Electricity is no longer merely an operating expense that keeps factories and data centers running. As AI and industrial electrification drive up power demand, the ability to secure and use electricity efficiently has begun to determine companies’ production capacity and investment speed. An era is emerging in which companies that create more products and computing output with the same amount of electricity gain an advantage in cost, carbon, and supply chain competition.

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Since industrialization, the corporate formula for growth has been relatively straightforward. Expanding factories, adding equipment, and increasing inputs of raw materials and energy led to higher output. This model of growth was supported by the belief that electricity would be available whenever it was needed. Companies were more concerned with managing their electricity bills than securing a power supply. Energy efficiency was also treated less as a management strategy than as a secondary activity for reducing costs or protecting the environment.

The power environment surrounding industry is now changing. Future growth industries, including semiconductors, batteries, electric vehicles, robots, automated equipment, and data centers, all require enormous amounts of electricity. Power demand is rising even faster as processes that once directly used fossil fuels are electrified to reduce carbon emissions. With transportation, heating, and industrial thermal energy also moving toward electrification, electricity has become not just one energy source among many but a vital resource supporting the entire industrial transition.

The spread of generative AI makes this transformation even more visible. In the past, data centers were facilities that stored information and provided internet services. In the AI era, however, they resemble enormous computing factories. Countless high-performance chips perform calculations without interruption, consuming vast amounts of electricity and generating intense heat in the process. As AI models grow in scale and usage, not only servers but also power supply and cooling systems must expand with them.

Global electricity consumption by data centers is projected to more than double, from approximately 415 terawatt-hours in 2024 to around 945 terawatt-hours in 2030. At the global level, this may appear manageable, but the problem is that demand is concentrated in particular regions. When large data centers and advanced factories cluster in one location, transmission networks and substations may become insufficient even when total generating capacity is adequate. Delays in completing factories and data centers while they wait for grid connections are no longer unusual.

For companies, failing to receive electricity when it is needed poses a greater risk than an increase in power prices. A factory cannot operate its production equipment without electricity, and a completed data center cannot install enough servers if it lacks sufficient power. In regions where grid connections take years, the right to use electricity itself becomes a scarce industrial resource. The question companies must ask is shifting from “How much will electricity cost?” to “Can we secure the electricity we need reliably?”

This transformation is also changing the meaning of power efficiency. In the past, reducing electricity consumption by 5 percent was calculated simply as an equivalent reduction in electricity costs. Today, saved electricity can be used to operate other equipment or install additional servers. Improving power efficiency does more than cut costs; it also creates additional production capacity.

Suppose a factory can receive 100 units of electricity and its existing production and cooling equipment already consumes all 100 units. Before adding new equipment, the company would first have to expand its power receiving facilities and transformers. If it improves process and cooling efficiency and reduces existing consumption to 85 units, however, the remaining 15 can be used to increase production. The factory can expand its production capacity without building a new power plant or transmission network. The electricity saved effectively functions as a kind of virtual power plant and invisible capacity expansion.

Power efficiency also strengthens a company’s ability to withstand fluctuations in energy prices. A company that uses less electricity to manufacture the same product experiences a relatively smaller cost shock when electricity prices rise. It can also maintain production more reliably when power supplies become unstable and consumption must be adjusted. The cost of responding to stronger carbon regulations and environmental requirements across supply chains is reduced as well.

Efficiency is different from passive conservation that saves energy by reducing production. It is the ability to lower electricity inputs while maintaining the required output and quality, then convert the resulting capacity into new added value. As the assumption that electricity will remain abundant and inexpensive begins to weaken, power efficiency is moving beyond an item managed by environmental departments. It is becoming a management variable that determines the speed of corporate growth and the scope for future investment.

A factory’s electricity consumption does not come only from a handful of enormous production machines. Less visible equipment, including motors, pumps, fans, compressors, chillers, dust collectors, conveyors, and heating, ventilation, and air-conditioning systems, consumes electricity continuously throughout the plant. The consumption of each machine may appear modest, but when hundreds or thousands of units operate for long hours, they account for a substantial share of total power use.

