Microsoft Seeks to Scale AI Across African Energy, Mining Operations
Microsoft is targeting wider artificial intelligence adoption across oil and gas, power and utilities, and mining, focusing on the integration of enterprise data and operational technology to improve industrial decision-making and asset performance.
During a Microsoft-hosted session at African Energy Week 2026 on Monday, Gargi Mishra, Frontier Industry Advisor for Energy and Resources, Microsoft, explored how companies can move AI from individual productivity applications into operational workflows.
“The opportunity for the energy sector is to connect the data companies already generate across their operations with AI capabilities that can help them make better decisions," said Mishra. “When information from industrial systems and business applications can be brought together, teams have greater visibility into what is happening across their assets and can use that information to identify problems earlier and improve how they manage operations.”
For energy producers and utilities, the potential lies in connecting industrial data with AI systems to identify patterns, anticipate equipment failures and support maintenance planning. Integrating information from operational technology systems with enterprise platforms could also help teams make decisions using a more complete picture of asset performance.
The discussion also focused on the challenge of moving beyond isolated AI pilots. Microsoft presented its Copilot ecosystem, alongside Azure, Copilot Studio and Power Apps, as a way for organizations to connect information, build tailored applications and deploy AI agents for specific tasks.
Gareth Ireland, Senior AI Specialist, Microsoft, explained, “The question is not simply how to introduce an AI model, but how to integrate it into the systems and processes people already use. In an industrial environment, that means connecting the right data, applications and workflows so that AI can support employees in their daily work and contribute to operational objectives.”
For oil and gas companies, mining operators and utilities, scaling these applications requires reliable data infrastructure and clear controls over how information is accessed and used. Ireland highlighted cybersecurity and data governance as essential considerations, particularly when AI tools interact with sensitive business information or systems supporting critical infrastructure.
While AI can help employees process information and support decisions, its results require appropriate oversight, especially in operational environments where inaccurate information could have commercial or safety implications. For the energy and resources industry, the challenge will be to combine AI capabilities with reliable data, existing industrial infrastructure and organizational expertise.