The Loss of Control Goes All the Way Up
On Friday, June 12, 2026, at 5:21 PM Eastern Time, Anthropic received a letter from the US Commerce Department. By 9:59 PM, the company's two most advanced AI models, Fable 5 and Mythos 5, were no longer available to any customer anywhere in the world.
The reason given was national security. The letter did not specify the concern. Anthropic later disclosed its understanding of the trigger: a narrow jailbreak technique that the company's own analysis indicated is also present in other publicly available models, including OpenAI's GPT-5.5. Anthropic complied with the directive while publicly disagreeing with the standard it set.
In other words, a frontier AI model was released, restricted under national security authority, and switched off for everyone in the same news cycle. Customers who had built products on top of it had hours, not weeks, to scramble for alternatives. The company's own CEO did not know on Friday morning that the model would be gone by Friday night.
The natural reaction in a change management deck is to file this under "regulatory complexity" or "tail risk." That misses the more important reading. Your workforce saw this. They are reading what it implies. And the conclusion they're reaching is more defensible than most adoption playbooks are willing to admit.
What the workforce actually sees
For two years, employees have been told a version of the same story by their leaders. AI is the future of our company. We are investing in this tool. We expect you to adopt it. Your role and your future depend on integrating it into your daily work.
Then, in three hours, the most advanced model from the most safety-focused major AI company in the world disappeared. The company building it could not prevent the disappearance. The customers, depending on it had no recourse. Nobody could promise it would come back, or what would replace it, or which tool would be next.
If you have spent any time in mandatory training on a vendor product that quietly got deprecated six months later, you already know how to read this signal. The signal is that betting your professional identity on a specific tool, in a domain where the tool itself can vanish overnight by government order, is a worse bet than your leadership is admitting.
The leaders don't actually know either (yikes)
Here is the part most adoption playbooks studiously avoid. The people demanding the commitment are no more certain than the people resisting it.
Dataiku and Harris Poll surveyed CEOs globally in May 2026 and found that 80% believe their own job is at risk by the end of 2026 if their AI strategies fail. In the US, the figure is 81%. BCG's January 2026 AI Radar survey of 640 CEOs and 2,360 senior leaders found that half of the CEOs said their job stability depends on getting AI right this year. PwC's 29th Global CEO Survey, released at Davos, found CEO confidence in their own company's revenue prospects at a five-year low, with only 12% reporting AI has delivered both cost and revenue benefits. 56% said they are getting nothing from AI yet.
Combine those findings, and a clearer picture emerges. The leadership pushing AI adoption is doing so under personal job risk, with thin returns to date, in a market where the most advanced tools can be revoked by the government without notice. They are uncertain in ways they cannot say out loud.
Vilas Dhar, president of the Patrick J. McGovern Foundation, wrote about this directly the night of the Fable 5 shutdown. The decisions affecting which AI exists, who can access it, and on what terms are being made for everyone, in hours, with no public process. That observation is correct, and it applies inside the company as much as outside it.
The asymmetry employees correctly sense
When a leader tells a worker to commit to a tool, the implicit contract is straightforward: I am asking you to invest in this, and in exchange, the tool will be there, the company will support you, and the skill you build will pay off.
What this week made vivid is that the leader cannot honor any of those terms unilaterally. The tool can vanish. The company's AI vendor can be restricted overnight. The skill the worker builds may be specific to a model that no longer exists in six months.
Workers who hesitate to bet their professional identity on this contract are pricing in the same uncertainty that the CEO surveys are pricing in privately. The difference is that the CEO is told to project confidence, and the employee is told to comply.
Sixty years of psychological research on reactance (Brehm, 1966) and on procedural justice (Tyler and Lind) predict how workers respond to that combination. When the cost of compliance is real, and the legitimacy of the demand is questionable, people protect their autonomy by foot-dragging, by hedging, by quiet refusal. The labels "resistance," "ignorance," and "Luddism" are how organizations name behavior whose actual driver is rational risk pricing they refuse to recognize.
What this changes for leaders
The first move is to stop pretending. The leadership communication style most companies still use, projecting certainty about the AI roadmap, treating doubt as a problem to manage, and framing non-adoption as a personal failing, is generating reactance that compounds with each headline like this week's. Workers know what they're reading. The dissonance between what they see and what they're told is the actual source of their resistance.
The honest alternative is harder and more durable. Acknowledge the uncertainty. Tell the workforce what you are confident in, what you are guessing about, and what you do not know. The companies that have done this with other transformations (the move to cloud, the early years of remote work) have consistently outperformed those that played certainty theater.
The second move is to design adoption for a world where the tools will change. Build skill in working with AI rather than skill in any specific model. Protect the worker's underlying capability (judgment, relationships, ability to read the work) from being entirely outsourced to a vendor who may not exist or may not be available next year. The cognitive offloading argument I made in earlier pieces lands harder when the news cycle keeps reminding everyone how thin the ground is.
The third move is to listen to the resistance for the signal in it. The workers who hesitate are often the ones reading the situation most accurately. Treating their hesitance as information rather than as a problem to overcome is the change management posture this moment actually calls for.
The deeper point
What this week showed is that the loss-of-control feeling running through the workforce around AI is an accurate reading of a system in which:
The companies building AI cannot fully predict what their models can do.
The governments regulating AI act in hours with a limited public process.
The CEOs deploying AI face personal job risk if it fails. The workers being asked to commit have the least information and the least leverage of anyone in the chain.
Every party in this chain is uncertain. Only the worker is told to project confidence to the people below them, or, more often, told to comply quietly.
Most AI adoption frameworks circulating right now assume the worker is the irrational party. The week's events suggest the worker may be the one party in this system reading the conditions accurately. The vaccine research I did years ago kept finding the same pattern. When an institution cannot acknowledge the legitimacy of what the resister is sensing, the resistance hardens, and the campaign fails on the institution's own terms.
The leaders who handle this well in the next few years will be the ones who learn to lead through honest uncertainty rather than perform certainty. The rest will keep generating exactly the resistance they are trying to overcome.
***
Sources
Anthropic (2026). Statement on the US government directive to suspend access to Fable 5 and Mythos 5. June 12, 2026. https://www.anthropic.com/news/fable-mythos-access
CNBC (2026). Anthropic disables access to Fable 5 and Mythos 5 to comply with government directive. June 12, 2026.
Bloomberg (2026). Anthropic Says US Orders Halt to Foreign Access for Fable 5, Mythos 5 AI Models. June 13, 2026.
Dataiku & Harris Poll (2026). Global CEO AI risk survey. May 2026.
Boston Consulting Group (2026). AI Radar 2026. January 2026. 640 CEOs and 2,360 senior leaders surveyed.
PwC (2026). 29th Global CEO Survey: Leading Through Uncertainty in the Age of AI. January 2026.
Brehm, J. W. (1966). A Theory of Psychological Reactance. Academic Press.
Tyler, T. R., & Lind, E. A. (1992). A relational model of authority in groups. Advances in Experimental Social Psychology, 25, 115–191.