Motor-driven systems lie at the heart of industrial power efficiency. Motors run pumps, move air through fans, operate compressors, and power production lines and material-handling equipment. It is no exaggeration to say that a motor stands behind almost every movement in a factory. Even so, many companies check only a motor’s efficiency rating without closely examining whether the entire system connected to it is operating in line with actual demand.

Installing a high-efficiency motor does not necessarily guarantee electricity savings. Considerable power is wasted when a motor is far larger than required or constantly runs at maximum speed while valves and dampers restrict the resulting flow. Equipment designed for maximum production continues operating at the same speed even under normal conditions. This is little different from keeping a car’s accelerator pressed while using the brakes to control its speed.

Variable-speed drives reduce this waste by adjusting motor speed to process demand. They lower the speed of pumps and fans when production is low and raise their output only when demand increases. For equipment that moves water or air, such as pumps and fans, even a small reduction in rotational speed can significantly reduce the power required. The essence of efficiency is not turning equipment off indiscriminately, but allowing it to operate only as much as necessary.

Compressed air is another major hidden cost. Because it does not generate sparks and is convenient to use, compressed air is employed for cleaning, drying, conveying, and operating tools, among many other tasks. Compressing air, however, requires large amounts of electricity. When air escapes through a small gap in a pipe, the compressor must operate longer to compensate for the loss. The faint sound of leaking air on a production line is not merely noise. It is a sign that electricity is continuously escaping.

Excessive pressure is another problem. If the setting of an entire compressed-air system is raised because one machine lacks sufficient pressure, every piece of connected equipment consumes more electricity. The true cause may be a narrow pipe, clogged filter, leak, or poor equipment layout. Some tasks can be handled adequately by low-pressure blowers, yet high-pressure compressed air is still used out of habit. This is why the entire path through which air is produced, transported, and consumed must be examined before a single machine is replaced.

Chillers and air-conditioning systems may appear to be auxiliary facilities unrelated to production, but they determine product quality and yield. Semiconductor, display, pharmaceutical, fine chemical, and food industries must maintain stable temperature, humidity, and cleanliness. Large amounts of electricity are used to remove heat from production equipment and control the working environment. As cooling loads rise with output, managing cooling equipment separately from production systems makes it difficult to understand overall efficiency properly.

Heat is one of the most frequently wasted resources in industrial facilities. Furnaces, boilers, dryers, compressors, chillers, and servers all release heat. Electricity is used on one side of a facility to remove heat, while fuel is burned again elsewhere to warm water and air. Waste heat can be difficult to use when its temperature is too low or when the times of generation and demand do not align. Even so, combining heat exchangers, heat pumps, and thermal storage systems appropriately can allow a considerable portion of it to be reused for process preheating or space heating.

Old equipment is not the only source of inefficiency. Energy can also be wasted in new factories when attention is focused solely on production volume and initial purchase prices. A company may choose the cheapest pumps and motors, only to bear high electricity costs for decades. The balance of the overall system can also be disrupted when individual departments purchase equipment independently. The purchase price is paid once, but electricity and maintenance costs continue throughout the operating life of the equipment.

Power consumption during production stoppages is also easy to overlook. In many factories, fans and pumps continue running while production equipment remains on standby, and air-conditioning systems operate under the same conditions at night and on weekends as they do on weekdays. As automation expands, the continuous power consumption of controllers, sensors, communications equipment, and power supplies is also increasing. The consumption of each device may be small, but when accumulated across an entire factory, it becomes a baseline load that cannot be ignored.

The problem is that such waste is not visible on an electricity bill alone. Even when a factory’s total power consumption rises, it is difficult to determine whether this resulted from increased production or inefficient equipment operation. To locate where energy is leaking away, companies must measure electricity consumption by production line, process, and major piece of equipment, then examine it alongside output, operating hours, pressure, flow, and temperature.

