{
  "id": 10214544,
  "title": "AI Is Not the Solution to Every Problem: When Rule-Based Systems Make More Sense",
  "url": "https://urgent.news/2026/09/27/ai-is-not-the-solution-to-every-problem-when-rule-based-systems-make",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-27T12:44:19.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/shivraj8615/ai-is-not-the-solution-to-every-problem-when-rule-based-systems-make-more-sense-jnh"
  },
  "original_language": "en",
  "account": "AI has become a buzzword for solving tasks across various industries, from using Large Language Models for Retrieval Augmented Generation on technical documents to generating designs with diffusion models or defect detection using image processing techniques like YOLO. However, it is becoming apparent that AI may not be the most efficient solution for every problem, particularly those that can be effectively addressed with rule-based systems that require less computational power and training.\n\nFor instance, consider the creation of a Bill of Materials (BoM) from a Piping and Instrumentation Diagram (P&ID). While AI-based solutions, such as using YOLO for object detection, may appear appealing due to their ability to automatically count equipment, they come with several limitations. The line tracing, properties, and other technical aspects present challenges in accurately detecting and categorizing each equipment. Furthermore, AI models need to be retrained whenever new equipment is added, increasing the cost and complexity of the solution.\n\nOn the other hand, a rule-based approach utilizing logic, understanding of drawings, and Python programming can provide a more cost-effective and efficient solution. By treating the drawing as a graph with nodes representing each equipment and connections denoting the piping relationships, Python libraries such as ezdxf can convert DWG files to DXF format, which is more accessible and editable. This allows for layer-by-layer JSON extraction of equipment information, which can then be directly inserted into an Excel template or generated as a PDF using libraries like pyxl.\n\nIn conclusion, it is crucial for decision-makers and solution builders to thoroughly evaluate the context and requirements of each use case before resorting to AI-based solutions. According to the Kaggle course on AI ethics, AI should be used judiciously and only when it genuinely enhances the process, taking into account factors such as computation cost, training time, and data collection. By leveraging rule-based systems when appropriate, organizations can save costs, reduce complexity, and produce more reliable results.",
  "summary": "Extensive Use of AI for Simple Task Costing Token and Even Then Not Producing Favorable Results Today AI has been the buzzword every industry that wants to solve their task with the utilisation of AI, whether it be LLM application for RAG on technical document to ask for solutions, whether it be code, idea, calculation etc., any diffusion model for design, poster generation and all, using image…",
  "key_points": [
    "AI not always best solution, rule-based systems more efficient for certain tasks",
    "Rule-based approach using Python and graph theory cheaper than AI for BoM creation",
    "Organizations should evaluate context before adopting AI solutions"
  ],
  "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."
}