CASE STUDY business operations. The collaboration is designed to improve decision-making, operational efficiency and long-term innovation across key enterprise functions including supply chain, finance, legal, human resources and market intelligence.
IBM’ s Client Engineering team initially supported Elsewedy Electric through a proof-of-concept project focused on expanding markets investment research. The project demonstrated how AI could accelerate market intelligence and investment analysis while building confidence in enterprise AI adoption.
Following this, IBM and Elsewedy Electric developed an enterprise AI roadmap featuring more than 30 prioritised use cases across major business areas. More than 10 AI initiatives have already entered advanced delivery stages and are delivering measurable productivity improvements.
Watsonx. ai enables the company to build and govern Generative AI models using enterprise data, while watsonx Orchestrate supports Agentic AI workflows through digital assistants and automation. Implementation support is also being provided by Xyris Technologies, helping drive long-term AI integration and Digital Transformation initiatives across the organisation.
We asked key executives further questions to find out more.
Ahmed Elsewedy, President and CEO at Elsewedy Electric
How is Agentic AI transforming core enterprise workflows across Elsewedy Electric’ s operations?
Agentic AI is transforming the way we operate across both our corporate functions and industrial environment. At Elsewedy Electric, we work across a wide spectrum of industries, from cables and construction to infrastructure and digital solutions, with operations spanning multiple global markets. Managing that level of complexity requires faster, more informed decision-making across the entire value chain.
Through our collaboration with IBM, we are embedding AI into functions such as finance, HR, legal, planning and market intelligence, while also enabling smarter co-ordination and better visibility across manufacturing and factory operations. AI is helping streamline planning, improve forecasting accuracy, and enhance execution across subsidiaries and production facilities.
Just as importantly, it allows our teams to shift their focus toward higher-value decisions, while AI handles more repetitive and data-intensive processes. In industrial environments, it also plays a role in supporting safer operations through earlier risk detection and more proactive monitoring. The result is a more agile and responsive organisation, better equipped to meet the demands of global markets.
What challenges have you faced in moving from isolated AI use cases to a fully governed, enterprise-wide AI strategy?
The main challenge was not the technology itself but ensuring alignment across a large and diverse organisation. With over 50 subsidiaries and 34 production facilities, moving from isolated pilots to a fully scaled AI model required consistency in how we approach data, processes and decision-making.
It was essential for leadership to take clear ownership of this transformation and position AI as a business enabler rather than a standalone technology initiative. At the same time, we worked to build a shared mindset across the organisation, one that recognises AI as a practical tool for improving performance.
This meant putting in place a unified framework with clear governance, common standards, and integrated systems that allow insights to flow seamlessly across both corporate functions and factory operations. That consistency is what enables us to scale AI in a responsible and effective way.
How do you ensure that AI adoption delivers measurable business value while maintaining strong governance and scalability?
We approach AI as an enabler of business performance, where every initiative is linked to a clear objective and measurable outcome. This may include improvements in productivity, faster decision-making, stronger planning or more efficient resource allocation across our operations.
Given the scale of our business, even incremental gains can have a meaningful impact. We track this through key operational indicators such as delivery timelines, cost efficiency and productivity across business units.
At the same time, governance remains central to how we scale. AI systems are embedded within our existing operational frameworks, ensuring
Agentic AI is transforming the way we operate across both our corporate functions and industrial environment. www. intelligentcio. com
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