Industrial efficiency cannot be achieved with a single innovative machine. Significant results emerge when small changes accumulate: repairing compressed-air leaks, adjusting settings, correcting oversized equipment, and matching motor speeds to demand. Equipment efficiency does not depend solely on purchasing machines that consume less electricity. It is determined by the ability to design and operate the entire production system so that it performs the required work with the least possible energy.

Cooling remained in the background of industry for a long time. If production equipment and servers were the main actors, cooling systems were treated as supporting devices that maintained temperatures and prevented equipment failure. As the power density of AI chips rises and manufacturing processes become more precise, however, cooling has emerged as a core technology that determines equipment performance and production capacity.

Equipment powered by electricity releases a substantial portion of its energy input as heat. As servers perform more calculations and semiconductor manufacturing equipment operates with greater precision, the amount of heat generated also increases. If this heat cannot be removed adequately, equipment reduces its own performance or stops operating. Component life is shortened and the likelihood of failure rises. Ultimately, cooling capacity determines how densely high-performance equipment can be installed and how long it can continue operating.

Traditional data centers have relied heavily on air cooling, which supplies cold air to server rooms and collects the heated air. The technology is mature and relatively easy to maintain, but when high-performance AI accelerators are concentrated in one location, air alone struggles to remove the heat. Air has less capacity to carry heat than liquid. Removing large amounts of heat requires rapid circulation of enormous volumes of air, increasing the electricity consumption of fans and chillers accordingly.

This is why direct-to-chip liquid cooling, which places cooling plates directly against heat-generating server components and circulates liquid through them, is attracting attention. Liquid can absorb and transport heat more effectively than air, making it advantageous for maintaining stable temperatures in high-density servers. Immersion cooling, in which servers or major components are submerged in a dielectric cooling fluid, is also emerging as an alternative. Because the fluid absorbs heat directly from components, it can reduce the need for large spaces and powerful fans to generate airflow.

The same cooling method, however, is not suitable for every data center. Direct liquid cooling requires new systems to ensure the reliability of pipes and connectors, detect leaks, and support maintenance. Immersion cooling must address compatibility between the cooling fluid and component materials, equipment replacement procedures, and technical standards. Converting an existing data center may require modifications not only to servers but also to building structures, pipes, racks, and electrical systems. Choosing a technology solely for its cooling performance can create unexpected operating and conversion costs.

Water consumption is another important consideration. Evaporative cooling, which removes heat as water evaporates, can lower electricity consumption but requires large quantities of water. In regions with water shortages or a high risk of drought, increasing the burden on local water supplies to improve power efficiency can create conflict with surrounding communities. Dry cooling, which minimizes water use, may consume more electricity during hot weather. Cooling technology must therefore be selected by considering not only electricity but also climate, water availability, power prices, and carbon emissions.

This is also why cooling efficiency cannot easily be judged by a single number. The share of a data center’s total electricity that is actually delivered to servers and storage devices is an important metric, but it does not reveal water consumption, server utilization, or the carbon intensity of electricity. Even if cooling power is reduced, it is difficult to claim that overall resource efficiency has improved when water use rises sharply or servers are not used sufficiently.

The belief that keeping temperatures as low as possible ensures safe operation also needs to be reconsidered. Setting temperatures far below the level actually required causes chillers to consume more electricity. Cooling effectiveness also declines when cold and hot air mix inside a server room. Separating the paths of cold and hot air and adjusting temperatures within the range permitted by equipment can reduce cooling loads without large-scale replacement.

Using heat that would otherwise be discarded during cooling can transform a cost into a new resource. Heat recovered from data centers and industrial chillers is generally too low in temperature to be used directly in high-temperature processes, but it can be applied to heating and hot-water systems in nearby buildings, agricultural facilities, fish farms, and low-temperature industrial processes. Heat pumps can raise its temperature and broaden the range of applications. Commercial viability depends on whether a suitable facility is located nearby and whether the timing of heat demand aligns with the timing of waste heat generation.

