The unstructured goldmine: How GBS leaders are turning data chaos into strategic advantage

Leaders in Shared Services and Global Business Services (GBS) are sitting on goldmines of unstructured data, yet most of the value remains out of reach. Locked in documents, scattered across systems, and riddled with risk, this data can’t drive efficiencies or fuel digital initiatives.

The pressure grows with each advance in generative and agentic AI. