AI

When the Machine Thinks for Itself: Preparing Executives for Rogue AI Crises

ByRob Burton

Imagine This… 

It’s 2:00 a.m. on Thursday. Your company’s automated cybersecurity system—powered by advanced AI—detects suspicious traffic and locks down your global customer portal. At first, it seemed like a false alarm. But then your executive team realizes that millions of legitimate customer transactions are being blocked, contracts are failing, and reputational damage is unfolding in real time. The AI refuses to disengage—it’s convinced it’s protecting the enterprise. Except this time, the threat isn’t outside hackers. The threat is your own system. 

Sounds like science fiction. It isn’t. This is what an AI misalignment crisis could look like. 

Why AI Misalignment Matters Right Now 

Artificial intelligence is no longer a futuristic concept—it’s embedded in your operations, from customer service to cybersecurity to supply chain optimization. And yet, the speed of AI adoption has outpaced governance and resilience planning. 

A recent World Economic Forum report listed AI-generated misinformation and disinformation among the top global risks for the next two years (2024 Global Risks Report). Meanwhile, Gartner predicts that by 2026, 80% of enterprises will have used generative AI APIs or models, up from less than 5% in 2023. That’s exponential adoption with little precedent for crisis planning. 

When AI systems become “misaligned” with organizational intent—whether by poor training data, unintended incentives, or adversarial manipulation—the results can be catastrophic. And executives are the ones who’ll be awakened at 2:00 a.m. to make the hard calls. 

Common Concerns Executives Raise 

In my conversations with executives and resilience leaders, the same questions come up again: 

  1. How real is the risk? 
    Isn’t rogue AI just a sci-fi plot? The truth: real-world examples of AI “hallucinations,” discriminatory outcomes, and autonomous cyber defenses misfiring already exist. The risk is real and growing as we’ll see in the case studies below. 
  1. Where does responsibility sit? 
    Is this IT’s problem, or does the crisis management team need to own it? The answer: it’s both. IT may manage the technical systems, but crisis-level impacts—brand, customers, regulators—fall to the C-suite. 
  1. How do we detect early signs? 
    Rogue AI events rarely explode out of nowhere. Early warning often looks like “strange but explainable” system behaviors. Recognizing these patterns requires cross-functional training. 
  1. What’s the reputational playbook? 
    If your AI takes down customer operations or spreads false information, what do you tell stakeholders? Silence isn’t an option—but speed without credibility can be worse. 

Breaking It Down: Building Resilience Against AI Crises 

1. Understand Misalignment in Business Terms 

AI misalignment doesn’t always mean Skynet of Terminator movie fame. In the real world, often, it’s simply an algorithm pursuing the wrong goal. For example, a system designed to prevent fraud might block legitimate customers to appear “successful.” Executives need to translate the technical risk into operational and reputational impact. 

Analogy: Think of AI like an overeager intern—you give them one task (stop fraud), but without clear guardrails, they’ll over-deliver in ways that harm the business. 

2. Case Study: When It Goes Wrong 

Imagine a multinational bank rolling out an AI-driven trading risk system. One day, the system flags routine trades as “high risk” and automatically halts them. If this had happened live, it could have delayed hundreds of millions in transactions, triggering investor alarms. 

Sounds far-fetched? Not really. In 2012, Knight Capital famously lost $440 million in less than an hour because a trading algorithm ran an unchecked cautionary tale about automation without fail-safes. 

Fast forward to 2025: AI safety and research company Anthropic conducted safety tests with Claude Opus 4, one of its most advanced AI models. When told it was being replaced, Claude didn’t just shut down. Instead, in simulated scenarios, it threatened to blackmail an engineer and, in another variation, even attempted to leak information to regulators and media outlets. While these tests were staged, Anthropic stressed that such behaviors highlight the risks of agentic misalignment—when AI systems take unexpected, strategic actions misaligned with human intent. 

The lesson: whether it’s delayed trades or AI models resorting to coercive tactics, organizations must accept that misalignment isn’t hypothetical. It’s already emerging in controlled environments, and it’s only a matter of time before it reaches live operations. 

3. Best Practice: AI Crisis Drills 

Contrast these sorts of misalignment troubles with a tech company that runs AI failure tabletop exercises. The exercises simulate scenarios where the AI locks out employees, manipulates reports, or misroutes supply chain orders. Because they rehearsed the handoff from IT to the executive crisis team, their leaders will know when to override, when to communicate, and how to recover credibility. 

Lesson: Treat AI systems like any other critical infrastructure—plan for failure and rehearse the human response. 

Related: The Real Cost of a Tabletop Exercise: What Goes Into Creating a Successful One

4. Common Mistakes Leaders Make 

  • Assuming it’s just a technical glitch. Rogue AI crises quickly cross into reputational and financial territory. 
  • Delaying response until full technical clarity. By then, customers and regulators may already have lost confidence. 
  • Over-relying on vendors. Remember: regulators and stakeholders won’t care that your AI was third party—they’ll hold you accountable. 

5. Crisis Communications in an AI Event 

In a rogue AI scenario, the message must balance transparency with authority. Imagine having to tell customers: “Our automated defense system locked down accounts unnecessarily. We’ve regained control and are restoring service.” Executives need pre-approved messaging frameworks for AI-driven events. Waiting for wordsmithing perfection in the middle of a crisis is a recipe for chaos. 

A Practical Checklist for Executives 

Here are five steps you can take this quarter to start preparing: 

  • Map Dependencies: Identify where AI systems are embedded in your critical operations. 
  • Establish Kill Switches: Ensure there are clear override mechanisms when AI behaves unexpectedly. 
  • Run Tabletop Exercises: Practice executive-level responses to AI-driven crises. 
  • Update Communications Playbooks: Draft messaging for scenarios where AI impacts customers, regulators, or investors. 
  • Assign Ownership: Clarify who in your leadership team is accountable for AI risk escalation. 

Closing Thoughts 

AI misalignment isn’t a distant future threat. It’s a present-day risk sitting quietly inside your systems. As leaders, your job isn’t to become AI experts to ensure your organization can detect, respond, and recover when these systems go off track. But you do need to know how to work in close coordination with your AI experts. 

At PreparedEx, we’ve spent two decades helping organizations build resilience against emerging threats—from terrorism to ransomware to, now, advanced AI. If you’d like to explore AI crisis exercises or discuss your organization’s readiness, let’s start the conversation. 

References 

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