It is time to automate your BI systems and make them more accessible to non-technical users across the organization. Here, we’ll discuss how large language models (LLMs) can aid your business intelligence (BI) investments and increase ROI.
Business intelligence helps enterprises transform their raw data into actionable insights through a series of tools, technologies, strategies, and processes. It helps employees and executives make data-driven decisions and gain a competitive edge. According to Business Research Insights, the global BI market is $30.72 billion in 2025 and expected to reach $50.66 billion by 2034 at a CAGR (compound annual growth rate) of 5.72%.
More statistics show that 67% of organizations will have adopted business intelligence by 2025, while 91% of enterprises have plans to increase their BI investments. These reports clearly indicate that business intelligence is becoming a part of most organizations. Now, traditional BI includes various manual processes that are time-consuming and stressful. Data analysts and BI experts must provide insights requested by employees from across the organization, handling all the necessary work.
However, thanks to artificial intelligence, you can automate and streamline various BI processes to save time and increase efficiency. For example, using LLMs for Power BI can empower the platform and your employees to deliver better outcomes.
In this blog, we’ll read about how large language models (LLMs) can be integrated with your BI systems and what benefits you can achieve from this integration.
What are Large Language Models (LLMs)?
Large language models (LLMs) are a type of AI and ML program that are trained on large datasets to recognize and generate text based on user input. The LLMs use a type of machine learning called deep learning to understand unstructured data (words, text, characters, sentences, etc.) and recognize patterns, distinctions, etc., without human intervention. The models are further trained and fine-tuned to suit the specific requirements of different businesses. This is done by training the LLMs on proprietary data to ensure the results are more relevant, accurate, and aligned with the outcomes you want.
Typically, large language model development is done for various reasons or tasks. You can hire an LLM development company to build, deploy, customize, and integrate the model as per your requirements. Some use cases of LLMs are as follows:
- Text generation
- Summarization
- Sentiment analysis
- Chatbots
- Online search and research
- Customer service, etc.
GPT-3, GPT-4, BERT, LLaMA, etc., are some examples of large language models.
GenerativeAI vs. LLMs
Though the terms generative AI and LLMs are used in similar contexts and even interchangeably at times, they are not the same. As the name suggests, generative AI generates content (text, audio, video, images, etc.). LLMs are limited to the text generation process of GenAI model development, though here ‘text’ can also include programming code, biological sequences, etc. Simply put, LLMs are a type of generative AI, but not every genAI model is an LLM.
From BI to AI: Using LLMs in Business Intelligence
LLMs have diverse use cases already, depending on how you want to integrate them into your existing systems. Empowering business intelligence is one of the important applications of large language models in today’s world, where data and insights play a crucial role in business growth and expansion. LLM consulting companies offer tailored solutions to fine-tune the models with business data and integrate them with your existing BI platforms like Power BI. This makes the BI platform more powerful, scalable, and flexible. It provides insights quickly and reduces technical complexity for the end users.
For example, using an AI chatbot in BI (Power BI has an AI chatbot capability through its Copilot integration) changes how employees interact with the platform. Instead of sending queries in SQL and using highly technical processes, employees can input their queries in English or other human languages. LLM integration enables the BI platform to read and understand the input, providing relevant insights. Even the insights can be simplified and summarized for employees to easily grasp the key points and make a decision quickly.
Similarly, there are many applications of large language models (LLMs) in business intelligence development.
Application of LLM in BI Development
LLMs nowadays have a vital role in an organization’s Power BI journey. They can offer robust data analytics, business intelligence, and reporting capabilities, which can be refined for greater accuracy and relevance as you continue to use the systems for data-driven decision-making. LLMs can be used in BI development in the following ways:
Sentiment and Customer Behavior Analysis
Customer behavior and feedback are critical for any business to ensure that its products and services are aligned with the market demands. Traditionally, enterprises used manual interpretation methods, which had a greater risk of error or misunderstanding. However, with large language model consulting for business intelligence, you can not only automate processes to save time but also minimize human error. This allows you to make swift decisions and keep your customers happy and satisfied with your offerings.
Data Preparation and Modeling
Large language models are good at data preparation and modelling, especially when dealing with massive datasets. Since both these steps are crucial in the business intelligence process, they can be streamlined and automated to optimize resources, save time, and reduce workload on employees. Moreover, LLMs are trained to study datasets to identify patterns, trends, and correlations that humans may not see immediately due to the extensive range of data that has to be analyzed. This makes it easier to identify variables, trace relationships, etc.
Interactive and Conversational BI
Business intelligence tools like Power BI have interactive dashboards that create graphical data visualizations in real-time. However, understanding complex reports requires technical knowledge. Enabling Power BI dashboard integration with LLM-powered chatbots bridges the gap. You can convert the dashboard into a conversational interface where the chatbot summarizes or simplifies the reports for non-technical users. This reduces the risk of misinterpretation and makes BI reports accessible to more employees across the organization. The chatbots are trained to understand the context and semantics when providing information to the users.
Scaling Insights Seamlessly
Businesses don’t have the same needs throughout. As your transactions increase, your data grows, and the workflow gets complicated. This means you should scale the systems accordingly to avoid delays, etc. Even the business intelligence processes have to be scaled to handle more data effectively and derive insights in a quick time. LLM integration is the best way to manage this change. Large language models are built for scalability and work better on a larger scale. There’s no need to hire more teams to handle the workload. LLMs can manage it as long as you have the necessary systems in place.
