By : Wael Elgafary
IBM announced a strategic collaboration with Elsewedy Electric, an integrated energy solutions provider, to advance enterprise-grade agentic AI adoption across the organization. The initiative reflects Elsewedy Electric’s move beyond isolated AI experimentation toward governed, action-oriented AI embedded within core enterprise workflows, leveraging IBM watsonx.ai and IBM watsonx Orchestrate.
The collaboration establishes a structured foundation for scaling AI across Elsewedy Electric operations, enabling faster decision-making, improved operational efficiency, and trusted, long-term innovation across mission-critical business domains.
Elsewedy Electric’s AI journey is anchored in its ambition to embed AI as a core enterprise capability spanning operations, supply chain, human resources, finance, legal, and market intelligence. To support this vision, IBM’s Client Engineering team partnered with Elsewedy Electric at an early stage to deliver a successful proof of concept focused on Expanding Markets Investment Research. The initiative demonstrated how AI can accelerate market intelligence and investment analysis under real-world conditions, while building confidence in AI’s enterprise value and establishing momentum for scaled deployment.
Building on this foundation, IBM worked closely with Elsewedy Electric to assess strategic business priorities and define an enterprise AI roadmap comprising more than 30 prioritized, high-impact use cases across core enterprise domains, providing a clear pathway from experimentation to enterprise-scale execution.
At the core of the initiative is watsonx.ai, which enables Elsewedy Electric to build, govern, and deploy enterprise-grade generative AI models using trusted operational and enterprise data. Watsonx Orchestrate extends these capabilities by operationalizing agentic AI – coordinating digital assistants and agents, automating AI-driven workflows, and embedding intelligence directly into day-to-day HR, planning, and enterprise processes to enable consistent execution at scale under governance controls.
Commenting on the collaboration, Ahmed Elsewedy, President and Chief Executive Officer at Elsewedy Electric, said: “Scaling AI requires more than advanced technology; it requires the right foundations to turn innovation into sustainable value. Working with IBM will help us to establish a structured, enterprise-wide approach to agentic AI—one that aligns strategy, governance, and execution and enables us to deploy AI responsibly and effectively across the organization.”
With IBM’s support, more than 10 AI use cases have already progressed into advanced delivery stages, delivering measurable productivity gains.
“As organizations move from experimenting with AI to embedding it into how they operate, governance and scalability become just as important as innovation,” stated Marwa Abbas, General Manager, IBM North East Africa. “Through the watsonx portfolio, Elsewedy Electric is advancing toward enterprise-grade agentic AI – moving beyond isolated use cases to AI capabilities that deliver measurable outcomes across the organization.”
Echoing this perspective, Dr. Hazem Shatila, Chief Artificial Intelligence Officer, Elsewedy Electric, shared: “AI is becoming a core capability that powers Elsewedy Electric’s future, not just a technology layer . By adopting IBM’s framework for change and AI agent-based approach, we were able to establish clear governance and standardized processes that enable us to consistently prioritize the right use cases, measure their impact, and scale AI across the organization with confidence.”
A key enabler of the transformation has been Xyris Technologies, IBM’s on-ground implementation partner. Along with Elsewedy Electric’s AI team, a portfolio of use cases were identified as a part of the company’s long term AI integration ambitions.
This collaboration reinforces IBM’s commitment to enabling secure, scalable, and responsible AI adoption for industrial organizations, supporting digital transformation, operational resilience, and long-term competitiveness across the manufacturing and energy sectors.
