VentureBeat Pulse Research
VentureBeat Pulse Research on Beyond Market Intelligence: a running collection of 8 stories we have gathered and hand-picked because they are worth your time. Every post here touches on venturebeat pulse research in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around venturebeat pulse research, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Four of five enterprises that secured AI agent identities still can't contain one that goes rogue
Recent VentureBeat research reveals a concerning gap in enterprise AI agent security. While 53% have already experienced an agentic security incident, and a majority (92%) rely on provider-native controls, only a fraction isolate their highest-risk agents. Visa's internal testing with Anthropic's Mythos exposed vulnerabilities, highlighting the need for proactive containment. This underscores a critical point: simply assigning identities isn't enough to prevent rogue agents – a lesson echoed by incidents at Meta and CrowdStrike.
Agentic security: Enterprises enforce agent permissions two-thirds of the time — and isolate high-risk agents less than one in five
Across 116 enterprises, AI agents are now in production, and so too are the associated security incidents—with over half reporting a confirmed event or near-miss. While two-thirds enforce scoped permissions and 56% monitor activity, a concerning gap exists: fewer than one in five isolate high-risk agents. This containment deficit, coupled with persistent credential sharing, highlights a critical vulnerability as AI-armed attackers are perceived as equally or more capable than current defenses.
The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs
Enterprises are rapidly accelerating investment in AI infrastructure, yet a significant "compute gap" exists – heavy spending outpacing the ability to truly understand and control its economics. New VentureBeat Pulse Research, surveying 107 organizations, reveals that while only 21% run AI at scale, nearly half intend to evaluate specialized AI clouds within the year, often lacking clear visibility into GPU utilization (83% below 50%) and compute costs.
The agent evaluation gap: Enterprise AI organizations have a reality-alignment problem, not a coverage problem — and most are shipping to production anyway
Enterprise AI organizations face a critical reality-alignment problem: an “evaluation gap” where increasing agent autonomy outpaces trust in the evaluations meant to govern it. A recent VentureBeat Pulse Research survey of 157 enterprises reveals that half have already deployed an agent that passed internal evaluations but then failed a customer. Despite this, two-thirds are moving toward fully automated deployments—highlighting a concerning disconnect. This research underscores the urgent need for evaluations that accurately reflect real-world outcomes, not just passing scores.
The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials
More than half of enterprises (54%) have already experienced a confirmed agent security incident or a near-miss, revealing a concerning gap between AI agent autonomy and the controls designed to contain them. Across 107 organizations, agents are gaining access to sensitive systems while security lags, with only a third providing each agent a unique identity and limited isolation of high-risk agents.
The agent security gap: 54% of enterprises have already had an AI agent incident, and most still let agents share credentials
More than half of enterprises (54%) have already experienced an AI agent security incident or near-miss, highlighting a critical gap between agent autonomy and effective controls. Across 107 organizations, agents are gaining access to sensitive systems while security measures lag, with only a third providing each agent a unique, scoped identity. This VentureBeat Pulse Research reveals that the security stack predominantly relies on borrowed solutions from model providers, leaving a significant vulnerability as AI-enabled attacks evolve.
The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs
Enterprises are accelerating AI infrastructure spending, yet visibility into its economics lags significantly—a phenomenon we've termed the "compute gap." Across 107 organizations, intentions to evaluate specialized AI clouds are surging, even as existing GPUs sit at half utilization or less, and fewer than half rigorously track compute costs. This reveals a disconnect: organizations are buying more infrastructure faster than they can account for what they already own, signaling a shift away from traditional hyperscalers.
Agentic orchestration: Enterprise AI organizations have a deployment problem, not a platform problem — and most are calling chatbots agents
Enterprise AI organizations face a deployment challenge, not a platform one—and many are framing chatbots as agents. VentureBeat Pulse Research, surveying 101 enterprises, reveals Anthropic’s Claude leads agent orchestration (40%), driven by model gravity and reliable multi-step execution. However, a significant gap exists: 71% report that less than a quarter of their agents are truly orchestrated workflows, highlighting the need for robust tooling and fiscal control. Enterprises are prioritizing hybrid control planes to avoid vendor lock-in, signaling a shift towards operational consolidation.