Factories must also move away from the practice of managing cooling and heating as separate systems. If a chiller releases removed heat outdoors while a boiler heats water for another process, there may be an opportunity to connect the two systems. Designing production processes, cooling, waste heat recovery, heat pumps, and thermal storage as a single thermal energy system can reduce both electricity and fuel consumption.

Competition in cooling in the AI era is not simply a technological contest to lower server temperatures. It is a comprehensive systems competition to handle higher power density while reducing electricity and water consumption, preserving equipment performance and service life, and even utilizing discarded heat. No matter how far semiconductor performance advances, actual computing capacity cannot be used fully if the resulting heat cannot be managed. Cooling has become not supporting infrastructure for advanced industries, but a technology that sets the upper limit of their growth.

One of the greatest difficulties in improving power efficiency is that energy consumption is invisible. Raw materials are stacked in warehouses and finished goods are counted as output, but electricity flows through wires and disappears the instant it is consumed. A monthly electricity bill shows how much power the entire factory used, but it does not reveal which equipment caused waste or why.

Smart metering and sensors make previously invisible energy flows visible. Installing power meters, thermometers, pressure gauges, flow meters, and vibration sensors on major equipment makes it possible to monitor energy consumption and equipment condition simultaneously. When these data are combined with output, quality, utilization rates, outdoor temperature, and electricity prices, companies can analyze not only how much consumption changed but also why it changed.

Even if a production line’s electricity use rises by 10 percent from the previous month, the amount of electricity required to manufacture each product has actually fallen if output increases by 15 percent. Conversely, if total consumption remains similar while production declines, efficiency has probably deteriorated. This is why companies must measure the electricity needed to produce one item, generate one won in revenue, or complete one computation rather than focusing only on total power consumption.

Equipment abnormalities may also appear first in energy data. If the electricity consumption and vibration of a normally operating motor gradually increase, bearing wear or shaft misalignment may be the cause. If a chiller’s efficiency continues to decline under the same weather and operating conditions, the heat exchanger may be contaminated or the refrigerant system may have a problem. Shifting from repairing machinery after failure to detecting and servicing early signs of performance deterioration can reduce both power waste and production stoppages.

A digital twin recreates an actual factory or data center in a virtual environment and tests different operating conditions. It can analyze how electricity consumption, output, and quality would change when equipment speed, temperature, pressure, or production plans are adjusted, without stopping the actual process. It can also examine in advance how server performance and power consumption would change if cooling temperatures were raised, or which combination of multiple chillers would operate most efficiently.

AI identifies optimal operating conditions among countless variables that would be difficult for people to calculate individually. By analyzing production schedules, outdoor temperatures, electricity prices, and equipment conditions, it can recommend the operating conditions that minimize power consumption. In data centers, AI can predict server loads and temperature distributions, adjust the output of fans and cooling systems, and move non-urgent computing tasks to times when power is more readily available or carbon emissions are lower.

Introducing AI, however, does not automatically improve efficiency. If sensor readings are inaccurate or equipment information is poorly organized, AI may make sophisticated misjudgments based on faulty data. Analytical reliability also declines when electricity and production data use different time intervals or when equipment names and locations do not match. The basic work of organizing on-site metering systems, data standards, and equipment inventories must come first.

Cooperation among production, facilities, and information technology departments is also essential. Production departments prioritize quality and delivery schedules, while facilities departments emphasize stable supplies of electricity and cooling. Information technology departments are responsible for system stability and security. If each department optimizes only its own objectives, the factory as a whole may become less efficient. Typical examples include operating equipment excessively out of concern over production disruptions or providing more cooling than necessary out of fear of equipment failure.

