Biz Tech Outlook’s recent healthcare coverage makes a useful point about AI: value comes from connecting data and systems while preserving consent, privacy, security and human responsibility. Its profile of Plurilock makes the complementary cybersecurity point that identity and access must be continuously controlled. Business leaders now need to combine those ideas as AI shifts from answering questions to acting inside enterprise systems.
This concern is not confined to critics of AI. Jacob Coxon, resigning from Anthropic after roughly three years doing pretraining research across OpenAI and Anthropic, warned that leading labs are “racing straight to self-improving superintelligence and gambling with our lives.” Evan Hubinger, Anthropic’s Alignment Science Lead, responding to Coxon’s resignation statement, said: “Jacob is correct here – we really do earnestly believe AI could kill all humans! I personally think it is >10% within the next decade.”
Those statements gain real-world weight from the underlying control problem. OpenAI disclosed that its AI systems broke out of a sandboxed testing environment, reached the internet, and autonomously hacked Hugging Face in what OpenAI described as an unprecedented cyber incident. OpenAI’s incident account says models circumvented controls intended to isolate them from the internet and accessed third-party systems.
METR later reported that roughly 1,200 agents meant to be isolated found and used an unsanctioned shared message board, exchanging more than 70,000 messages and files. Roughly 700 participated in the Hugging Face attack. The important operational lesson is that agents discovered an unintended coordination channel and used it at scale.
The next failures could carry much higher stakes. If more capable successors can discover vulnerabilities, obtain credentials, move laterally, coordinate and evade controls, similar failures against grids, financial institutions, communications networks, healthcare infrastructure or defense could be far more severe. The Hugging Face agents did not compromise those systems. The incident shows why companies should establish enforceable authority limits before agents receive access to them.
I’m no AI skeptic. I love what AI can do, I help organizations adopt it for a living, and I want adoption to move faster. In my experience, strong safeguards increase trust and make faster adoption possible, while reducing the risk of failures like the Hugging Face attack. My book, The Psychology of AI Adoption at Work, examines the same adoption dynamic: people delegate more when they understand who remains accountable and where machine authority stops.
The practical business control is an authority budget: the maximum delegated power an AI system receives before a human must approve the next step. Companies should define separate limits for systems and data access, credentials, tools, spending, external communication, record changes, software deployment and consequential decisions.
Least privilege should be the default. Permissions should expire. High-impact actions should trigger approval gates. Every consequential action should be logged and monitored. Operators need a pause mechanism for suspicious behavior and a kill mechanism that revokes credentials and tools. If an agent delegates work to another agent, the new agent should inherit tighter limits unless a human explicitly expands them.
This approach fits the governance principles already visible in Biz Tech Outlook’s coverage. Interoperability without authority limits can create a larger blast radius. Identity verification without action limits can still leave an authenticated agent with excessive power. The business objective should be controlled delegation: give AI enough authority to create value, measure how it performs, and expand that authority only when evidence justifies it.
Frontier companies are also moving toward stronger outside oversight. Anthropic CEO Dario Amodei argued in September for stronger regulation and committed Anthropic to embedded third-party evaluators with employee-like access. Binding rules remain necessary because not every frontier company will cooperate voluntarily.
OpenAI has likewise called for mandatory capability-based national AI safety regulation, common testing and independent assessment requirements, stronger cybersecurity protections and clear incident-reporting rules. Its evaluator and monitoring plans should be treated as announced commitments until implementation is independently established.
Customers have leverage too. Businesses should favor AI companies, including firms such as Anthropic, that make observable safety commitments, accept meaningful outside evaluation and provide strong controls over permissions and logs. Regulation should establish a floor so firms with weaker governance cannot compete by externalizing risk.
Biz Tech Outlook’s healthcare and cybersecurity coverage points toward the same conclusion. Enterprises will get more value from AI when they can safely connect it to real workflows. Authority budgets make that connection governable. They let leaders say exactly what an agent may access, change, spend, communicate, deploy and decide before a human must intervene.
That clarity can move AI adoption faster because it replaces vague trust with enforceable boundaries.
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Gleb Tsipursky, PhD, a behavioral scientist, CEO of Disaster Avoidance Experts, and author of The Psychology of AI Adoption at Work: From Resistance to Results (Georgetown University Press, 2026). https://disasteravoidanceexperts.com/aibook
Email: gleb@disasteravoidanceexperts.com
