Artificial intelligence and robotics are two of the world’s latest, most influential technologies. Could suppliers, transporters and providers in the energy industry use them to combat rising costs and make fuel more affordable?
Fuel Costs Have Been Hitting Record-Breaking Highs
Fuel expenses have been rising erratically in recent years, and everyone from suppliers to consumers has felt the squeeze. On average, fossil fuels reached $5.22 per metric million British thermal units in 2022 — a 36.6% year-over-year increase. Out of all types, petroleum had the most significant price jump, rising 64% in just one year.
These increases have an unpleasant trickle-down effect. Rising fuel prices impact shippers’ operational expenses, which usually forces them to charge consumers more. People often pay more at the pump for something entirely out of their control. Unfortunately, this has been happening more often than not lately.
Several recent supply chain disruptions have made reliable sources scarce. For instance, Russia used to be the third-highest coal exporter, the second-highest natural gas producer and the third-highest crude oil producer before its invasion of Ukraine prompted countries to impose sanctions and look elsewhere for nonrenewables.
Many countries have tried to combat these rising expenses traditionally. According to the International Energy Agency, consumption subsidies — government grants, loans or tax incentives meant to lower prices — for oil, natural gas, electricity and coal topped a record high of $1.09 trillion in 2022. This figure is more than double its 2021 level of $531 billion.
However, those subsidies haven’t kept prices low. On top of managing supply chain disruptions, many in the oil and gas industry are trying to recover the revenue they lost during the COVID-19 pandemic. The labor cost has been increasing in many sectors, further complicating things. Realistically, the world needs modern, unconventional solutions to tackle this complex issue.
Ways Robots Can Address Rising Fuel Prices
There are several ways suppliers, distributors and retailers in the energy industry can use robotics to address rising prices.
1. Work Alongside Oil and Gas Workers
Collaborative robots — better known as cobots — work alongside people. They’re usually smaller, safer versions of the industrial-grade machines commonly found in manufacturing plants. This technology can speed up production and reduce companies’ reliance on manual labor, ultimately increasing supply and lowering price tags.
2. Scope Out and Maintain Sites
Drones can fly over oil, natural gas or wind farm sites to evaluate them. They can use cutting-edge sensors and computer vision technology — a type of AI that lets computers interpret images or videos — to produce a three-dimensional model of the area. This way, decision-makers can develop foolproof construction strategies.
Mobile robots can help maintain sites by carrying out inspections or repairs. An operator can remotely control them from a distance using a controller, tether and live video feed. Alternatively, autonomous AI-powered machines can perform routine maintenance tasks without human intervention. Lowering labor and accident-related expenses would bring fuel prices down.
Ways AI Can Address Rising Fuel Prices
AI is one of the most powerful technologies, so using it to lower costs and prevent future price surges makes sense. There are numerous ways it can address this issue.
1. Automate Wells, Drills and Rigs
Automation is one of AI’s most powerful features. It can perform day-to-day functions independently since it controls itself instead of relying on human intervention or supervision. Reducing labor and accident-related expenses makes production cheaper, allowing firms to pass their savings to consumers.
2. Drive Energy Decisions With Data
An advanced machine learning (ML) model can process massive datasets — meaning dozens of documents, images or spreadsheets — in seconds. Since it is fast and accurate, it’s the ideal tool for guiding decision-making. Energy industry leaders can use it to decide how to optimize extraction, refinement and distribution.
For example, someone could use ML to analyze hundreds of past geological surveys to predict the next best reservoir for natural gas extraction, saving time on-site selection and money on expensive modeling software. Alternatively, they could use it to adjust commercial vehicles’ routes to reduce gas consumption. All these improvements result in downstream savings.
3. Improve Consumers’ Energy Efficiency
AI can analyze robot- and sensor-generated data like temperature, heat loss, occupancy and electricity usage to tweak a building’s heating, cooling and lighting systems. For example, it could lower the thermostat temperature when the homeowners aren’t home. Consistently reducing power consumption can significantly lower electricity bills.
