Post by Sandwich Lab

Meta just laid off 8,000 people and reassigned 7,000 to AI teams. Same week. Read it as an organizational hard restart: Meta is rebuilding its team structure around AI-native workflows and reorganizing into AI-focused pods. Here's the uncomfortable part. 79% of enterprises report serious challenges with AI adoption，a double-digit jump from 2025 and 54% of C-suite leaders say AI is tearing their company apart (WRITER 2026). Individual productivity is up 5X. Only 29% see meaningful ROI. The pattern is clear. Companies buy AI tools. Plug them into existing processes. Keep the same meetings, the same approval chains, the same Excel-based reviews. Then wonder why ROI never shows up. The tools upgraded. The organization didn't. We're seeing growth teams split into three types: → Tool stackers: multiple AI tools, none connected. Humans bridge every gap. This is most teams today. → Partial automators: one pipeline is AI-connected (usually creative → launch). Strategy and review still run on human meetings. → Decision system operators: AI participates in the full loop — signal, decision, action, learning. Each cycle compounds into the next. One pattern we see repeatedly: a brand expands into a new market. The old week — a two-hour strategy meeting with no local data, creative built on guesswork, launch params copied from another market. By Friday the numbers look off and no one knows why. The data lands in a spreadsheet no one reopens. The AI-native week — market signals arrive pre-structured. The lead spends 20 minutes confirming direction instead of two hours debating it. AI drafts creative and campaign configs; the human approves and corrects. Friday's review writes itself and becomes Monday's starting point. Same task. One resets to zero every cycle. The other compounds. Meta forced a jump from type 1 to type 3. Most companies don't need to be that dramatic. The direction is the same. The real shift is in how decisions get made. That's what an Enterprise Growth Decision System is built for connecting market signals, decision logic, and execution into an auditable loop. Last decade, growth competed on execution efficiency. Next decade, it competes on decision efficiency. #EnterpriseAI #AITransformation #GrowthStrategy #FutureOfWork #AILeadership #lanbow