Go, Set, Ready? Why AI Fails Without the Right Data Foundation

Go, Set Ready.  Wait a minute, shouldn’t that be Ready. Set. Go?

In the race to implement Generative AI, many organizations are doing things backward —jumping straight to “Go” before ensuring they are truly AI-ready. But without a strong foundation, AI initiatives are bound to stumble.

At the Gartner Data & Analytics Summit I attended this week, I had the opportunity to sit down with Gartner Director Analyst Deepak Seth to discuss the growing importance of unstructured content in GenAI applications. With 70-90% of enterprise data now unstructured, businesses must rethink how they manage and prepare data before feeding it into AI models.

The Unstructured Data Blind Spot

Most organizations are only scratching the surface of their unstructured content. While some focus on data stored in SharePoint Online, the reality is that petabytes of valuable information is spread across file shares, OneDrive, business applications, financial systems, and even physical records stored in banker’s boxes. These overlooked assets contain crucial insights—contracts, HR records, invoices, and more—that could enhance AI-driven decision-making if properly leveraged.

However, most of this data is missing from AI pipelines because it is:

• Not trusted – Sensitive data (PII, PHI, confidential records) is often mixed in, raising compliance and privacy risks.
• Undiscovered – Hidden in legacy systems and disparate storage locations.
• Not trusted – Sensitive data (PII, PHI, confidential records) is often mixed in, raising compliance and privacy risks.

Why “Go” Comes First—And Why That’s a Problem

Deepak pointed out a common challenge: C-level executives are focused on immediate AI-driven results (the “Go” mindset), often overlooking the need for AI-ready data. While this urgency is understandable, it leads to rushed implementations that fail to deliver meaningful insights.

Meanwhile, Chief Data & Analytics Officers (CDAOs) believe they are already “Set” because they’ve invested in traditional data quality solutions. But as Gartner emphasized in multiple sessions, data quality does not equal AI readiness. Unstructured data requires more than basic governance; it demands AI-driven analysis, classification, and contextual enrichment to be truly usable.

The Missing Piece: AI-Driven Metadata Enrichment

To bridge the AI readiness gap, organizations must shift focus toward enhanced metadata. Traditional or Passive metadata—such as file name, creator, and date—offers little value when trying to extract meaningful insights. Active metadata—created specifically for AI use cases—enables AI models to discover, extract, and utilize content effectively.

Consider this scenario: A company loads travel expense reports into its AI pipeline to analyze spending trends. What if the CEO’s confidential travel expenses related to an undisclosed acquisition are included? Without proper labeling and AI-driven metadata tagging, sensitive information could be exposed—posing serious security and compliance risks.

By using AI to fully understand the meaning of unstructured content, you can ensure it is safe (devoid of private or sensitive information) and contextually correct. 

The Trust Factor: Why AI Needs Reliable Data

Both Deepak and EncompaaS agree: The missing link in AI readiness is trust. Before data enters an AI pipeline, organizations must:

• Identify and classify unstructured content.
• Enrich metadata with AI-driven tagging and labeling.
• Filter out sensitive or non-relevant data to avoid compliance risks.
• Ensure contextual accuracy so AI can generate meaningful, reliable insights.

Without this trust layer, AI cannot deliver the results that “Go” focused executives expect. Organizations must first be “Ready”—with AI-prepared data—before they can be “Set” to launch successful GenAI initiatives.

The Path Forward: Are You AI-Ready?

At EncompaaS, we help organizations unlock the full potential of their unstructured data—ensuring it is discovered, trusted, and optimized for AI-driven success. If you’re ready to move beyond traditional data governance and truly prepare for AI, let’s connect.

Reach out to me directly or respond to this post, and we will be glad to offer insights on best practices to help your organization get Ready, Set… and then Go.