Using Modern Technology for Alternative Energy Sources
While much of the world is focused on how modern technologies can support the oil and gas industry, there’s a huge untapped market for solutions like wind, solar, hydroelectric and geothermal. AI and robotics are driving prices down for alternative power sources, fueling the transition to clean electricity.
These sources are already comparatively cheap. According to the International Renewable Energy Agency, 86% of the renewable energy capacity — 187 gigawatts, to be exact — was cheaper than nonrenewables in 2022. However, further lowering price tags can help countries shift toward alternatives. Since fuel consumption is on the rise — new energy demand in North America doubled from 2022 to 2023 — adopting a renewable-focused approach could prevent countries from putting all of their eggs in one basket, so to speak.
Transitioning to renewables may not seem like a big deal, but it matters. Diversification was a large part of why events like the Russia-Ukraine war didn’t cause a massive energy crisis — many countries had cleaner, cheaper electricity sources they relied on until they found a long-term solution. In other words, lowering expenses can make the world resilient against price surges.
How AI and Robotics Can Make Renewables Affordable
AI and robotics can make renewable energy more accessible and affordable.
1. Facilitate Peer-to-Peer Energy Trading
The concept of peer-to-peer power trading sounds complex but is actually simple. People who use solar panels and batteries to capture and store electricity from the sun can sell their excess or buy some extra on an as-necessary basis. AI and robotics can facilitate this process by optimizing consumption and tracking market demand.
For example, homeowners could use a chatbot to navigate the market while deploying a panel-cleaning robot to maximize capture. This concept sounds futuristic, but it is already happening. For instance, the peer-to-peer charging market was worth $35.5 million in 2021 and is expected to grow at a compound annual growth rate of 22.3% through 2030.
2. Support Energy Industry Technicians
Solar panel farms and offshore structures like wind turbines need regular inspections and repairs to keep operating effectively. Usually, technicians have to scale dizzying heights or dive to shadowy depths to perform maintenance. On top of being expensive and time-consuming, this work is dangerous.
AI-powered robots can take their place, reducing labor and injury-related expenses. One uncrewed underwater robot is doing just that — it dives, crawls and climbs to check if the anti-corrosion paint is flaking off or the seam welds are cracking. It weighs only 48.5 pounds, so it can even be moved manually instead of via crane.
Considerations for Those Deploying These Technologies
While AI and robotics are promising tools to help suppliers and providers lower fuel costs, there is a catch — these technologies can be immensely resource-intensive. Robots and ML models often have to communicate with servers or other systems to exchange data and function properly, which drives data center construction.
A data center is a building that houses computer systems, servers and data storage systems. It’s easily one of the most resource-intensive building types. Compared to a standard office building, it consumes 10 to 50 times more electricity per floor space. Unfortunately, AI and advanced robots need one for training and operation.
There’s the issue of security, which, realistically, is also a safety concern. If hackers attack an ML model or cobot, they can cause unintended behaviors or equipment damage. At best, enterprises have to spend weeks recovering from the breach. At worst, a hacked system injures or even kills someone.
How to Resolve Pain Points to Ensure Success
Addressing concerns will take time, but it is doable. For instance, businesses can leverage efficient motors or controllers to reduce robots’ fuel consumption significantly, reducing operating expenses and improving equipment life span. The gains may seem small, but they add up with each machine optimized.
For AI, companies can use servers in specific locations at certain times when demand is low and the electricity supply is plentiful. This strategy reduces their power consumption and lowers their greenhouse gas emissions by anywhere from 20%-80% during training. Unconventional solutions like this require strategic coordination but are manageable with the right team.
Securing AI and robotics against cyberattacks is more complex because what hackers target differs depending on the industry, facility and system type. To be safe, decision-makers should leverage best practices like using strong passwords, deploying network defenses and mandating authentication measures.
How Long Will It Take for Fuel Costs to Go Down?
Since supply chain disruptions, geopolitical conflicts and demand fluctuations can all affect fuel costs, there’s no telling when prices will return to normal. However, if suppliers, distributors and providers strategically implement AI and robotic-driven solutions, they’ll likely drop much faster.
