Algorithms just became the new smoke-filled room. Here's what that means for your tech stack. The DOJ's settlement with RealPage in late 2025 changed everything. Not just for real estate — for every company using shared pricing tools or third-party AI models. The core finding: when competing businesses feed data into the same algorithm, regulators now treat that as coordinated price-fixing. Same legal weight as executives shaking hands on rates behind closed doors. California and New York followed with their own laws. The message is clear — if your AI touches market decisions and runs on shared infrastructure, you're exposed. Here's what most teams miss: Sending your business data through a public API doesn't just create a security gap. It creates a legal one. When your competitors use the same model trained on similar signals, regulators can argue you're participating in indirect information exchange. The fix isn't "stop using AI." It's about where the AI lives and what data it touches. Our latest research breaks down the architecture shift happening right now — private model deployment, mathematically provable privacy layers, and hybrid systems where human judgment governs every critical decision. Three things the DOJ settlement now requires: → No live competitor data in pricing recommendations → No auto-accept features without human override → Pricing logic must weigh decreases equally to increases This isn't theoretical. These are enforceable rules reshaping enterprise software in 2026. Save this if your company uses any algorithmic pricing, revenue management, or AI-powered market tools 🔖 What industry do you think gets hit with enforcement next — healthcare, logistics, or financial services? #algorithmicpricing #enterpriseAI #antitrustlaw #AIconpliance #datasovereignty