Large Language Models (LLMs) are a driving force for innovation as they are tools that can contribute to greater efficiency and productivity. Knowing about LLMs and the value they can bring to an organisation is essential to keep up with the ever-changing market and its demands. In this blog post, you will learn more about the potential of LLMs to streamline processes and add real value to your organisation.    

What are Large Language Models (LLMs)? 

Large Language Models (LLMs for short) are AI models that have been trained on huge amounts of data, enabling them to fulfil various tasks. Some examples of popular LLMs are ChatGPT from OpenAI, Gemini from Google and Llama from Meta. Companies use these LLMs for content creation, marketing and other valuable applications.

Thanks to their human-like text generation, large language models improve technological efficiency in companies and are used in a wide range of applications in the business world.

An Introduction to Large Language Models

Use cases for large language models

Large Language Models (LLMs) have different applications for different business cases. It is worth evaluating how you can best utilise LLMs for your company. That's why we've compiled a list of seven business use cases of LLMs from different industries. In this section, we will explore each of these applications and understand how they add value to an organisation:

• Cybersecurity: Cybersecurity is one of the top three challenges facing CEOs today. Large Language Models can help mitigate this challenge by providing valuable insights from massive cybersecurity data. LLM-powered data insights enable better anticipation, identification and response to likely security threats. Threat detection and data generation from LLM advancements improve cybersecurity. This contributes to strengthening the overall security posture of organisations. 
• Training and further education: Large Language Models are immensely useful in providing personalised education and training tailored to the needs of learners. LLMs can serve as supplementary educational material that students can use for tutoring sessions to find simple explanations for complex topics and test their knowledge. The pedagogical capabilities of LLMs provide social value by encouraging collaborative learning. Large Language Models also have the potential to provide fun learning experiences that can be engaging for learners. 
• Analysing customer sentiment (sentiment analysis): Large Language Models are trained on textual and linguistic sentiments to better understand and respond to customer enquiries. The functions of GPT-4 and BERT for sentiment analysis outperform conventional methods by recognising subtle emotions and contexts. LLMs can also analyse customer data such as feedback, complaints, reviews and social media comments to determine public perception of the brand. This has proven beneficial for various applications, such as market research, political strategy and brand monitoring. 
• Content creation: The extensive Training data and the Language comprehension of Large Language Models can generate high-quality content based on user prompts. This serves as a productive additional tool for employees. This business application allows companies to use LLMs for dialogue creation, storytelling or content enhancement. LLMs can also extract useful information from long documents and summarise them efficiently and effectively. 
• Search functions: Large Language Models provide relevant information by improving the quality of search results. Users around the world are already benefiting from the search engines offered by Google and Bing, and they are using LLMs for better search results. LLMs have improved the search results experience as search engines can now deliver personalised results by understanding the user's intent. This search experience is novel for users as they don't have to go through all the search results; the LLM uses summary chains to analyse hundreds of search results and provide users with much denser results to their queries. 
• Research and analysis: Large Language Models can help in developing a content strategy and launching new products by supporting research efforts. They are extremely helpful when it comes to capturing important keywords in the data and creating a comprehensive analysis. This can prove beneficial when it comes to improving market research efforts and accelerating innovation. In addition, LLMs can help analyse open survey results to understand customer satisfaction and areas for improvement. 
• Gaining knowledge from data: Large Language Models have proven to be helpful in gaining insights from large amounts of unstructured data. LLMs can collect unstructured data from social media posts, customer feedback and complaints. The models can understand customer behaviour, sentiment and preferences by extracting relevant information from the unstructured data. 

Large language models are transforming interaction with technology and expanding its application from content creation to customer service. Our overview presents 14 relevant representatives in detail:

The 14 Top Large Language Models: A Comprehensive Guide

The added value of LLMs for companies

In the previous section, we discussed the use cases of Large Language Models (LLMs) and how the applications create added value for companies. Organisations can benefit from using LLMs in their specific automation and process strategy. We have compiled a list of three main reasons why organisations should use LLMs:

1. Transformational value: Large Language Models offer companies transformative value that helps them stay ahead of the competition. This wave of innovation is driven by automation, improved workflows and risk management capabilities that LLMs possess. 
2. Increasing efficiency: Large Language Models play a crucial role in increasing employee efficiency, organisational innovation and improving the customer experience. LLMs relieve employees of repetitive tasks, freeing up more time for strategic work. Organisations can make more strategic decisions by using the data insights generated by LLMs. Large Language Models also support Chatbotswho are available around the clock for customer support, especially when employees are not on duty. 
3. Rationalisation of processes: Large Language Models streamline a company's workflows, which ultimately leads to a satisfying customer experience. LLMs help to personalise customer interactions by analysing their past behaviour and identifying their preferences. Companies can use this data to make targeted product recommendations. 

Examples of the successful use of LLMs

• Healthcare: Large Language Models are transforming healthcare by helping with medical diagnosis by analysing patient symptoms, medical histories and clinical data. LLMs also facilitate the review of medical literature as they are able to analyse huge amounts of scientific material. In addition, Large Language Models provide therapy recommendations by finding patterns in genetic data, medical reports and electronic health records. 
• Finance and insurance: Large Language Models help financial organisations detect and prevent fraud by identifying anomalies, detecting fraudulent trends and alerting officials by using algorithms to process natural language and to the machine learning use. LLMs can also analyse financial data from sources such as news, articles and reports to help traders make better financial decisions. In addition, LLMs help banks assess risk more efficiently by analysing large amounts of consumer data. 
• Retail and e-commerce: Large Language Models enable global companies to overcome language barriers by providing a localised customer experience thanks to their real-time translation capabilities. LLMs help localise websites and software for foreign markets. LLM-based translations speed up the process of translating menus, product descriptions and other text content and ensure that they are linguistically and culturally appropriate. In this way, Large Language Models contribute to an improved user experience. 

Find out all about foundation models and how they can be used effectively in companies to give you a competitive edge and accelerate business processes in our basic article.

An Introduction to Foundation Models

Wide range of use cases for large language models

Although still in the development phase, LLMs have revolutionised the business world across industries and are contributing to economic gains for companies and countries alike. Their use cases in various prominent areas such as healthcare, cybersecurity and legal have a direct impact on improving the human experience, and organisations are leaving no stone unturned to make the most of this technology and improve the customer experience. Organisations around the world have more reasons to continue using this technology and plan to diversify their applications due to its paramount importance and inevitable need in the future. Therefore, organisations that are still hesitant to adopt LLM for business applications must seize the opportunity before it is too late.