Efficiency targets should not be defined simply as reductions in consumption. Requiring a uniform decrease in electricity use can create side effects, such as lowering output or reducing essential ventilation and cooling. Power efficiency must be evaluated alongside output, quality, safety, and equipment utilization. Even if electricity consumption falls, total factory energy use may actually rise when higher defect rates lead to more rework.

The timing of electricity use is also becoming increasingly important. When every piece of equipment operates simultaneously during periods of high power demand, peak demand rises and places a greater burden on the grid. Adjusting production schedules, chiller operation, battery charging, and thermal storage can lower peak demand while maintaining output. Storing electricity or cooling energy when power prices are low and using it when needed can reduce both costs and grid pressure.

The goal of integrated optimization is not to achieve the highest efficiency for a single machine. Even if one motor operates at its most efficient speed, bottlenecks and waiting time in the next process may reduce the efficiency of the entire factory. Improving the efficiency of one chiller may increase the burden on another. Individual machines, production processes, electricity supply, cooling, and production planning must be treated as one system so that total costs and energy consumption can be reduced.

Data transforms efficiency improvement from a one-time project into a lasting operational capability. New equipment may show high efficiency immediately after installation, but settings change, parts wear out, and production conditions shift over time. Performance must be measured continuously and deviations from standards identified if improvements are to be sustained. Power efficiency is not a target achieved once and then forgotten. Like productivity and quality, it is a metric that must be managed every day.

The most common reason companies postpone investment in high-efficiency equipment is the initial cost. Replacing existing equipment that still functions with more expensive machinery increases immediate capital expenditure. If only electricity bill savings are considered, the payback period may also appear long. Evaluating the economics of efficiency solely through electricity costs, however, causes companies to overlook its true value.

Equipment economics must be assessed through total cost of ownership, including purchase price, electricity expenses, maintenance costs, service life, failure risk, productivity, and quality. For equipment that operates for long periods, such as pumps, motors, and chillers, lifetime energy expenses can greatly exceed the original purchase price. Cheap but inefficient machinery may appear to save money at the moment of purchase, but it generates higher electricity bills every month thereafter.

Efficiency improvements also affect productivity. Reducing equipment heat and vibration can extend component life and decrease breakdowns and downtime. Stable cooling and temperature and humidity control can reduce defect rates and rework. When compressed air, steam, and cooling water are supplied reliably under the required conditions, fluctuations in production processes also decline. Improvements in power efficiency therefore extend beyond energy expenses to yield, delivery performance, and quality competitiveness.

The ability to reduce investment in power infrastructure must also be included in the calculation. Expanding a factory may require larger transformers and power receiving facilities, as well as a new grid connection. If greater efficiency in existing equipment creates spare power capacity, these investments can be delayed or reduced. In a data center, servers can be added using the capacity released by reducing cooling power. Saved electricity effectively becomes a productive asset that generates new revenue.

Carbon emissions are also gradually becoming a real cost. The more a company’s electricity is generated from fossil fuels, the greater the indirect emissions associated with its power consumption. As carbon prices, emissions allowance costs, and renewable energy procurement expenses rise, inefficient companies bear higher costs to produce the same products. Reducing electricity consumption is the most direct way to lower indirect emissions.

Supply chain requirements are also changing. Global corporations are seeking to manage not only emissions from their own operations but also those generated through raw materials, components, transportation, and product use. They are increasingly asking suppliers to disclose energy consumption and carbon emissions and incorporating reduction performance into purchasing requirements. When prices and quality are comparable, suppliers with higher power efficiency are more likely to be selected.

Accurate measurement and verification are becoming even more important. Simply dividing a factory’s total electricity use by output cannot precisely calculate efficiency and carbon emissions for each product. Different products may use the same equipment, while shared facilities such as cooling and compressed-air systems support several production lines. Product-level figures vary depending on how shared energy is allocated and how utilization rates and seasonal changes are reflected.

