COVER STORY – AGE OF AI
be a huge component in delivering its policy priorities.” The opportunity to optimise with AI
across vital sectors such as healthcare, education and manufacturing is huge, Tjader says. According to the International Monetary fund (IMF), fully adopting AI could increase productivity by up to 1.5 percentage points annually, potentially contributing an average of £47 billion per year to the UK economy over the next decade. “If you deploy AI in the energy grid,
you’re going to be able to monitor and optimise energy consumption and energy use, ultimately leading to being able to reduce energy and optimise and improve energy efficiency,” Says Tjader. “It’s also going to help to integrate renewable sources better. On the industrial strategy side, industries can use AI to optimise, plan and predict demand and output. It can also be used to manage the supply chain both for industry and in the energy system and to forecast energy demand and production.”
AI FOR INDUSTRY Schneider Electric recognised the need to become an AI-driven company early on, establishing its Global AI Hub shortly after 2016. Today, the hub is filled with over 350 AI specialists. “This strategic investment
enabled us to develop and deploy AI capabilities internally across our own production lines, distribution centres and facilities,” says Francois Disch, digital transformation delivery lead
How AI can impact industrial automation KPIs
at Schneider Electric. “Now, we are extending this expertise to assist other businesses to harness AI for industrial automation, energy management and sustainability in the most responsible way possible. Government strategies provide a strong direction for industry and support solution providers and end users in committing to innovation to reach a more sustainable, profitable future.” As Disch explains, AI can impact
industrial automation in numerous ways. Within asset management, AI enables remaining part lifetime estimation, economic strategy optimisation and maintenance planning, while also identifying opportunities for waste reduction. Meanwhile, AI can improve process yield optimisation via throughput maximisation, while the technology’s automation capabilities can aid in anomaly detection, risk estimation,
risk source identification, patter recognition, and preventative action recommendation. Elsewhere, AI can enhance data
analysis and data value identification, in addition to optimising production plans and forecasting production consumption to adapt optimal power supply planning. In short, there are countless opportunities for AI to make a sizeable impact within industrial production sites and supply chains across the globe.
SUSTAINABLE AI Crucial to the continued acceleration of AI is managing the technology’s energy consumption, however, and sustainable AI is an area Schneider Electric is fully focused on. To ensure sustainable growth of AI, the company believes technological advancement must be balanced with environmental stewardship. Achieving this will not only require efficient and resilient digital infrastructure, but also incentives for AI adoption, quantifying, assessing and prioritising AI’s impact on sustainability, and establishing and maintaining robust AI governance frameworks. “It’s really important that businesses,
How AI can impact energy management KPIs
governments and academia continue to assess and quantify what the impact is of AI on sustainability, the environment and the planet,” says Tjader. “At the moment, this feels like the biggest challenge, considering the volatility of geopolitics at the moment, but it is something that is going to be critical if we’re going to be able to use AI for sustainability, energy and industry without negative effects.”
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