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Agentic AI and robotics represent one of the most innovative opportunities to improve efficiency in modern manufacturing. But as automation expands, questions arise that may not be on the minds of manufacturers. The question is, how much will the energy cost be?
According to recent information, PwC survey81% of executives plan to increase investment in artificial intelligence over the next three years, and 93% believe that America’s industrial advantage will be built on intelligent systems. Additionally, 46% of energy and industry professionals report that their companies: Investing in renewable energy generation and storageapproximately one-third expect to achieve energy independence by 2030.
Meanwhile, agent AI and robotics are becoming safer, smarter, and more affordable. This comes as the manufacturing workforce faces talent shortages exacerbated by an aging labor pool and loss of organizational knowledge.
For companies in the early stages of AI and robotics adoption, energy costs can seem almost negligible.
Agility Robotics, which deploys its humanoid robot Digit for customers including Amazon, GXO and Toyota Motor Manufacturing Canada, estimates that electricity costs about $1 per shift.
“The real complexity in physical automation isn’t power; it’s integrated into real-world workflows, safety systems, and field operations,” co-founder and chief robotics officer Jonathan Hurst said in an email.
This framework will resonate with manufacturers new to automation. But companies looking to rapidly scale up agent AI and robotics may need to consider another reality: increased energy usage.
“As we scale up and these factors become a larger part of production, that amount can increase significantly,” said Jackie Bacalarski, a principal focused on sustainability and ESG at Avetta.
Bakalarski recommends that you carefully consider whether the lower energy numbers still apply, given your specific considerations.
“If you normalize the costs of infrastructure, buildings, running your own small power plant, etc. It will probably add up to a dollar or more per shift over time. ”
Energy is no longer linear with power
Perhaps the most important insight for manufacturers is that the traditional relationship between energy consumption and output is fundamentally changing.
There was a time when energy increased along with productivity. According to Bakalaski, that may no longer be the case.
“In the past, energy demand was largely reflected in production,” she says. “Those circumstances are now changing to some extent, so production could increase significantly while energy demand will probably increase only slightly.”
This decoupling is one reason why some find agent AI to be an attractive option for manufacturers.
“My personal goal is to increase employee productivity by at least 30%,” said Anoop Mohan, chief product and technology officer at Augury. “If we can do that, that to me is the role of what I call an AI agent.”
Augury’s Mohan describes a world where AI agents continuously collaborate with reliability engineers, maintenance teams, and operations staff. These agents interpret sensor data, flag potential failures before they occur, and recommend actions in real-time. The result is less unplanned downtime, smoother production, and greater energy efficiency. A machine running at optimal performance uses less power than a machine running in a degraded state awaiting repair.
Plan power as parallel orbits
Where companies are failing, Bakalaski said, is by not planning for energy infrastructure in tandem with changes in production.
“If you’re planning to change your production and you’re adding robotics or doing something like creating a larger pool of energy, you need to plan for energy.”
Automakers have historically led the field by digitally modeling production environments, including energy load sequences, before making changes to the factory floor. As the AI industry evolves, manufacturing companies are increasingly competing with data centers for energy resources, says a report. Recent AlphaStruxure research. Risks posed by resource constraints include energy shortages and delays in opening new sites if energy is not available to support the facility.
Another factor is the promise of alternative energy sources.
a Recent Deloitte energy and industry The report focused on a wide range of areas including cleantech manufacturing, data centers and AI, and said that “renewable energy is competing with other clean power generation options to fill the resource gap.” A possible benefit of renewable energy is that it may increase overall energy availability and ultimately reduce costs.
With all these factors in mind, experts say the manufacturers best positioned to realize the full productivity promise of agentic AI and robotics are those that treat energy as a core input in their investment decisions from day one, rather than as an afterthought.
