The country sales director, Process Automation, Sub-Saharan Africa at Schneider Electric, Elijah Daniel, has said AI-powered industrial intelligence is transforming operations by enabling companies to use years of operational data to improve efficiency, reduce downtime and strengthen decision-making.
Speaking on the impact of AI on industrial operations, Daniel said yesterday that the biggest advantage lies in connecting an organisation’s operational history, including process data, maintenance records and equipment performance, to AI systems capable of generating actionable insights.
He said Africa stands to benefit significantly from the technology, particularly in the oil and gas, mining, energy and manufacturing sectors, where skilled personnel are unevenly distributed and operations often span vast geographical areas.
According to the African Development Bank (AfDB), AI deployment could contribute up to $1 trillion to Africa’s gross domestic product (GDP) by 2035.
Daniel said industrial intelligence differs from general AI because it is trained on a company’s own operational data rather than publicly available information.
“What matters is what you feed it. Every oil and gas facility, every FPSO, every mine holds years of irreplaceable operational history. Once connected to AI, it becomes something a competitor cannot easily replicate,” he said.
He cited industry examples, noting that the Abu Dhabi National Oil Company (ADNOC) generated $500 million in AI-driven value in 2023, while Norway’s Equinor recorded $130 million in AI-related savings in 2025.
Daniel said AI enables predictive maintenance by identifying equipment likely to fail before breakdowns occur, allowing operators to take preventive action and minimise costly disruptions.
He added that Schneider Electric and AVEVA are developing connected worker solutions that provide field technicians with real-time access to equipment history, maintenance records and operational data, regardless of their location.
According to him, the approach allows engineers, control room operators and field workers to work from the same operational information in real time, improving productivity and decision-making.
“The future control room is not a room. It is wherever the worker happens to be standing,” Daniel said.
He maintained that companies that successfully combine AI with their institutional knowledge and empower their workforce will be better positioned to outperform competitors over the coming decade.
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