The evolution of business intelligence: from dashboards to AI-driven assets
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This article marks the beginning of our AI & BI series, where we explore the intersection of artificial intelligence and business intelligence. BI has evolved significantly over the years, shifting from static reports to AI-powered decision-making. While AI has always played a role in BI—through NLP, built-in predictions, and automation—the rise of large language models (LLMs) has accelerated this transformation. In this article, we examine BI’s past, present, and future, focusing on Microsoft, OpenAI, and Databricks.
1. The history of AI in business intelligence
Business intelligence has been a critical component of data-driven decision-making for decades. Initially, BI relied on descriptive analytics, where static dashboards and reports helped organizations analyze past performance. Early AI-driven BI included basic forecasting and clustering tools, often used separately from traditional BI platforms.
The term “augmented analytics” emerged in 2017, marking a shift where AI began automating data preparation, insight generation, and query handling. Features like natural language processing (NLP) allowed business users to ask questions in plain language and receive data-driven answers. Microsoft Power BI, for instance, introduced Q&A features that let users interact with data conversationally, making BI more accessible. Over time, businesses sought BI tools that moved beyond passive reporting, focusing instead on proactive insights and automation.
While AI has long been present in BI, its role was largely limited to predictive analytics, anomaly detection, and auto-generated insights. The introduction of generative AI and LLMs has opened entirely new possibilities, fundamentally altering how businesses interact with their data.
2. AI in BI today - conversational AI, automation & new tools
Modern BI is undergoing a major shift towards conversational and generative AI, making insights more accessible and actionable. While traditional BI still relies on predictive capabilities, built-in reporting, and automated insights, the rise of conversational AI is revolutionizing the way businesses interact with their data.
Ask your data - The rise of conversational AI in BI
One of the most transformative aspects of modern BI is Conversational AI, where users can interact with data using natural language instead of predefined dashboards. This approach allows non-technical users to explore insights dynamically, without requiring deep knowledge of data structures or query languages.
Instead of navigating complex reports, users can “ask their data” for insights and receive AI-generated responses instantly. For example, a retail company using AI-powered BI tools can analyze sales trends simply by typing a question like „What were our top-selling products last quarter?” and receiving an instant, visualized response without building a report manually. This trend is reshaping BI by:
- Enhancing user adoption by making data analysis intuitive and accessible.
- Reducing reliance on predefined dashboards and static reports.
- Bridging the gap between traditional BI users and advanced analytics.
This feature is now a core element in BI solutions, complementing traditional analytics tools. With AI-driven predictive models, automated anomaly detection, and built-in reporting, conversational AI is becoming a key differentiator for modern BI platforms.
Overview of leading AI-driven BI solutions
There are multiple players shaping this transformation, including Microsoft, OpenAI, Databricks, Snowflake, Amazon, and Google. While many vendors are innovating in this space, we will focus on Microsoft, OpenAI, and Databricks due to their significant contributions to AI-driven BI and their influence on current enterprise solutions. In this section, we will focus on Microsoft Power BI, OpenAI, and Databricks.
Microsoft Power BI, Copilot & Fabric
- Power BI Copilot is a game-changer in AI-powered analytics, allowing users to generate reports, summarize data, and receive AI-driven insights using natural language commands.
- Built-in AI functionalities in Power BI and Fabric include automated insights, anomaly detection, key influencers analysis, and natural language Q&A, enabling users to extract meaningful patterns without deep technical expertise.
- Microsoft Fabric unifies data engineering, real-time analytics, and AI-driven BI on a single platform. This integration ensures that organizations can leverage AI at every stage, from raw data processing to final reporting.
- The combined effect of Power BI and Fabric is a more dynamic, automated approach to BI, reducing reliance on manual data modeling and enhancing real-time decision-making.
OpenAI & ChatGPT
- Unlike Microsoft and Databricks, OpenAI does not offer a BI-specific tool. However, its models are increasingly used as BI solutions themselves.
- Many businesses now use ChatGPT and OpenAI-powered tools to analyze data from Excel, CSV files, and databases. This self-service approach allows non-technical users to gain insights without dedicated BI platforms.
- The flexibility of OpenAI’s models means that while they are not embedded in existing BI systems, they are shaping how businesses interact with and interpret data.
Databricks & AI/BI
- Databricks is pioneering AI-Driven Business Intelligence (AI/BI), which integrates AI directly into analytics workflows to enhance decision-making.
- AI/BI enables users to interact with their data through AI-powered automation, making insights more dynamic and actionable without requiring extensive manual intervention.
- This bridges the gap between traditional BI and AI-driven automation, making data more accessible and allowing businesses to accelerate insight generation and improve data-driven decision-making.
The growing capabilities of these platforms indicate that AI-driven BI is rapidly advancing, but the exact trajectory of generative AI in BI remains uncertain. While we see significant progress, the full impact and adoption curve of these technologies are still unfolding.
3. The future of AI-driven BI: agentic BI & automated decision making
Looking ahead, BI will move beyond passive insights to decision intelligence, where AI not only presents findings but also recommends or automates actions. Two key directions are emerging:
- Agentic BI & AI assistants – AI-powered BI agents will autonomously execute multi-step analysis tasks, proactively surfacing insights and suggesting actions. These systems will go beyond responding to queries by anticipating business needs and proactively delivering insights.
- Automated decision-making – AI will play a larger role in operational decisions, adjusting strategies based on predictive models in real time. This will enable businesses to act more dynamically in response to shifting market conditions, automating tasks that previously required manual intervention.ion.
However, the future of AI-driven BI is not set in stone. While trends suggest an increasing role for AI agents, automation, and decision intelligence, we must acknowledge that the long-term impact of generative AI in BI is still uncertain. Businesses must remain flexible, adapting as AI capabilities continue to evolve.
“AI and BI is the next big step for traditional business intelligence. With generative AI, we are entering a new era of possibilities—one that expands reporting adoption and shifts how businesses leverage data for better decision-making. However, the future of AI-driven BI is not yet fully defined, and businesses should remain adaptable as the landscape continues to change.”
- Key takeaways
- BI has evolved from static reports to AI-powered, interactive analytics.
- Conversational AI is becoming a core feature of modern BI, complementing traditional predictive and reporting capabilities.
- Microsoft, OpenAI, and Databricks are at the forefront of AI-driven BI advancements.
- The future of BI is shifting towards decision intelligence and automation, but businesses must remain flexible as AI technologies evolve.
This is the first article in our four-part AI & BI series. Stay tuned for our next articles, where we explore AI-driven BI challenges, real-world use cases, and how Ask Your Data is shaping the future of business intelligence. In the meantime, explore the power of AI-driven BI tools today and unlock new possibilities for your business.
Sources:
Wiktor Zdzienicki
Senior Portfolio Lead D&AI
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