The US wind industry needs AI now more than ever

The rapid growth of artificial intelligence (AI) in the US is driving increased demand for clean power sources – but wind developers are struggling to build projects fast enough. 

In January, Boston Consulting Group reported electricity demand for US data centers is set to double from 40GW at the end of 2024 to 81GW in 2028. This is forecast to cause US electricity consumption to reach record levels in both 2025 and 2026, according to the US Energy Information Administration’s ‘Short-Term Energy Outlook’ study in April.

The EIA said the US saw flat growth in electricity demand of just 0.1% annually between 2005 and 2020, when higher demand due to economic growth was offset by efficiency improvements and the transition from manufacturing to the service sector.  

It said that US electricity demand is now growing on average 1.7% annually between 2020 and 2026, and that over the next two years electricity use in the commercial sector specifically is set to expand on average 2.6% annually. Data centers are playing a huge role in that. The EIA said this growth was spurring the rollout of renewables generation and energy storage projects in Texas, California, the upper Midwest and the Northeast. 

To help power this growth, the American Clean Power Association (ACP) showed in its 2024 annual statistics that an impressive 49GW of clean power was commissioned in the US last year. This was followed by 7.4GW in the first three months of 2025, as reported by the ACP in its ‘Clean Power Quarterly Market Report’ in May.  

The ACP also reported that there is more than 184GW of clean electricity capacity under construction or in development in the US, led by solar and storage.  

Wind developers have been facing challenges with rising costs, supply chain disruption and permitting delays, but the need to roll out new wind and solar capacity to cope with increased demand from areas including AI remains. This is where AI can help developers overcome some of the challenges they face.

Turbines and technicians 

US wind developers are under strain not just due to recent policy changes and uncertainty. They are also dealing with the side effects of the focus to squeeze as much cost out as possible.  

For example, the pressure on developers to drive down the levelized cost of energy at onshore wind farms forced many to change how they approach wind farm development. Projects are now on average larger than they were a decade ago, over 1GW in some cases, which makes some as complicated as the larger offshore wind developments we see worldwide. 

Turbines are bigger too. The average size of onshore wind turbines used at US onshore projects is now around 3.5MW each, which is up from around 2MW a decade ago. This makes the logistics of producing, transporting, installing and maintaining turbines much more challenging than they were. This is exacerbated at sites with difficult terrain. 

Finally, the US is not immune from a global shortage of technicians.  

A study last year from the National Renewable Energy Laboratory, called ‘National Wind Workforce Assessment: Challenges, Opportunities & Future Needs’, estimated that demand for trained wind energy workers in the US could reach 258,000 by 2030 but that the supply of full-time workers may only reach 134,000, which is around half of what is needed. Developers are finding it hard to access the qualified technicians they need and assess the credibility of different maintenance firms in a fragmented marketplace. 

How AI Helps

This is where AI-powered digital technology helps. Shoreline Wind enables companies in the US wind industry to optimize the design, construction and operations of their wind farms, and is deployed across 465GW of onshore and offshore projects globally. Our system uses AI to underpin advanced simulations and collaboration tools, based on real-time data, that help developers secure the permits their projects need; and mitigate the logistical challenges linked to the use of larger turbines and risks of supply chain disruption. By using agent-based modelling, we enable companies to plan and execute project design, construction and maintenance plans to boost efficiency and make cost savings. 

By using AI to harness insights from a huge range of sources and sharing that across the companies involved in the wind farm delivery process, companies building wind farms can coordinate effectively. 

Developers also rely on Shoreline’s AI in construction to track projects in real time so they can navigate supply chain challenges, cut delays, use technicians’ time efficiently, and optimize execution. This empowers developers to boost efficiency and accelerate deployment in the face of structural challenges in the US and regulatory upheaval.  

In the operational phase, such AI-based tools help support operators manage market difficulties, coordinate with technicians, and ensure their projects are fixed quickly. This increases availability and squeezes more uptime from portfolios. 

For instance, a wind farm owner may use a predictive maintenance system to gather information about the performance of the projects in their portfolio. If this system senses an issue with a particular wind farm, it triggers an alert in the Shoreline system that then automatically creates a defect log, creates a work order to repair the fault, reserve replacement equipment, assigns a technician, and so on. An AI-powered system can quickly and accurately carry out work that would take hours of work for a human being. 

Wind will continue to play an important role in providing the electricity to keep the US at the front of the global race to be an AI superpower. 

AI may be causing the power demand surge but, for wind developers, using AI to speed up their projects can help meet the growing need from data center operators. 

Want to deliver US onshore wind projects faster and smarter? Discover here how Shoreline’s AI-powered software makes it happen.