Querying in Natural Languages
Querying in business intelligence is not an easy task. It requires knowledge of SQL or other querying languages and is a technical process. However, with LLM Consulting services and integration with your BI systems, your employees can enter queries in regular/ natural languages like plain English text. The model will understand the input, analyze data, and provide an output in the same simple language. For example, you can enter a query, ‘What is the customer segmentation for this quarter’s sales for product X?’ and receive an appropriate answer immediately with graphs as well as a text summary.
Dynamic Reporting and Data Visualization
The Power BI dashboard is known for its data visualization capabilities. By integrating it with large language models, you can further enhance the reporting process. The time taken to manually extract data from sources, transform it, and analyze it is heavily reduced due to automation. Moreover, LLMs can generate custom reports based on user preferences. Each stakeholder can have a customized dashboard or report with specific parameters. All this is possible even without technical knowledge. In short, LLMs promote self-service BI capabilities to make the insights easily accessible to everyone in the enterprise.
Real-Time Predictive Analytics
Large language models are continuously evolving and getting better. This will make it possible to derive real-time predictive analytics based on present data. For example, you can generate data-driven predictions/ forecast reports about the possible sales for a product or service. It helps in developing targeted marketing campaigns, adjusting inventory levels, and managing competition. You can also personalize promotions to reach a wider range of audiences based on their interactions with your business.
LLM-Driven Competitor Analysis
Every organization has to keep an eye on its competitors and the market to stay ahead of others or grab opportunities quickly. This requires robust business intelligence reporting, which is possible by integrating LLMs with Power BI dashboards. In fact, you can hire end-to-end Power BI consulting services with large language model development to set up a comprehensive business intelligence system (on-premises, on cloud, or a hybrid infrastructure). Then, you can automate insights by analyzing market trends, competitor movements, social media interactions, etc., to make proactive decisions.
Conclusion
Large language models are the future. They can aid your business intelligence systems in various ways, be it data processing or report generation. Automation, accuracy, scalability, and flexibility will become easier when you integrate LLMs with your BI platforms.
Hire reputable AI product development companies to build, train, deploy, and integrate powerful LLMs with your Power BI and other business intelligence systems. Future-proof your business while empowering employees to be more productive at work without compromising quality. Stay ahead of your competitors and accelerate growth.
FAQs
How can LLMs increase the ROI of my existing BI investments?
LLMs can increase the ROI of your existing business intelligence investments by automating the analysis and reporting processes, empowering employees through self-service BI, accelerating insights, and enhancing data interpretation to provide more accurate reports. At DataToBiz, we help businesses by offering tailored LLM integration with BI systems and providing long-term support services.
Do LLMs make BI insights more accessible for non-technical executives like me?
Yes, LLMs can make BI insights more accessible for non-technical executives by generating summaries of the reports and explaining the insights in simpler words. Large language models make it possible for non-technical users to access BI reports and make data-driven decisions without directly relying on the IT teams.
What new business decisions can I enable by combining BI with LLMs?
You can make different business decisions by combining BI with LLMs. For example, you can create better customer experiences, predict future sales/ opportunities to develop robust marketing campaigns, track your competitors, and streamline internal operations. Talk to LLM developers at DataToBiz to know more about how integrating large language models with business intelligence can boost your business.
Will adopting LLMs with BI require a major overhaul of my current data systems?
Adopting LLMs with BI will require some changes to your existing systems, though the actual developments are case-sensitive. If you already have a central data repository (data warehouse or a data lake), major overhauls are not necessary. DataToBiz offers end-to-end LLM product development services and can streamline your data connection, storage, systems, etc., deliver the desired outcomes and increase ROI.
How do LLMs improve the speed and accuracy of business reporting?
LLMs enhance the speed and accuracy of business reporting by automating various processes, including data analysis, content generation, and reporting. This reduces the risk of human error and increases accuracy over time. However, it is vital to fine-tune the LLMs on quality datasets to ensure accurate and meaningful business reports. Our experts at DataToBiz build and train the large language models as per your needs.
What risks, like compliance or data security, should I plan for when adding LLMs to BI?
Consider the following risks when adding LLMs to BI:
- Data quality and bias
- Data compliance
- Data security and privacy
- Ethical considerations and responsible AI
- Interoperability
- Resource optimization
- Ability to interpret
DataToBiz has the necessary experience to help you overcome these challenges and enable successful LLM integration with BI to achieve your goals.
More in LLMs Development Services Providers
LLM development services help build, train, and deploy high-quality large language models aligned with your business specifications and objectives. From strategy development to long-term maintenance and support, our end-to-end services are customized to help each organization strengthen its internal processes, enhance customer experience, and increase revenue. With high-performing LLMs, you can make proactive data-driven decisions and gain a competitive edge in the global market.
Read the links below for more information about LLM development.
- LLMs in AI Development – Key to AI’s Next Breakthrough?
- 15+ Next Gen ML Engineering Companies – The 2025 Watchlist
- How to Hire the Right LLM Consultant? CEO’s Guide to Exploring LLM Integration
Fact checked by –
Akansha Rani ~ Content Management Executive
