Exploring artificial intelligence in the legal energy sector

As the world’s legal landscape continues to evolve, so too does the role of artificial intelligence (AI) in the energy sector. AI can revolutionize how legal services are delivered by automating tasks such as contract management and document review and analysis. If you're looking to learn about the potential benefits of using AI in the legal energy sector, its key challenges, common use cases for AI integration, and its future applications — you're in the right place. 

How can AI help the legal energy sector? 

Navigating the complex and rapidly evolving energy sector is becoming increasingly challenging due to its intricate regulatory landscape. Artificial intelligence has emerged as a potential solution in the legal energy sector to address this challenge. By utilizing AI technologies like machine learning and natural-language processing, law firms can help advise clients quicker and with deeper intelligence.

Automation to focus on high-value work 

AI has the potential to revolutionize the way law firms operate in the energy sector. Automating standard processes can remove human error and provide accurate results in a fraction of the time it would take manually. Additionally, AI-powered systems can quickly analyze large sets of data or documents with ease, leaving legal professionals with more time to perform more high-value work.

Superior, strategic decision making 

Integrating AI into existing processes also offers new opportunities for law firms in the energy sector to gain a competitive advantage over their peers. By tracking changes in regulations or policies more efficiently through AI-powered systems, law firms will have access to up-to-date information that can inform strategic decisions in real time.

However, integrating AI into existing processes within the legal energy sector is challenging. As with any new technology, there are data and security risks and concerns about the cost of ownership and scalability when dealing with large datasets or complicated problems. Law firms must weigh these risks against potential rewards when considering integrating AI into their operations.

What are the key challenges of AI in the energy sector? 

When it comes to AI in the legal energy sector, firms must consider certain challenges for successful integration. A couple of common challenges to be aware of include: 

• Ensuring data accuracy and reliability.
• Staying up to date with the ever-changing technology uses and trends.
• Contract documents in the renewable energy sector are unique, and what is important to each one is different than the others.

An easy way to overcome the above challenges is by using technology that guarantees accuracy, reliability, and relevancy. We asked John Gottshall, Renewable Energy Subject Matter Expert at Thomson Reuters, how to overcome the abovementioned challenges. "The right technology allows for quicker and more accurate review of contract documents," Gottshall said. "Document Intelligence uses pre-trained AI models that are built specifically on Renewable Energy documents, which is key to more efficient and effective contract management." 

What are the benefits of using AI in energy practices? 

The legal energy sector stands to benefit greatly from the utilization of artificial intelligence. 

Predictive analytics 

AI-powered automation tools can take over document review and analysis, contract management, and research, freeing up lawyers' time for more high-value activities such as providing strategic advice to their clients. Predictive analytics enabled by machine learning algorithms, natural language processing (NLP) tools, and other capabilities can assist lawyers in anticipating and responding to potential issues quickly.

Summarization assistance 

Additionally, AI-driven document summarization tools can easily and accurately produce summaries of large sets of documents. These tools allow lawyers to access, understand, and advise on the critical information in their client’s governing documents without having to read through each document line by line.