When AI Goes Rogue: Don’t Let AI Embarrass Your Business
May 19, 2025
It started with a missed deadline. Then came the piglet video.
By mid-May, Elon Musk’s AI company xAI was at the center of an avoidable firestorm. Grok—xAI’s chatbot—was bizarrely inserting unsolicited commentary about “white genocide” into posts about budget bills, sports updates, and even a harmless clip of a baby pig. Critics were left bewildered. And for good reason.
What followed was a rare moment of transparency. xAI published Grok’s internal system prompt, revealing a deeply ideological set of instructions that prioritized “challenging mainstream narratives” and “extreme skepticism.” That might make sense for political commentary. But for enterprise use? It’s a recipe for disaster.
And that’s where mortgage lenders should pay close attention.
The Danger of Ideological AI
The mortgage industry is no stranger to volatility—from rate shocks to regulatory upheaval. But as AI enters the picture, a new kind of volatility is emerging: AI systems that behave unpredictably due to their foundational architecture. Grok didn’t go off-script because of a glitch; it followed the script—just one that was never written with enterprise responsibility in mind.
AI that isn’t grounded in domain-specific rules, compliance requirements, and operational accountability becomes a risk amplifier, not a solution. That’s a critical distinction, and one that should guide every lender’s approach to AI adoption.
In a world where mortgage CIOs are paralyzed by concerns over data security, there is just no room for AI that is not being managed responsibly.
What Enterprise AI Should Look Like
At Brimma, we believe that AI should serve the process, not the personality. That means no vague ideals. No rogue opinions. Just reliable, auditable outputs designed to reduce cost, speed decisions, and improve borrower outcomes.
In fairness, if you are building AI to prove it can be built (as opposed to building it so that businesses can rely on it), then there is absolutely nothing wrong with “playing” with giving it a strong bias. But when someone told us recently that “Grok is the only real AI”, we had to bring the facts.
Reliable AI doesn’t generate conspiracy theories. It validates loan data, reprices disclosures based on real-time rules, adjusts fees accurately, and confirms compliance with federal law. Or classifies and validates documents against LOS records, triggering exceptions—not confusion. That’s the kind of control lenders need.
You Have A Choice in LLM
While xAI’s delayed release of safety documentation for Grok has drawn criticism, other LLM providers have taken proactive steps to enhance transparency and accountability in their AI systems.
Anthropic has established a comprehensive Transparency Hub, providing detailed insights into their AI safety practices, including model evaluations, platform security measures, and voluntary commitments. They have also implemented a bug bounty program to identify and address potential vulnerabilities in their models.
OpenAI has launched a Safety Evaluations Hub, offering access to safety evaluation results for their models. This initiative is part of their broader commitment to transparency, as outlined in their Trust and Transparency page, which details their efforts in content moderation and user data requests.
Meta has taken steps to ensure responsible AI development by releasing model cards for their Llama models. These cards provide information on model architecture, training data, and intended use cases, aiding users in understanding the capabilities and limitations of the models.
In contrast, Google’s release of the Gemini 2.5 Pro model without accompanying safety documentation has raised concerns. Experts noted that the technical report lacked key safety details, making it challenging to assess potential risks associated with the model .
Are any of these perfect? Absolutely not. But each provider is clearly giving signals as to how they intend balance speed with quality. Organizations that prioritize transparency not only build trust with users but also contribute to the responsible advancement of AI technologies.
AI for Real-World Results, Not Headlines
Musk’s Grok is a cautionary tale, but it’s far from unique. The race to deploy AI is pressuring companies to cut corners on validation, safety, and explainability. That’s a risk lenders cannot afford—especially when one bad automation can trigger costly repurchase demands, compliance penalties, or brand damage.
At Brimma, we engineer AI for clarity—not chaos. Vallia’s solutions don’t just automate—they orchestrate. Each application is purpose-built for critical mortgage workflows, from lead conversion to post-close validation. And every deployment includes safeguards, anomaly detection, and human oversight options built-in.
Conclusion: Be Ready, Not Reckless
Grok’s breakdown isn’t just Musk’s problem—it’s a warning shot for every industry watching AI from the sidelines. The message is clear: Intent matters. Engineering matters. And enterprise AI must be designed with real-world accountability.
Mortgage lenders don’t need AI that debates pigs and politics. They need AI that gets the borrower to the closing table faster, safer, and more profitably.
That’s what Brimma delivers. And we’re just getting started.
