Post by ForceTechh

Morgan Stanley Cut 2,500 Jobs. Amazon Cut Its Robotics Team. Both Are Betting Big on AI. Here's the Problem With That Math. Eugene Kim Business Insider Adam Chronister Glen Loveland Thomas Wagenberg The Wall Street Journal Morgan Stanley just laid off 2,500 employees across investment banking, wealth management, and asset management. Amazon cut at least 100 jobs in its robotics division. Both companies framed the cuts around "shifting priorities" and "efficiency gains." Here's what makes this interesting: Morgan Stanley reported an 18% profit INCREASE for Q4 2025. Amazon just deployed its ONE MILLIONTH robot and has trimmed 30,000 corporate employees since October, tying the cuts directly to AI efficiency gains. So profit is up. Automation is accelerating. And companies are cutting the people who... build and manage that automation? Amazon's robotics division designs the warehouse automation systems. Morgan Stanley's wealth management and investment banking teams develop the AI tools and algorithmic trading platforms. These aren't back-office administrative roles getting eliminated. These are the people building the systems companies claim will drive future growth. CEO Andy Jassy said it directly last year: "As we roll out more Generative AI and agents, it should change the way our work is done. We will need fewer people doing some of the jobs being done today." But here's the cycle nobody's addressing. Block cut 4,000 people because AI could supposedly handle their work. Forrester research shows 55% of companies regret those AI layoffs and quietly rehire within a year. When Morgan Stanley and Amazon realize they actually NEED the robotics engineers and wealth management technologists they just laid off, how will they identify qualified replacements? Through the same credential-based hiring systems that can't detect overemployment, can't connect 7.4M job seekers to 6.5M openings, and auto-reject qualified candidates for resume gaps. ForceTechh Take Companies are cutting the people who build automation, betting AI can replace specialized expertise. When that bet doesn't pay off and they need to rebuild those teams, their hiring infrastructure won't be able to identify the talent they're looking for. PLCD verifies what people can actually DO through real work demonstrations. When companies realize they cut too deep and need to rehire robotics engineers or wealth management tech specialists, verification systems that test capability matter more than algorithms that screen for employment gaps and credential pedigree. The pattern is consistent: cut jobs for efficiency, realize you need the expertise, struggle to rehire because your own systems filter out qualified people. If you're laying off specialized teams while investing heavily in the areas they support, what's your plan for identifying that expertise when you need it back? #TechLayoffs #AIAutomation #WorkforceStrategy #FutureOfWork #TalentVerification https://forcetechh.com/