Watsonx BI is on the Horizon

Will it be a hit or miss?

Craig Colangelo, September 22, 2025

Introduction

Many organizations invest heavily in Business Intelligence (BI) tools, but despite this significant investment, adoption remains surprisingly low, often stuck around 30%. The complexity of traditional BI workflows and the reliance on a limited number of data analysts create bottlenecks, preventing most employees from easily accessing the insights they need to make timely, data-driven decisions.

But what if you could empower everyone in your organization to gain actionable insights in seconds, simply by asking questions in plain language?  Enter the age of generative business intelligence (GenBI), and specifically, IBM’s Project Ripasso, now known as watsonx BI. This AI-powered business analyst and advisor is possibly poised to improve how businesses interact with their data, making complex analysis accessible to ordinary business users without needing specialized skills. It aims to surface insights tailored to your business context and data with speed and ease, guiding you toward more impactful decisions.

Looking ahead, the integration of watsonx BI with existing platforms like IBM Cognos Analytics, watsonx.data, and watsonx Orchestrate suggests a future where AI-driven insights are seamlessly woven into daily workflows and decision-making processes.  This represents IBM’s vision for the next generation of BI (BI 3.0), designed to unlock new value and dramatically increase data literacy and adoption across the enterprise by bringing AI-augmented analytics to the large percentage of employees who don’t currently use BI tools.

Preview mode is currently available. A targeted General Availability (GA) date of September 2024 was missed…and pricing and a full sales kit are not yet available. IBM encourages interested users to join a waitlist to be contacted when watsonx BI is available. It’s also noted that some (most) of its features will probably work their way into Cognos Analytics Assistant features in due time. As with any statement about future direction, the release and timing are subject to change or withdrawal without notice…after all, we’re prognosticating here. 

Summary

This quick synthesis provides an outline of IBM’s watsonx BI, formerly known as Project Ripasso, and its positioning within the burgeoning field of generative Business Intelligence (BI). Acknowledging the historically low adoption rates of traditional BI tools despite significant market investment, IBM is introducing watsonx BI as an AI-powered business analyst and advisor designed to democratize data analysis and accelerate decision-making for all business users, not just data analysts. Key themes include the leveraging of generative AI and Large Language Models (LLMs) for natural language interaction, automated data preparation, metric creation, and semantic modeling. The service emphasizes trust, transparency, and governance, integrating with the broader IBM Data and AI ecosystem while also allowing for connections to third-party data sources.

Key Themes and Important Ideas:

Addressing Low BI Tool Adoption:

• Traditional BI tools are perceived as complex and slow, leading to a significant gap between market investment and actual employee usage.
• The business intelligence software market is projected to reach USD 27.9 billion by 2027, yet only around 30-35% of employees use traditional BI tools for decision-making.
• The primary hurdle in adopting BI tools is their complexity.
• watsonx BI aims to simplify BI and empower all business users with actionable insights.

Generative AI and Natural Language Interaction:

• watsonx BI is primarily powered by generative AI and utilizes Large Language Models (LLMs).
• It allows users to interact with complex data systems using intuitive natural language, similar to generative AI chatbots like ChatGPT.
• Users enter natural language instructions and the tool responds accordingly.
• This eliminates the need for specialized programming languages (like SQL) or complex dashboard building, making data analysis accessible to non-technical users.
• Ask questions using natural language and receive answers through a simple, intuitive interface.

Automated Data Preparation and Semantic Modeling:

• watsonx BI (Project Ripasso) empowers users with “AI-powered data preparation”
• Key features promise automated metric creation, real-time exploration using natural language, and robust semantic models.
• The platform automates the creation of business semantics, clarifying the meaning of data within a business context.
• It saves time by automatically profiling, enriching, and modelling data.
• A centralized metrics catalog allows for defining, standardizing, and sharing key metrics across teams for consistent reporting.

Focus on Trust, Transparency, and Governance:

• IBM emphasizes the importance of trusted AI, stating that “The full impact of AI can only be achieved when AI can be trusted.”
• watsonx BI is designed with strong data governance, compliance, and transparency in mind.
• Answers generated by watsonx BI offer explainability, allowing users to understand how the AI arrived at its conclusions. This provides a clear path from data input to insight output, helping users uncover the “why” behind insights.
• The platform is built on a robust governance and permissions model.
• IBM explicitly states that they do not train their models on client data. Only metadata sent to LLM, not the actual data. This addresses privacy concerns.
• To mitigate the risk of hallucination (generating false and often very convincing outputs), watsonx BI is built with boundaries and guards, and will inform users if it cannot find the right information to answer a question. Retrieval augmented generation (RAG) is mentioned as a technique to ground responses in factual external knowledge.

Integration with the IBM Data and AI Ecosystem:

• watsonx BI is designed to lighten up the IBM Data and AI ecosystem.
• It integrates with existing IBM tools such as Planning Analytics and watsonx.data Data Intelligence (IKC + DPH).
• It can leverage governed semantic models and metrics defined in Cognos Analytics.
• Additionally, the platform is designed to integrate with any third-party vendor via APIs, eliminating vendor lock-in. Fantastic idea!

Beyond Dashboards: Actionable Insights and Proactive Partner:

• watsonx BI aims to move beyond static dashboards to provide actionable insights in seconds.
• It acts as an AI-powered business analyst and advisor, guiding users toward impactful decisions.
• The platform provides insights with smart alerts and prompts, delivering personalized and contextual insights relevant to a user’s business context and data.
• Examples of use cases across Sales, Operations, and Finance highlight how watsonx BI can provide proactive alerts and insights to drive specific actions (e.g., adjusting delivery plans due to inventory shortfall, proposing shifting resources to growth areas).
• watsonx BI is presented as a “proactive partner founded on trusted data and AI.”

Market Positioning and Availability:

• watsonx BI, formerly Project Ripasso, is a relatively new offering from IBM. Not yet GA.
• It is positioned as a user-friendly solution for both technical and non-technical users.
• Compared to competitors like Tableau or Power BI…Project Ripasso (watsonx BI) really emphasizes data governance, compliance, and transparency. IBM sees this as critical for adoption by the masses.
• Currently, Project Ripasso’s pricing is not publicly available.
• watsonx BI is currently in preview, with a waitlist available for interested users.

Conclusion

IBM’s watsonx BI represents a strategic move to address the persistent challenge of low BI tool adoption by leveraging generative AI. By simplifying data interaction through natural language, automating data preparation and semantic modeling, and prioritizing trust and transparency, IBM aims to empower a broader base of business users to derive actionable insights and make data-driven decisions at an accelerated pace. It aims to take BI to the masses in ways that were previously unimaginable.  The platform’s integration with the existing IBM data ecosystem and its open interface for third-party connections underscore a commitment to providing a flexible and governed environment for generative BI. While still only in preview, watsonx BI appears to be a significant step in the evolution of business intelligence towards AI-powered self-service analytics.  Will it be a hit or a miss?  The overall idea and the gaps that it proposes to address position it to be a difference maker.  The nuance around how IBM chooses to implement genAI-based vs rule-based assistant components and functions, seems to me to be the nut that they must crack well in order to make this a hit.  Time will tell. 

Next Steps

If you found this analysis insightful, we’d love to continue the conversation. At PMsquare, we help organizations evaluate, implement, and optimize solutions like watsonx BI within their broader analytics strategy. Whether you’re exploring how generative AI can enhance self-service analytics or need guidance on modernizing your BI environment, our team is here to help. Contact our team to discuss how we can support your journey toward more impactful, AI-driven insights.

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