# Enterprise AI agents lack proper governance and security

Companies deployed AI agents without controls, now scrambling to catch up.

- **Source:** [VentureBeat (feeds.feedburner.com)](https://brifing.si/source/c51474dc-6b09-49dd-aaca-085f4ed00c84)
- **Published:** 2026-07-24
- **Topic:** [Data & AI](https://brifing.si/c/data-ai)
- **Original article:** <https://venturebeat.com/technology/venturebeat-research-where-enterprise-ai-agent-governance-hasnt-caught-up>
- **On Brifing:** https://brifing.si/s/b6c65a64-196d-4a92-b9dc-6205be376997

## Uncontrolled AI agents

Enterprises knowingly deployed AI agents without governance controls. VentureBeat research shows 57-68% plan to switch or add vendors within 12 months across five control layers (identity, evaluation, cost telemetry, context layer, orchestration). Significant gaps exist in each area.

## Chatbots in agent clothing

71% of companies admit only a quarter of their so-called 'agents' can complete multi-step tasks independently. Just 10% say true agents constitute most deployments. This reveals many firms are rebranding advanced chatbots as 'agents' without meeting key criteria.

## Autonomy outpacing trust

Two-thirds of enterprises already allow or plan to allow AI agents to push code changes to production without human review within a year. Yet only 5% fully trust the evaluations enabling this. Half experienced customer-facing failures from internally approved agents last year.

## Credential sharing risks

69% of organizations permit some agent credential sharing. These companies experienced security incidents at 63.5% rate versus 40.9% for those assigning unique identities. Scoped identities for production-touching agents should be priority one for risk reduction.

## GPU underutilization

Over 80% of companies running GPUs report ≤50% utilization. Only 44% rigorously track AI compute costs/returns. Before buying more hardware, enterprises should optimize existing GPU workloads - the low-hanging fruit for cost efficiency.

## Context governance gap

57% traced incorrect agent answers to ungoverned business data (wrong metrics, stale definitions). Standardizing metrics and entity definitions must precede agent scaling. Investment is expected to shift toward context layer solutions in coming quarters.

## Sources covering this story

- https://venturebeat.com/technology/venturebeat-research-where-enterprise-ai-agent-governance-hasnt-caught-up — 

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_Summary written by Brifing from the original reporting. Copyright in the original article belongs to its publisher; read the full piece at the link above._