{
  "id": 17740210,
  "title": "Manufacturing’s black art is retiring. AI may be the best chance to keep it",
  "url": "https://urgent.news/2026/11/02/manufacturings-black-art-is-retiring-ai-may-be-the-best-chance-to",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-02T04:00:00.000Z",
  "source": {
    "name": "The Business Times - Companies & Markets",
    "slug": "the-business-times-companies-markets",
    "url": "https://www.businesstimes.com.sg/companies-markets/manufacturings-black-art-retiring-ai-may-be-best-chance-keep-it"
  },
  "original_language": "en",
  "account": "Manufacturing's \"black art\" – the intuitive expertise of veteran engineers – is fading as the industry ages. As these seasoned professionals retire, their knowledge disappears with them, leaving behind a critical gap. Meanwhile, AI has proven its worth in other sectors, raising the question: Can it help manufacturing keep up?\n\nIn factories today, sensors continuously track production data, but turning this data into actionable insights remains a challenge. Dashboards are proliferating, yet decisions still rely heavily on the experience of a few key engineers. AI has the potential to bridge this gap by analyzing vast production data, identifying patterns, predicting issues, and supporting real-time decision-making on the factory floor. When a dip in yield occurs, an AI system trained on the plant's engineering drawings and production data can pinpoint the problem within minutes, recommend specific adjustments, and verify the fix.\n\nHowever, implementing AI in manufacturing presents challenges. Change management is crucial, as even small process changes can have far-reaching consequences. Companies are already allocating budgets for productivity-enhancing technologies, but convincing managers and workers to embrace change is difficult. Additionally, data security is paramount. Manufacturers view their production data as invaluable, and any AI solution must operate in-house, focusing on intelligence rather than becoming a data aggregator.\n\nTo succeed, an AI solution for manufacturing must fit seamlessly into existing workflows, leverage the data and equipment already in place, and work alongside floor engineers. The focus should be on demonstrating ROI through measurable outcomes like yield improvement, reduced scrap, and less downtime. Forward-deployed engineers play a vital role, working on-site with customers to implement AI solutions that generate clear, measurable results. By bridging the expertise gap and overcoming deployment challenges, AI has the potential to keep manufacturing's \"black art\" alive.",
  "summary": "Manufacturing may not be the most glamorous sector, but it could be where AI proves its real worth",
  "key_points": [
    "Veteran engineers' expertise fades as manufacturing industry ages",
    "AI can analyze production data to predict issues and support decision-making"
  ],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}