The Path to Maturity in 2026 (n=1,500 IT professionals, 3,900 total employees, six countries, February–March 2026). Exclusive CISO sourcing by VentureBeat.

Evans put structure around the Clearwater board conversation. The bank CISO that Robbins described assumed AI is everywhere and governed from containment instead of discovery. Governance that tries to catalog every shadow AI tool will fail because the surface grows faster than any inventory.

At scaled, business-critical organizations, 54% of IT professionals say AI makes their work both faster and better, according to Ivanti. At early experimentation organizations, 24% say the same. At scaled organizations, accountability lives in the platform. At early ones, it lives in a document the agent never reads.

The six questions above give every CISO a way to test whether their governance actually works where it matters. At runtime, under load, and before the next renewal check clears.