Since 2022, artificial intelligence has undergone a remarkable transformation, with generative AI at the forefront of this evolution. What began as simple text generation has blossomed into a suite of sophisticated multimodal capabilities, including advanced text analysis, image processing, and seamless text-to-image conversions. This technological leap has had far-reaching implications across industries, with Business Intelligence (BI) experiencing a particularly profound impact.

Over the past two decades, BI itself has charted an impressive course of progress. The journey began with foundational SQL-based tools that enabled basic data querying, providing organizations with their first glimpse into the power of data-driven decision-making. This was followed by the rise of visualization pioneers like Tableau, which revolutionized how businesses interacted with and understood their data through intuitive, interactive interfaces. The next wave brought augmented BI tools, exemplified by platforms like ThoughtSpot, which leveraged AI to enhance data discovery and analysis. Today, we stand at the cusp of a new era with the emergence of Generative BI, a paradigm that harnesses the full potential of generative AI to redefine how we approach data analysis and insight generation.

Generative Business Intelligence (Generative BI) represents the convergence of large language models (LLMs) with traditional BI processes. This integration streamlines complex tasks such as data analysis, visualization, and reporting. At its core, Generative BI employs natural language interfaces to democratize analytics, enabling users across all organizational levels to generate profound insights without the need for specialized technical skills.

By leveraging the capabilities of generative AI, Generative BI tools can:

• Process and analyze vast amounts of structured and unstructured data
• Generate human-readable reports and visualizations from simple prompts
• Provide real-time insights and recommendations based on complex data patterns
• Automate routine BI tasks, freeing up human resources for more strategic work

This democratization of data analytics means that even team members without a background in data science or programming can engage deeply in data-driven decision-making, breaking down traditional barriers to entry in the field of business intelligence.

Generative AI, particularly through large language models (LLMs) and AI agents built with these models, is revolutionizing the field of Business Intelligence. This technology is enhancing various BI processes:

1. Data Collection: Generative AI tools can discover, clean, transform, and aggregate data from multiple sources, preparing it for analysis.
2. Data Analysis: These tools excel at processing vast amounts of complex data, including unstructured information, to identify patterns, answer questions, and uncover trends.
3. Data Reporting: Generative BI enables natural language reporting and interactive Q&A, making data insights more accessible to all users.
4. Action Planning: By analyzing data trends, generative BI can provide recommendations and help in scenario modeling for informed decision-making.

Data Collection

Generative BI tools streamline the data collection process by integrating various data sources, cleaning the data, and transforming it into a usable format. For example, when tasked with creating a report on spending by a business unit, a generative BI tool can automatically locate relevant financial records across the organization, standardize data formats, and compile the information into a coherent report.

Generative AI can significantly expedite this process by:

1. Automating data cleaning and normalization
2. Identifying and reconciling data inconsistencies across sources
3. Suggesting appropriate data transformations based on analysis goals
4. Creating metadata and data lineage documentation automatically

This automation not only saves time but also reduces the risk of human error in data preparation, ensuring a more reliable foundation for analysis.

Data Analysis

Generative BI tools shine by their ability to handle unstructured data and perform advanced pattern recognition. Consider a scenario where a user asks the tool to identify business units that have consistently exceeded their budget over the past eight quarters. The generative BI tool can quickly analyze financial data, recognize spending patterns, and even suggest potential reasons for overspending based on various data points it has access to.

Traditional BI tools excel at analyzing structured data but often struggle with unstructured information like text documents, images, and videos. Generative AI excels in processing and deriving insights from unstructured data by:

1. Applying natural language processing to analyze text documents and social media content
2. Using computer vision to extract information from images and videos
3. Combining structured and unstructured data analysis for a more comprehensive view

This capability allows organizations to tap into a wealth of information previously inaccessible through traditional BI methods, providing a more holistic understanding of their business environment

Data Reporting

Generative BI transforms data reporting through natural language interfaces. Users can simply ask for specific visualizations or reports using plain language. For instance, a request like “Show me a pie chart of our top 5 best-selling products last year, divided by each product’s percentage of sales” would prompt the tool to analyze the sales data and generate the requested visualization automatically.
Generative BI goes beyond just presenting data; it can craft narratives around the insights it uncovers. This feature transforms raw data and visualizations into coherent, easy-to-understand stories, making complex data analyses accessible to stakeholders across all levels of an organization.
It can also offer recommendations based on its analysis. For example, a manufacturing company might use Generative BI to analyze production data and receive suggestions for optimizing their supply chain, reducing costs, and improving efficiency.

Action Planning

In action planning, generative BI tools can provide data-driven recommendations. For example, after analyzing business unit spending, the tool might suggest breaking down expenses on a per-project basis to identify which projects aren’t delivering sufficient return on investment. This capability enables organizations to make more informed decisions about resource allocation and strategic planning.

