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Enterprise AI's real risk isn't autonomous agents. It's the complexity between them.
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Enterprise AI's real risk isn't autonomous agents. It's the complexity between them.

Presented by Gravitee Agent complexity is the insidious shadow lurking inside enterprises right now that needs a light shone on it. That’s because enterprises don't deploy a single agent and watch it run, they deploy fleets, each one calling APIs, calling other agents, reaching into applications that were never built with a machine decision-maker in mind. That's the failure mode that should keep you up at night: a windy, complicated system nobody can see clearly enough to govern. But why do things get so opaque so quickly? Add a second agent to a system, and you've added one connection. Add

VentureBeat AI
When agents act on their own, governance has to live in the data layer
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When agents act on their own, governance has to live in the data layer

Presented by EDB As enterprises give AI agents more autonomy — the ability to plan, decide, and act across systems without a human approving each step — a hard question moves to the center of every architecture review: When an agent tries to complete an action that it was never authorized to do, what actually stops it? These are your agents, running on your models, touching your data in your infrastructure — and the responsibility for what they do sits with you. That responsibility can’t be met in hindsight or with a set of abstract policies that live on paper but not in practice. Agents nee

VentureBeat AI
Orchestration is the new challenge for CX in the age of AI agents
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Orchestration is the new challenge for CX in the age of AI agents

Presented by Tata Communications Enterprises are deploying AI agents, voice AI, and automation across messaging, voice, and digital channels faster than the architecture meant to support it. Most of that deployment has involved attaching conversational AI to legacy systems never built for it, says Gaurav Anand, global head of the Customer Interaction Suite at Tata Communications. "In the rush to deploy AI, organizations have largely bolted conversational AI onto legacy systems," Anand says. "As a result, while many enterprises have adopted digital tools, very few have platforms that are trul

VentureBeat AI
VentureBeat names Rob Strechay as its first Lead Analyst, expanding its enterprise AI research push
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VentureBeat names Rob Strechay as its first Lead Analyst, expanding its enterprise AI research push

Rob Strechay, until recently managing director and principal analyst at theCUBE Research, has joined VentureBeat as our first Lead Analyst and a founding analyst of VentureBeat Research. His arrival is the next step in a deliberate move at VentureBeat toward deeper specialization: analysis built for the technical decision-makers — the directors, VPs, CIOs, and CTOs — who are evaluating, buying, and deploying enterprise AI. The enterprise AI stack is being rewritten in real time, and the decision-makers I talk with are starved for objective, defendable data. Rob Strechay has the mix of technica

VentureBeat AI
The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials
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The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials

Across 107 enterprises, AI agents are being given real access to systems and data while the controls meant to contain them lag behind. More than half have already had a confirmed agent security incident or a near-miss; only about a third give every agent its own scoped identity, and most agents still share credentials; and only three in ten isolate their highest-risk agents. The security stack is overwhelmingly borrowed from the model providers and hyperscalers rather than purpose-built for agents, spending remains a thin slice of the security budget, and enterprises are evenly split on whethe

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

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The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix
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The AI context gap: Enterprise AI organizations have a trust problem, not a retrieval problem — and most are still building the fix

Across 101 enterprises, the infrastructure that feeds AI agents their business context is being built faster than it can be trusted. Retrieval-augmented generation is already the default context source, and provider-native retrieval has quietly overtaken the dedicated vector databases that define the category — yet a majority of enterprises have already watched their agents produce confident, wrong answers traced to missing or inconsistent context. A governed semantic layer is emerging as the fix, but most are still building it; the field is converging on hybrid retrieval; and even as provider

VentureBeat AI
The agent evaluation gap: Enterprise AI organizations have a reality-alignment problem, not a coverage problem — and most are shipping to production anyway
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The agent evaluation gap: Enterprise AI organizations have a reality-alignment problem, not a coverage problem — and most are shipping to production anyway

Across 157 enterprises, organizations are granting AI agents more autonomy while trusting the evaluations meant to gate that autonomy less. Half have already shipped an agent that passed their internal evaluations and then failed a customer in production; only one in twenty fully trusts automated evaluation today; and the most-cited weakness is that evaluations do not align with real-world outcomes. Yet two-thirds already allow, or are actively engineering toward, deploying agent changes to production on automated evaluation alone — with no human in the loop. The result is an evaluation gap —

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Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents
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Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents

Across 101 enterprises, agent orchestration is consolidating onto model-provider platforms — Anthropic’s Claude leads by a wide margin — chosen for the gravity of the underlying model and judged on reliable multi-step execution. But the ambition runs well ahead of the reality: most deployed “agents” are still chatbot wrappers, the control plane enterprises expect is deliberately hybrid to avoid lock-in, and real-time fiscal control over token burn remains the exception. This wave of VentureBeat Pulse Research examines enterprise agent orchestration: which platforms enterprises run on, what dri

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Google just redesigned the search box for the first time in 25 years — here’s why it matters more than you think.
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Google just redesigned the search box for the first time in 25 years — here’s why it matters more than you think.

