Zain Group hosted its ‘AI in Action: Smarter Network Operations’ workshop at its headquarters in Kuwait, bringing together ICT leadership from across its operating companies to showcase the company’s artificial intelligence initiatives and reinforce its position as a technology-driven telecom operator.
The workshop highlighted Zain’s progress in embedding artificial intelligence across network operations and digital transformation initiatives as part of its ‘4WARD – Progress with Purpose’ corporate strategy. The company emphasized its focus on converting AI insights into measurable business outcomes, including improved operational efficiency, enhanced customer experience, and stronger commercial performance.
Zain Group Chief Technology Officer Mohammed Al Murshed noted that machine learning, deep learning, and large language models are increasingly shaping the telecommunications landscape, with infrastructure, algorithms, and data forming the foundation of AI-driven transformation across key business functions. He added that Zain is accelerating the adoption of AI to drive efficiency gains and improve service delivery across its regional operations.
A key announcement during the workshop was the launch of an Autonomous Network Level 4 (AN L4) assessment, initiated in Kuwait and covering critical domains including wireless, core, and IP networks. The initiative forms part of Zain’s long-term roadmap to achieve advanced autonomous network capabilities between 2025 and 2030, guided by industry frameworks and high-value use cases aimed at enabling predictive, self-optimizing, and energy-efficient network operations.
The workshop also demonstrated practical AI deployments already delivering operational benefits. In Kuwait, Zain introduced intelligent agents for wireless operations and maintenance in collaboration with Huawei, aimed at accelerating fault isolation and resolution and reducing outage durations. In Jordan, LLM-powered intelligent agents are being used to analyze network complaints, classify fault types, and improve issue diagnosis and resolution workflows. In Iraq, AI-driven churn prediction models are being deployed to identify customers at risk of leaving the network, enabling proactive retention strategies while supporting broader business support system transformation initiatives.
