Kyvos and Generative BI: Paving the Way for AI-Backed Analytics

Artificial intelligence is getting as real as it can very real, very quickly. With new applications and opportunities rising every day, it has become the go-to for matching human capabilities. One of the most recent and transformative advancements in this space is generative BI which has unlocked new frontiers in business intelligence.

At its core, Gen BI is about making data more accessible and actionable for users. It offers the potential to automate complex analyses, provide deeper insights and empower all users to connect to their data using natural language. As more organizations adopt AI-driven tools, generative BI is quickly becoming a must-have rather than an optional choice for data and analytics-driven enterprises.

How Is Generative BI Different from Traditional BI

Traditional BI tools were designed to extract, analyze, present data and working with these tools requires significant technical skills. This makes it challenging for users and stakeholders with non-technical background to access and act on the available data. As a result, there lies a gap between the data and the people who want to make sense of it for business growth.

In contrast, generative BI uses NLP and ML to simplify and automate the data analysis process. It also allows users to ask complex questions in natural language and get instant and contextually relevant answers. It makes complex analyses seem extremely simple even to users who lack technical skills to handle the intricacies of SQL or data models.

How Does Generative BI Work

Generative BI tools use gen AI techniques and combine them with business intelligence to facilitate easy insight discovery. This approach represents a paradigm shift from reactive to proactive analytics through intuitive and conversational interactions. Users don’t have to wait for reports to be generated as they do using traditional BI tools. A generative BI tool can also be used to perform different steps like data collection, analysis, visualization, recommendations etc.

For example, consider the scenario of an e-commerce retailer experiencing a decline in sales for one of their target regions. Instead of creating and analyzing multiple reports via BI tools, the retailer can use generative BI and simply ask a question in natural language, “Why have sales decreased in the East region over the past quarter?” In response, the tool may perform the following steps:

1. Use NLP techniques to interpret the question and identify relevant data sources to generate the answer
2. Clean and prepare data to compare the performance of the East region with the rest of the regions for identifying any patterns and trends
3. Get insights based on the data and analysis to share reasons behind low sales in the said region
4. Create visualizations to showcase the results. Example, a line chart showing the declining sales trend or a bar chart comparing regional performance
5. As a final step, the tool might also suggest recommendations and strategies such as targeted marketing campaigns etc. to improve the sales of that region

And all of this is done within seconds by responding to the user in natural language and retaining the context. The beauty of generative BI lies in the fact that it simplifies the entire data analysis process so smoothly. Through advanced AI techniques, it automates complex data processing tasks and delivers what the users want, all while maintaining accuracy and scalability.

Advantages of Adopting Generative BI

The generative AI market is expanding to new horizons. According to a report published in 2024 by Grand View Research, the global generative AI market was valued at USD 16.87 billion in 2024 and is projected to grow at a compound annual growth rate (CAGR) of 37.6% from 2025 to 2030. This leads to an increase in the applications of this advancing technology. Generative BI, being a part of this revolution, is set to deliver several advantages that make it appealing for companies

With self-serve analytics, users can analyze all their data almost instantly just by asking the right questions. This capability facilitates effective use of analytics for data workers of all skill levels across various business functions like finance, marketing, sales or operations. These tools enable users to get AI backed insights with faster and optimized analytics.

Built to scale with expanding needs of enterprises, generative BI tools stand out with their capability of handling large volumes of both structured and unstructured data. They also assist in analyzing it efficiently, as compared to manual analysis or traditional BI approaches. Generative BI can also help organizations to save time, lower costs and boost productivity for BI efforts by automating time consuming and resource-intensive tasks such as creating reports and performing complex calculations. Tasks that once took days or weeks with manual or even traditional tools can be completed quickly.

Kyvos Copilot: What Sets It Apart

Generative BI has changed the way businesses connect to their data. Kyvos Copilot adds value to this equation by enabling businesses to create, explore and summarize insights intelligently. Built on the Kyvos semantic layer, Copilot blends natural language understanding with guided exploration and reasoning capabilities to simplify complex analytics tasks. Kyvos Copilot uses gen AI capabilities that differentiates itself in the competitive market by offering the following innovative features:

• Automates business calculations: Users can describe KPIs or metrics in natural language, and Copilot automatically generates optimized MDX or SQL expressions—removing the need for manual query writing.

• Interactive query playground: Lets users visualize data, compare metrics and analyze trends on the fly—without switching tools or knowing technical syntax.

• AI-generated summaries: Produces instant natural language summaries of key points such as anomalies, trends and outliers automatically and delivers them directly to the user’s inbox.

• Intelligent data selection: Dynamically identifies the most relevant semantic models and datasets to ensure accurate, consistent insights every time.

With Kyvos Copilot, analytics becomes proactive and assistive—users can discover insights, validate hypotheses and generate business logic effortlessly. It’s not just about getting answers; it’s about accelerating decisions with context-aware, governed intelligence.

Wrapping Up

Generative BI is reshaping the way organizations leverage data, shifting from traditional, reactive analysis to AI-driven, proactive insights. By automating complex tasks and enabling natural language interactions, it supercharges analytics for accelerated decision-making. Kyvos amplifies this transformation with its advanced AI-enabled copilot platform and enhances data accessibility for faster yet trustworthy analytics. As generative BI evolves, it will be key for enterprises seeking to maintain a competitive edge in an increasingly data dependent environment.