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 The Deanship of Scientific Research at IMSIU Hosts a Workshop on Building Smart AI Workflows Without Programming

      IMSIU, represented by the Deanship of Scientific Research, organized a specialized workshop on Tuesday, January 27, 2026, titled “Building Smart AI-Based Workflows Without Programming." The workshop was delivered by international consultant Shaher Z. Khaled.

 

      The workshop aimed to enable university staff and interested participants to understand the design and implementation of intelligent, self-operating workflows that enhance the efficiency of institutional operations. It also focused on developing practical skills in automating internal procedures to improve accuracy, accelerate execution, and enhance output quality.

 

      Participants received training on building automated invoice-processing systems using Optical Character Recognition (OCR), in addition to exploring applications for automating social media operations and artificial intelligence–powered appointment scheduling systems. The workshop emphasized identifying high-impact use cases for intelligent technologies within institutions and expanding their adoption without advanced programming expertise.

 

      The sessions focused on the concept of smart workflows that integrate tasks, systems, and data into an automated operational chain capable of making basic decisions independently. This approach reduces human involvement in routine tasks and redirects efforts toward higher-value analytical and creative work within academic and administrative environments.

 

      The workshop also highlighted the institutional dimension of automation by demonstrating how internal procedures can be reengineered using artificial intelligence tools to improve operational efficiency, reduce human error, and enhance process traceability, thereby improving service quality and response speed.

 

      On the practical side, participants learned how to develop a specialized artificial intelligence solution for invoice processing using OCR and data extraction, then convert outputs into automated actions such as matching, review, and archiving. This provided a practical model for automating financial and administrative operations.

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1/27/2026 11:01 PM
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