In factories, AI-powered robotics and algorithms are speeding up manufacturing for shampoo, dog food, and more (www.businessinsider.com)

Manufacturers from legacy firms to startups are embedding AI across new production sites to boost output, cut costs and reduce downtime. Bausch + Lomb deployed Arena AI’s Atlas predictive‑maintenance system in new contact‑lens lines and says it enabled production of “millions of lenses” more than would otherwise have been possible. Startups—Prose, Spot & Tango and FranklinWH—have likewise added AI: Spot & Tango uses Didero’s agentic supply‑chain tool to log and confirm purchase orders and build production schedules (now automating ~60% of POs), FranklinWH applies camera‑based visual‑inspection models on lithium‑iron‑phosphate battery lines to flag quality issues, and Prose runs autonomous robotics plus some 200 ML algorithms for demand planning, formulation, predictive maintenance and scheduling to cut per‑unit manufacturing markup below $1. Technically, these deployments combine predictive‑maintenance alerts, continuous‑learning vision models, agentic procurement agents, and large suites of optimization algorithms to prevent failures, improve yield, and scale capacity without proportional headcount increases. A KPMG survey found 77% of manufacturers plan to boost AI investments this year, underscoring rapid industry adoption. Companies emphasize careful piloting and human oversight—testing tools in real scenarios for months—because vendor promises can overstate readiness and integration often surfaces unforeseen technical or adoption challenges.