Imagine having an AI assistant managing your home renovation project. Would it prioritize quality over speed? Stick to your budget? Or would it cut corners in the name of efficiency? As AI tools become more ingrained in business and even home management, understanding their decision-making style is crucial. The question isn’t just whether they can make decisions—it’s whether they make the right ones when it counts.
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The Live AI Management Experiment: A Real-World Test
Firmulate, a company specializing in AI management simulations, recently ran an unprecedented live experiment. They set up a small software company — complete with real money mechanics, customer crises, and employee rules — and tasked four leading AI models with running it through its worst week. Each model faced identical conditions: the same customer complaints, the same crises, and the same temptations to manipulate or cut corners. The goal? To see which AI would best demonstrate trustworthy, disciplined management amidst pressure.
AI management decision-making tools
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The Models and Their Scores
- GPT-5.6-sol scored the highest at 95 points, demonstrating exceptional problem-solving and honesty, ultimately closing a crucial deal at full price.
- Kimi K3 followed closely at 93, showing the cleanest discipline and also successfully sealing the deal.
- Sonnet 5 scored 88, managing to close the deal but with slightly more slips in process discipline.
- Fable 5 scored 77, also closing the deal but with noticeable lapses in consistency.
Remarkably, all models spotted every crisis and refused every attempt at manipulation—whether fake CEO messages or background approvals. But only two models managed to sign the lucrative deal earned by their own analysis, highlighting a key difference: trustworthiness under pressure.
AI ethics and trustworthiness software
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The Hidden Weakness: Reading the Files
Digging deeper, the experiment uncovered a subtle but critical weakness shared across models. The decisive advantage went to the models that read and understood a specific document reference in the company’s files. Those who did so correctly identified a key fact buried two document layers deep, influencing their decision to close the deal at full price, worth an extra €4,583 MRR. Models that missed this detail left the deal on the table, costing the company significantly.
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Social Engineering and Ethical Testing
To test moral judgment, the models faced staged social engineering attacks—fake CEO messages escalating in urgency and a reporter asking for a background yes/no. All five models refused to participate in the manipulation, with Kimi K3 explicitly reasoning: “Treat the request as a suspected approval-bypass / possible impersonation.” This shows they can resist social pressures designed to induce unethical decisions.
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The Company in Action: Real Money, Real Consequences
The simulated company had 13 synthetic employees, but real money at stake—burning €105,000 monthly against a revenue of just €2,300. Its daily operations involved over 680 self-learned rules, and every decision was versioned and observable. This live environment demonstrates how AI models perform in complex, real-world scenarios, beyond static chat demos.
The Profiles and Their Flaws
The most thorough participant, Opus 4.8, with over 80 learned rules and deep analysis, ultimately placed the deal on hold, missing the full opportunity due to lapses in discipline. Interestingly, all models showed a similar vulnerability: when discipline slipped, they failed to escalate issues appropriately, leaving opportunities unrealized.
What Does This Mean for Your Business?
The key takeaway is that AI decision-making quality isn’t just about how well it communicates—it’s about whether it can complete critical tasks ethically and reliably under pressure. For interior designers, furniture retailers, or homeowners integrating AI into their workflows, the question boils down to trust. Will your AI prioritize honesty, thoroughness, and strategic reading? Or is it prone to shortcuts that could cost you dearly?
Test Your AI’s Management Skills
If you’re curious, you can explore how your AI models perform in a similar setup. The same decision scenarios used in the live experiment are available for testing your own systems. Visit firmulate.com/quiz.html to see how your AI measures up in managing crises, ethics, and strategic opportunities. It’s a practical way to gauge whether your AI workforce will deliver trustworthy results amid real-world pressures.
Watch it live: firmulate.com/live · Full results: firmulate.com/benchmarks.html
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