Energy management and automation company Schneider Electric introduced a new industrial generative artificial intelligence (AI) copilot in collaboration with Microsoft. Designed to boost productivity and enhance workforce efficiency, it integrates Microsoft Azure AI Foundry with Schneider Electric’s industrial automation solutions.
Eliminating repetitive tasks, the generative AI-powered assistant simplifies application development to deliver efficiency gains and help bring quality solutions to market faster, according to the announcement.
What are industrial copilots?
Industrial copilots are increasingly adopted to address labor shortages and enhance complex operations. They empower workers by reducing mental strain, providing support and retaining knowledge despite high turnover.
By automating routine tasks, copilots boost productivity and allow workers to focus on complex activities. They improve efficiency with real-time recommendations, leading to smoother operations and quicker decisions. Copilots also minimize machine downtime with immediate troubleshooting and predictive maintenance, integrate data for better decision-making and reduce manual work, saving costs.
Industrial generative AI copilot available in Schneider’s new automation environment
The new copilot will be available within Schneider’s newly launched unified automation environment, EcoStruxure Automation Expert Platform, a press release stated. The EcoStruxure Automation Expert Platform integrates across various hardware and software platforms, enhancing collaboration between copilots, operators and engineers by incorporating real-time data access – crucial for providing accurate recommendations, predictive maintenance and immediate troubleshooting.
“We are at a pivotal moment where industry must achieve unprecedented levels of flexibility and efficiency with generative AI,” said Aurelien LeSant, chief technology officer (CTO) at Schneider Electric, industrial automation. “Our copilot, developed in collaboration with Microsoft and leveraging our deep domain expertise, is designed to improve industrial competitiveness by boosting worker confidence, simplifying processes and bridging skills gaps.”
The innovative solution proactively assists engineers in adding complex functionalities, such as new production lines, with simple steps by pre-generating code, checking for errors and improving the reuse of existing libraries, LeSant added. “It allows engineers and operators to leverage Schneider Electric’s industrial data sets to bring systems online faster and optimize them for long-term success.”
Generative AI adoption is soaring
Generative AI adoption is soaring with 95 percent of US companies now using it, up 12 percentage points in a year, according to the Generative AI Readiness Survey by Bain & Company. It found more than 80 percent of generative AI use cases meet or exceed expectations – with 60 percent of firms seeing business gains.
Investment is also surging. AI budgets have doubled over the past year with most allocation expected to come from standard budgets.
However, scaling generative AI still poses challenges, exposing talent gaps and vendor issues with concerns about security, output quality and leadership support slowing adoption.
Generative AI is transforming industries, but its true power hinges on data. Simply put – without high-quality, well-governed data, generative AI remains an unfulfilled concept, unable to drive meaningful impact. As AI continues to evolve, data governance will be the bedrock of its success, ensuring ethical, transparent and high-quality data underpins AI-driven systems.
Image credit: Schneider Electric
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