Two recent studies from VentureBeat's Pulse Research series, fielded in June 2026 across more than 100 large enterprises, have exposed a worrying reality: the enterprise AI investment wave is moving far faster than actual operational control. Organizations are pouring millions of dollars into compute infrastructure and agent orchestration platforms while leaving expensive hardware underutilized and inflating simple chatbots into "AI agents."
Bối cảnh & Nguyên nhân
The rush to integrate AI into business processes has triggered a wave of panic buying, where infrastructure investment decisions are made before enterprises can even define how to measure their economic return. According to VentureBeat, most organizations still run their AI on a familiar foundation of major hyperscalers and commercial model APIs. However, the fear of falling behind and the prospect of vendor lock-in are driving them to transition toward specialized AI clouds or build their own control layers, even before they are technically prepared.
Lãng phí phần cứng và lỗ hổng quản lý chi phí
One of the most shocking findings from the infrastructure survey (107 respondents) is the idling of expensive GPU accelerators. A staggering 83% of enterprises operating GPUs report actual utilization at or below 50%, with nearly half (49%) running at 25% or less. Ironically, while existing hardware runs cold, 45% of enterprises still plan to evaluate specialized AI clouds in the coming year. More seriously, only 44% of enterprises rigorously track their AI compute costs, creating a massive financial visibility gap where investment spending runs far ahead of accounting.
Bẫy 'chatbot' gắn mác AI Agent
This misalignment between ambition and reality is equally apparent in agentic orchestration software, as revealed in the survey of 101 enterprises. Despite constant industry buzz surrounding complex multi-step automation, 71% of enterprises admit that a quarter or fewer of their deployed "agents" are true multi-step orchestrated workflows. The rest are merely basic chatbots wrapped as agents. Currently, Anthropic leads this orchestration layer, with 40% of enterprises choosing Claude as their primary platform, driven by "model gravity" — the preference to align orchestration with their chosen base LLM.
Xu hướng dịch chuyển kiến trúc
To counter the risk of vendor lock-in, which ranks as the top concern (35% of responses), enterprises are shifting toward more flexible architectures. By the end of 2026, 51% expect to run a hybrid control plane, blending provider-native tools with external orchestration layers. Furthermore, fiscal control over token consumption by autonomous agents remains reactive. About 27% of enterprises admit they have no real-time, programmatic way to stop a runaway agent before a budget-breaking bill arrives.
Tác động & Tương lai
VentureBeat's reports deliver a stark warning to technology leaders, especially in rapidly growing markets like Vietnam: spending heavily on fashionable hardware or AI platforms without detailed performance and cost measurement systems only creates an illusion of capability. The upcoming trend is no longer about how many GPUs an enterprise owns, but about optimizing existing hardware utilization and building robust engineering guardrails to manage the financial risks of autonomous agents.