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The research behind the reporting. Analyst reports, vendor comparisons, implementation playbooks, and benchmark data for enterprise teams making real AI investment decisions.

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Infrastructure and compute: Enterprises are buying AI compute for speed while flying blind on what it costs

Performance and GPU availability have overtaken cost as top buying criteria, even as most GPU fleets run at half capacity or less, new Pulse Research finds.

VB Staff

August 12, 2026

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Agentic orchestration: Enterprise AI organizations know how to govern agents but still can't meter what they cost

107 enterprises, one shared blind spot: nobody can say what their AI agents will cost until the invoice shows up.

VB Staff

August 12, 2026

Agentic security: Enterprises enforce agent permissions two-thirds of the time — and isolate high-risk agents less than one in five

Enterprises have built the controls that watch and permission AI agents, but not the one that limits damage when those controls fail.

VB Staff

August 12, 2026

Agentic reliability and evaluations: Enterprises that got burned by a bad eval are the most likely to remove humans from the loop, not the least

108 enterprises on agent evals: The ones who already shipped a bad answer are the most eager to cut humans out next, not the most cautious.

VB Staff

August 12, 2026

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Agent context layers: Enterprises governing their AI data are catching twice as many bad answers as the ones who aren't

Enterprise AI agents are giving confident, wrong answers more than once, most often at the companies best equipped to catch it.

VB Staff

August 12, 2026

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

AI infrastructure spending accelerates, yet most enterprises can't measure its economics. Only 21% run AI at scale, while 64% plan to switch providers.

VB Staff

July 23, 2026

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

AI agents in 107 enterprises face security gaps, with over half reporting incidents. Identity and isolation controls lag behind agent autonomy.

VB Staff

July 23, 2026

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

57% of enterprises report AI agents giving wrong answers due to context issues. The industry is building solutions, but most are not yet in production.

VB Staff

July 23, 2026

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

Enterprises grant AI agents autonomy beyond evaluation trust, risking customer failures. Two-thirds move toward zero-human deployment despite trust gaps.

VB Staff

July 23, 2026

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

Anthropic's Claude leads enterprise AI orchestration, favored for model gravity and reliable execution, though most agents remain simple chatbot wrappers.

VB Staff

July 23, 2026

The Control Gap: Enterprise AI organizations have an ownership problem, not a technology problem — and most are governing it by hand

145 enterprise leaders say AI spend is outrunning governance — most can't name a single owner for cross-platform AI, and shadow spending is already costing them.

VB Staff

July 1, 2026

The Agentic Reckoning: Enterprise AI organizations have a runtime problem, not a model problem — and most are building the wrong solution

New VentureBeat survey: the production failure point isn't the model. It's the runtime — and most are building the wrong fix.

VB Staff

June 8, 2026