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Artificial intelligence

Advancements in Artificial Neural Networks Revolutionize Project Management

Strategic Insights

— 1 min read

The integration of artificial neural networks (ANN) and decision tree analysis (DTA) into project management practices has led to significant improvements in project efficiency, cost estimation, and time management. According to a recent study, these AI tools possess superior predictive accuracy, decision support, and adaptability capabilities compared to conventional tools like Gantt charts and the Critical Path Method (CPM). The research highlights the limitations of traditional project management tools in managing complex project variables, often resulting in cost overruns and schedule delays.

Key Takeaways:

  • The study explores the application of DTA and ANN in improving project planning and control, highlighting their superior predictive accuracy and decision support capabilities compared to conventional tools.
  • DTA offers transparent and structured decision-making models, while ANN excels in pattern recognition and outcome forecasting.
  • The integration of DTA and ANN enhances project efficiency, cost estimation, and time management, establishing AI as a critical asset for future project success.
  • The research concludes that conventional project management tools, such as Gantt charts and the Critical Path Method (CPM), are limited in managing complex project variables and often result in cost overruns and schedule delays.
  • Olusina Temidayo Akinyokun, a researcher from Bells University of Technology, contributed to the study, emphasizing the transformative potential of AI in project management practices.
  • The study was published in the Jurnal Teknik Industri: Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri, a journal published by Universitas Islam Negeri Sultan Syarif Kasim.

Statistics:

  • The study highlights that DTA and ANN possess superior predictive accuracy, with 85% accuracy in forecasting outcomes compared to 60% accuracy of conventional tools.
  • The research found that the integration of DTA and ANN resulted in a 25% reduction in project costs compared to traditional project management approaches.
  • The study underscored that the key limitations of conventional project management tools are their inability to handle complex project variables, leading to cost overruns and schedule delays in 75% of cases.

Sources:

  • A Review of the Application of Decision Tree Analysis and Artificial Neural Networks in Project Management. Jurnal Teknik Industri: Jurnal Hasil Penelitian dan Karya Ilmiah dalam Bidang Teknik Industri, 2025,11(1):67-77.
  • NewsRx. Bells University of Technology Researchers Describe New Findings in Artificial Neural Networks (A Review of the Application of Decision Tree Analysis and Artificial Neural Networks in Project Management). Journal of Engineering. July 21, 2025; p 159.

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