The same principle applies to data centers. Low losses during cooling and power conversion do not necessarily indicate high overall efficiency. Even when facility efficiency is excellent, a low server utilization rate can mean that a large amount of electricity is consumed for each actual computation. Conversely, even if facility metrics are somewhat less favorable, resource productivity may be higher when servers maintain high utilization and process more useful computing tasks. Facility, server, software, and computational efficiency must all be assessed together.

Power efficiency is a particularly important challenge for Korean industry because energy- and electricity-intensive sectors such as semiconductors, displays, steel, petrochemicals, and batteries account for a large share of the economy. Major production facilities and data centers are concentrated in the Seoul metropolitan area and a limited number of industrial complexes. As a result, new investment may be delayed by insufficient regional transmission capacity even when the country’s total electricity generation is adequate. If advanced manufacturing facilities and AI data centers expand simultaneously, competition for electricity in individual regions could become even more intense.

Small and medium-sized enterprises can easily miss opportunities for efficiency improvements because of aging equipment, limited investment capacity, and shortages of specialized personnel. Electricity bills may represent a large share of costs, yet many companies lack the metering systems needed to determine which equipment consumes how much power. A framework is required that goes beyond simple support for equipment replacement and connects energy audits, investment financing, operational improvements, and verification of savings.

Within companies, power efficiency should not be left solely to facilities management teams. Senior executives must consider not only the output and return on investment of new equipment but also its required power and cooling capacity, water consumption, carbon costs, and prospects for grid connection. When selecting locations for factories and data centers, long-term supply stability and the potential for regional grid expansion are becoming more important than current electricity prices.

Efficiency improvements can begin with measurement and operational adjustments. Companies should first measure power flows, identify where waste occurs, and adjust operating hours and settings. They can then repair leaks and improve insulation, introduce variable-speed drives and control systems, and install waste heat recovery equipment. Machinery that has reached the end of its life or is structurally inefficient can be replaced with high-efficiency equipment. Rather than replacing everything at once, it is more practical to proceed in stages, beginning with areas that offer the greatest savings and productivity gains relative to investment.

When selecting equipment, companies must consider not only current electricity prices but also future production methods. Production equipment remains in use for a long time once installed, and factory structures cannot easily be changed. New machinery should be evaluated for whether it can adjust output to power demand, recover waste heat, and integrate with renewable energy and storage systems. A decision that lowers the immediate purchase price should not lead to high operating expenses over many years.

Industrial competitiveness will no longer be judged solely by how much a company produces. The amount of electricity, water, raw materials, and carbon required to manufacture the same product will determine both costs and access to markets. Efficient factories experience smaller shocks when energy prices rise and maintain more output when power supplies are constrained. They can also respond to carbon regulations and supply chain reduction requirements at a lower cost.

Adjusting motor speeds, repairing compressed-air leaks, and optimizing cooling temperatures do not look like glamorous new businesses. When such improvements accumulate across factories and data centers, however, they create capacity comparable to securing new power generation facilities. Small efficiency gains become the foundation for expanding production capacity, accelerating investment, and lowering carbon costs.

The standard of industrial competition is shifting from securing more electricity to creating more value with the electricity already secured. Power efficiency is a strategy that can reduce costs and carbon emissions while expanding production capacity at the same time. This is also why cooling and energy management are moving out from behind the equipment and into the center of corporate management. Power efficiency is no longer a technology for simply using less electricity. It is an industrial capability for producing more reliably and sustaining growth for longer.

International Energy Agency, April 2026, Key Questions on Energy and AI

International Energy Agency, November 2025, Energy Efficiency 2025

International Energy Agency, April 2025, Energy and AI

European Commission, July 2025, Assessment of the Energy Performance and Sustainability of Data Centres in the EU

ASHRAE, August 2024, ASHRAE Launches Comprehensive Data Center Resources Hub

US Department of Energy, February 2014, Improving Motor and Drive System Performance: A Sourcebook for Industry