For a quarter century, the Google search box has been one of the most recognizable interfaces in computing: a thin white rectangle, a blinking cursor, a few typed words, and a list of blue links. On Tuesday, Google will formally retire that paradigm. At its annual I/O developer conference, Google announced a sweeping redesign of the search box itself — the literal text field where billions of queries begin every day — transforming it from a simple keyword input into a dynamic, AI-driven conversation starter that can accept text, images, PDFs, videos, and even open Chrome tabs as inputs. The co

VentureBeat AI
Railway secures $100 million to challenge AWS with AI-native cloud infrastructure
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Railway secures $100 million to challenge AWS with AI-native cloud infrastructure

Railway, a San Francisco-based cloud platform that has quietly amassed two million developers without spending a dollar on marketing, announced Thursday that it raised $100 million in a Series B funding round, as surging demand for artificial intelligence applications exposes the limitations of legacy cloud infrastructure. TQ Ventures led the round, with participation from FPV Ventures, Redpoint, and Unusual Ventures. The investment values Railway as one of the most significant infrastructure startups to emerge during the AI boom, capitalizing on developer frustration with the complexity and c

VentureBeat AI
Claude Code costs up to $200 a month. Goose does the same thing for free.
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Claude Code costs up to $200 a month. Goose does the same thing for free.

The artificial intelligence coding revolution comes with a catch: it's expensive. Claude Code, Anthropic's terminal-based AI agent that can write, debug, and deploy code autonomously, has captured the imagination of software developers worldwide. But its pricing — ranging from $20 to $200 per month depending on usage — has sparked a growing rebellion among the very programmers it aims to serve. Now, a free alternative is gaining traction. Goose, an open-source AI agent developed by Block (the financial technology company formerly known as Square), offers nearly identical functionality to Claud

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Listen Labs raises $69M after viral billboard hiring stunt to scale AI customer interviews
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Listen Labs raises $69M after viral billboard hiring stunt to scale AI customer interviews

Alfred Wahlforss was running out of options. His startup, Listen Labs, needed to hire over 100 engineers, but competing against Mark Zuckerberg's $100 million offers seemed impossible. So he spent $5,000 — a fifth of his marketing budget — on a billboard in San Francisco displaying what looked like gibberish: five strings of random numbers. The numbers were actually AI tokens. Decoded, they led to a coding challenge: build an algorithm to act as a digital bouncer at Berghain, the Berlin nightclub famous for rejecting nearly everyone at the door. Within days, thousands attempted the puzzle. 430

VentureBeat AI
Salesforce rolls out new Slackbot AI agent as it battles Microsoft and Google in workplace AI
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Salesforce rolls out new Slackbot AI agent as it battles Microsoft and Google in workplace AI

Salesforce on Tuesday launched an entirely rebuilt version of Slackbot, the company's workplace assistant, transforming it from a simple notification tool into what executives describe as a fully powered AI agent capable of searching enterprise data, drafting documents, and taking action on behalf of employees. The new Slackbot, now generally available to Business+ and Enterprise+ customers, is Salesforce's most aggressive move yet to position Slack at the center of the emerging "agentic AI" movement — where software agents work alongside humans to complete complex tasks. The launch comes as S

VentureBeat AI
Anthropic launches Cowork, a Claude Desktop agent that works in your files — no coding required
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Anthropic launches Cowork, a Claude Desktop agent that works in your files — no coding required

Anthropic released Cowork on Monday, a new AI agent capability that extends the power of its wildly successful Claude Code tool to non-technical users — and according to company insiders, the team built the entire feature in approximately a week and a half, largely using Claude Code itself. The launch marks a major inflection point in the race to deliver practical AI agents to mainstream users, positioning Anthropic to compete not just with OpenAI and Google in conversational AI, but with Microsoft's Copilot in the burgeoning market for AI-powered productivity tools. "Cowork lets you complete

VentureBeat AI
Nous Research's NousCoder-14B is an open-source coding model landing right in the Claude Code moment
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Nous Research's NousCoder-14B is an open-source coding model landing right in the Claude Code moment

Nous Research, the open-source artificial intelligence startup backed by crypto venture firm Paradigm, released a new competitive programming model on Monday that it says matches or exceeds several larger proprietary systems — trained in just four days using 48 of Nvidia's latest B200 graphics processors. The model, called NousCoder-14B, is another entry in a crowded field of AI coding assistants, but arrives at a particularly charged moment: Claude Code, the agentic programming tool from rival Anthropic, has dominated social media discussion since New Year's Day, with developers posting breat

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