How AI will unlock new possibilities in 2025
Edwin van den Maagdenberg, Vice-President of Industrial Automation for Europe at Honeywell, shares the possibilities or AI in energy in 2025.

In the first of a series of articles, industry experts offer their insights into the trends and technologies they believe will come to the fore in the energy transition in 2025. First up are the predictions of Edwin van den Maagdenberg, Vice-President of Industrial Automation for Europe at Honeywell, on AI new possibilities.
Artificial intelligence is shaping the path to autonomy across industries, revolutionising how businesses process and act on vast amounts of data.
For companies looking to unlock new avenues for growth, this acceleration represents a major opportunity. AI’s ability to analyse enormous datasets at vastly superior speeds – and in the case of deterministic AI, make precise, data-driven decisions – offers a distinct advantage.
In industries where ambiguity can cause significant operational setbacks, this level of accuracy is invaluable.
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As deterministic AI continues to address some of the most pressing industrial challenges, 2025 is set to be a pivotal year for data intensive industries.
Many sectors are grappling with persistent labour shortages, particularly in roles requiring precision, safety and reliability. AI can play a transformative role by upskilling workers, and closing critical skills gaps within manufacturing.
By harnessing real-time data insights and digital augmentation, AI can enable a two-year novice to quickly develop decision making capabilities more akin to those of a 30-year veteran. This accelerated path to expertise empowers workers while enhancing productivity.
AI-powered automation
The synergy between automation and energy efficiency is another significant area of opportunity, especially as businesses strive to balance sustainability targets with growth and cost management.
For example, AI-powered automation can quickly optimise energy usage across industrial processes and buildings, reducing both energy intensity and operational costs.
Similarly, AI-enhanced control systems allow plants and facilities to operate at peak performance for longer periods, improving efficiency while minimising downtime.
Automation is also playing a critical role in shaping the future of the energy sector. One example of technology that is set to benefit from AI’s enhanced automation capabilities is energy storage and grid management.
Battery energy storage systems are essential for enabling renewable power – storing energy for those times when the sun doesn’t shine, and the wind doesn’t blow.
The process of storing and releasing that energy into the grid is a complex process, and automation plays a critical role in managing it effectively.
AI optimising infrastructure
As more industrial facilities develop their own microgrids, the demand for nimble, scalable automation and control systems to run these grids and integrate renewable energy sources will only grow. AI can play a valuable role in optimising this infrastructure, ensuring efficient operation and maximum reliability.
The role of artificial intelligence in shaping the future of industry is clear – not only from a labour perspective but in transforming how we produce, store, distribute and consume energy.
To reduce consumption and optimise efficiency, businesses first need a clear understanding of what energy is being used, and where it is being wasted. Once that foundation is in place, the next step is identifying and implementing the right improvements without disrupting operations.
This process relies on high-quality process data: where that exists, AI has the potential to unlock results more quickly and effectively.
With the rapid advancements in AI over the past few years, the opportunities for businesses in 2025 and beyond are truly exciting.
AI is opening up new ways to drive efficiency, enhance worker productivity, address labour and skills gaps and deliver growth across industries. It is imperative that companies embrace industrial AI now, to avoid being left behind.
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