Security

2024 Tech Trends: Here’s What's in Store for Energy and Utilities Companies

While cybersecurity is as important as ever, energy businesses and utilities will spend 2024 prioritizing renewable options and the technology that supports them.

Joe Kuehne

Joe Kuehne is an Associate Editorial Director at BizTech magazine.

Throughout 2023, cyberattacks remained a persistent threat to the energy and utilities sector, and that trend will likely continue into 2024 and beyond. Cybersecurity must remain a top priority for energy companies and utilities, but they have new weapons at their disposal to protect themselves and their data.

Forbes recently reported, “Ransomware attacks, a persistent threat in recent years, are expected to continue their upward trajectory in 2024. Cybercriminals are likely to target not only corporations, but also critical infrastructure and municipal services. The potential for disruption and financial loss remains significant, necessitating organizations to prioritize robust backup solutions, employee training and vulnerability assessments to mitigate the impact of ransomware.”

The National Infrastructure Protection Plan “provides a risk management framework on how government and private sector participants in the critical infrastructure community collaborate to protect the critical infrastructure and resources essential to the Nation’s security,” according to the Department of Energy. However, the plan hasn’t been updated since 2013, leaving energy companies and utilities open to new vulnerabilities.

As Forcepoint puts it when defining the NIPP, “If the bad guys know where the vulnerabilities are in a critical infrastructure environment, it's not a matter of if you are attacked but when. These threats can come from a number of angles: attacks to legacy systems that are no longer supported and therefore cannot be patched, attacks to systems that are connected to the internet, and phishing attacks that rely on human interaction.”

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Energy Companies Will Enlist AI and ML to Shore Up Cyberdefenses

Fortunately for energy and utility companies, automation offers some new and innovative ways to better protect assets in a shifting threat landscape. Forbes predicts that artificial intelligence and machine learning will play a prominent role in both cyberattacks and cybersecurity in 2024.

“Expect cybercriminals to leverage AI and ML to automate and enhance their capabilities, making attacks more sophisticated and adaptive. Cybersecurity professionals must harness the power of AI themselves to stay one step ahead of these evolving threats,” the article notes. “The rapid advancement of AI presents both opportunities and challenges in cybersecurity, and the same tools that equip attackers with advanced capabilities can also serve useful in cyber defenses. A diligent approach is needed to apply AI effectively in cybersecurity, ensuring it addresses specific problems within the tech stack.”

According to a recent blog post from NVIDIA, the Department of Energy has already implemented some interesting use cases for AI. “In one project, the department developed a tool that uses AI to automate and optimize security vulnerability and patch management in energy delivery systems. Another project for artificial diversity and defense security uses software-defined networks to enhance the situational awareness of energy delivery systems, helping ensure uninterrupted flows of energy.”

The industry is likely to see even more AI use cases as time goes on. “To keep up with an evolving threat landscape and ensure physical security, energy security and data security, public organizations must continue integrating AI to achieve a dynamic, proactive and far-reaching cyber defense posture,” NVIDIA writes.

DISCOVER: Find out how to increase your ransomware recovery capability.

Data Analytics Will Offer Multiple Benefits to the E&U Sector

Beyond cybersecurity, AI and ML are poised to become powerful tools for the industry, according to a recent article from the International Energy Agency.

AI and ML are “uniquely placed to support the simultaneous growth of smart grids and the massive quantities of data they generate,” the agency writes. “Smart meters produce and send several thousand times more data points to utilities than their analogue predecessors. New devices for monitoring grid power flows funnel more than an order of magnitude more data to operators than the technologies they are replacing. And the global fleet of wind turbines is estimated to produce more than 400 billion data points per year. This volume is a key reason energy firms see AI as an increasingly critical resource.”

The IEA predicts, “Potential uses for AI across power systems are likely to soar in the years to come.”

In addition to improved forecasting of energy supply and demand, the agency says AI can be used for predictive maintenance of physical assets, managing and controlling grids, facilitating demand response, and “providing improved or expanded consumer services, using AI or machine learning processes in apps and online chatbots to better customers’ billing experiences.”

Industries Rely on Tech to Meet Demand for Renewable Energy in 2024

Just as 2023 was drawing to a close, the White House published a blog calling for the further development of renewable energy initiatives that will support measures called for in President Biden’s Investing in America agenda.

In its 2024 renewable energy industry outlook, Deloitte notes, “the tandem push of federal investments flowing into clean energy and pull of decarbonization demand from public and private entities have never been stronger. Moving into 2024, these forces could enable renewables to overcome hurdles caused by the seismic shifts needed to meet the country’s climate targets.”

The IEA highlighted AI as a key tool in addressing demand. “One of the most common uses for AI by the energy sector has been to improve predictions of supply and demand. Developing a greater understanding of both when renewable power is available and when it’s needed is crucial for next-generation power systems. Yet this can be complicated for renewable technologies, since the sun doesn’t always shine, and the wind doesn’t always blow. That’s where machine learning can play a role. It can help match variable supply with rising and falling demand.”

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