IBM unveils watsonx.data’s generative AI capabilities at Think 2025

IBM‘s new watsonx.data platform is taking center stage at Think 2025 as the company addresses a critical challenge in enterprise AI adoption: data readiness. While organizations are rapidly embracing generative AI, IBM reveals that less than 1% of enterprise data is currently being utilized for these initiatives, despite approximately 90% of corporate data being unstructured and scattered across various systems. This data fragmentation, rather than model optimization or inference costs, represents the true bottleneck preventing companies from realizing AI’s full potential.

The big picture: IBM is positioning watsonx.data as the solution to the enterprise unstructured data problem by transforming it into a hybrid, open data lakehouse with data fabric capabilities.

• The platform aims to simplify the data-for-AI stack with an open architecture that can operate across hybrid environments.
• New features include “watsonx.data integration” for managing diverse data formats and “watsonx.data intelligence” which uses AI to automate data curation and governance.

Why this matters: With enterprise adoption of generative AI accelerating, many organizations are discovering their legacy data environments aren’t equipped to support AI initiatives effectively.

• Most enterprises have been misaligning their generative AI strategies by focusing on application development rather than addressing foundational data challenges.
• The platform addresses the reality that approximately 90% of enterprise data is unstructured and dispersed across multiple locations, formats and systems.

Real-world impact: IBM showcased several business examples demonstrating watsonx.data’s effectiveness across industries.

• BanFast, a construction company, reduced manual data input by 75% while enhancing worker health and safety.
• A U.S. financial services firm saved $5.7 million by creating a unified view of operational IT data.
• A global manufacturing client automated indirect tax data ingestion across 34 source systems operating in 73 countries.

Implementation challenges: Despite its promise, watsonx.data faces several adoption hurdles that enterprises will need to overcome.

• Complex data integration across diverse environments remains technically challenging.
• Data sprawl and governance issues continue to complicate implementation.
• Many organizations face readiness and skill gaps when deploying sophisticated data platforms.
• Cost and operational complexity present additional barriers to adoption.