While generative BI offers significant advantages, it also presents several challenges that organizations must address:

1. Data Quality: The effectiveness of generative BI relies heavily on the quality of input data. Organizations must implement robust data governance practices to ensure data accuracy and consistency.
2. Integration Complexity: Integrating generative BI tools with existing data infrastructures can be complex. It’s crucial to develop a comprehensive integration strategy that addresses potential compatibility issues.
3. User Adoption: Despite the user-friendly nature of generative BI tools, there may still be resistance to adoption. Organizations should focus on change management and provide adequate training to ensure smooth implementation.
4. Trust in AI-Driven Decisions: Building trust in AI-generated insights is critical. Implementing AI accountability measures and ensuring transparency in how the AI arrives at its conclusions can help mitigate this challenge.
5. Data Security and Privacy: With the increased use of AI in data analysis, ensuring data security and privacy becomes paramount. Organizations must implement robust security measures and comply with relevant data protection regulations.

• Measurement and Calibration: Ensuring AI Accountability:To maintain trust in AI-driven BI, organizations must implement rigorous measurement and calibration processes. By integrating reinforcement learning and performance assessment tools, businesses can ensure AI insights remain as reliable as traditional BI—if not more so. This approach enhances both speed and precision, providing a solid foundation for strategic decision-making.
• The Power of Multi-Agent Strategies:A multi-agent strategy could emerge as a game-changer in supporting structured data analysis. By deploying multiple specialized AI agents, each focusing on specific aspects of data interpretation, we can achieve a more comprehensive and nuanced understanding of complex business landscapes.These BI agents are inherently adaptable, making them perfect for seamless integration into existing business applications. Whether it’s financial forecasting, market trend analysis, or operational efficiency assessments, a multi-agent approach ensures that no stone is left unturned in the quest for actionable insights.
• Unlocking New Market Opportunities:The true potential of AI in BI lies in its ability to provide personalized insights. Imagine conversational agents tailored to individual user needs, capable of understanding context and delivering relevant information on demand. This level of personalization not only enhances user experience but also democratizes data access across the organization.These intelligent agents go beyond mere data retrieval. They become catalysts for innovation within enterprises by enabling:
  • Advanced data discovery, uncovering hidden patterns and correlations
  • Predictive analytics, forecasting trends and potential outcomes
  • Dynamic content generation, creating reports and visualizations in real-time

By streamlining data access and interpretation, AI-driven BI empowers organizations to make informed decisions faster and with greater confidence.

• A New Era for Business Intelligence:AI-driven BI is more than a technological enhancement—it’s a fundamental shift in how businesses leverage data. This transformation is built on ;
  • Collaboration – Combining human expertise with AI-driven insights
  • Continuous innovation – Advancing data interpretation techniques
  • Trust & accountability – Ensuring AI reliability through rigorous validation

As AI continues to evolve, BI systems will become increasingly proactive, offering predictive and prescriptive analytics that not only inform but also guide business strategy.For more insights into what to expect for 2025 with regards to AI, check out the comprehensive e-book on AI Business Trends 2025.

At 66degrees, we develop innovative, human-centric AI solutions. Our approach to Generative BI focuses on creating tools that enhance human decision-making rather than replace it, ensuring that AI serves as a powerful ally in business strategy and operations.

A prime example of this philosophy in action is 66degrees’ collaboration with TVision, a leading media measurement company. This project highlights how 66degrees implements tailored BI solutions that enhance decision-making capabilities through human-centered design. 

They helped provide TVision with a new solution specifically crafted for improved business analysis, and demonstrated how AI can serve as a powerful ally in shaping business strategy and optimizing operations.

The success of the TVision project underscores the transformative potential of human-centric AI solutions in BI. By making use of advanced analytics and cloud technologies, 66degrees helped TVision streamline their data processes and gain deeper insights into their business operations. This collaboration not only improved TVision’s analytical capabilities but also empowered their team to make more informed, data-driven decisions.

Generative BI stands at the intersection of artificial intelligence and business intelligence, offering unprecedented opportunities for organizations to use their data to its full potential.While traditional BI focused on past analysis, Decision Intelligence powered by Generative AI provides actionable, forward-looking insights that enhance strategic planning and operational efficiency. It’s not just better data visualization; it’s an intelligent system that works alongside decision-makers, offering recommendations and anticipating future scenarios.

At 66degrees, we’re not just implementing new tools; we’re reimagining decision-making frameworks. Our approach to Generative BI creates a holistic ecosystem that:

• Empowers employees at all levels to derive insights without advanced technical skills
• Utilizes intuitive interfaces and natural language processing
• Fosters a culture of data-driven decisions
• Leverages the robust, scalable Google Cloud infrastructure

As we look to the future, we’re particularly excited about the potential of Conversational AI in the BI space. Imagine being able to ask your BI system complex questions in natural language and receiving instant, nuanced responses. This is not a far-off dream, but a reality we’re helping to create for our clients today. 

At 66degrees, we empower organizations to make the right choices when it comes to cloud modernization and setting the stage for AI integration. Our strategic Google Cloud consulting services help align your technology needs with your business objectives, ensuring a robust, future-proof AI infrastructure. By making use of our deep expertise in cloud, data and AI engineering, we guide you through every step of your transformation journey. Connect with us to learn how we can help.