Why AI Falls Short Without Access to the Right Data
Artificial intelligence has quickly moved from experimentation to enterprise necessity. But as organizations invest in AI tools and LLM-based assistants, many are hitting a wall: the results aren’t as accurate or relevant as expected.
The issue? AI is only as good as the data it can access. And the reality is that most of the data your AI needs is hidden in unstructured formats—emails, PDFs, presentations, video files, and chat transcripts. These are rich sources of institutional knowledge, but they live outside the traditional training datasets used by most large language models.
Recent research shows that less than 1% of enterprise data has been used to train LLMs. That means 99% of your most valuable insights are being left out of the equation—and it shows in the quality of AI responses.
This gap between enterprise data and AI effectiveness is becoming one of the biggest limiting factors in ROI. Fortunately, there’s a solution.
Content-Aware Storage Changes the Game
IBM Storage Scale now offers content-aware capabilities that fundamentally shift how enterprise data interacts with AI. Instead of manually tagging or transforming your data to make it usable for AI models, content-aware storage extracts meaning automatically—right at the point of storage.
By embedding metadata extraction, indexing, and contextual understanding into the storage layer, IBM Storage Scale enables:
- Real-time access to the most current and relevant enterprise information
- Streamlined inferencing and retrieval-augmented generation (RAG) workflows
- Improved accuracy and contextual depth in AI assistant responses
- Lower costs by reducing the need for duplicative storage or retraining
This means that AI tools can access and use enterprise-specific knowledge without requiring manual curation or IT intervention. From the moment a file is saved, it becomes usable by AI—securely, efficiently, and contextually.
Explore the video and resources here to see how this works in action.
Real-World Impact: AI That Actually Knows Your Business
One of the most compelling use cases comes from the healthcare research space. In a recent demonstration, medical researchers working to improve outcomes for cystic fibrosis patients used IBM and NVIDIA technologies to build AI agents that analyze patient notes, study data, and historical trends.
Without content-aware storage, much of that information—especially in PDFs and handwritten notes—would remain locked away. With IBM Storage Scale, the data became instantly available for inferencing, enabling real-time reporting and actionable insights that can improve care.
This is just one example. Every enterprise has its own untapped well of insight hidden in unstructured content. Content-aware storage helps make it usable.
Why Jeskell Systems
As an IBM Platinum Business Partner with over 35 years of experience, Jeskell Systems helps organizations navigate the complexities of modern infrastructure to get the most out of their AI investments.
We understand the nuances of secure data management, unstructured data challenges, and hybrid cloud environments. Our experts work with you to design and deploy scalable storage strategies that:
- Integrate IBM Storage Scale for real-time content awareness
- Optimize storage for GPU-accelerated AI workloads
- Support secure, governed access to data across environments
- Improve performance, reduce infrastructure sprawl, and lower costs
From early strategy to deployment and long-term support, we’re the partner that helps turn infrastructure into innovation.
See how content-aware storage can unlock smarter outcomes for your organization.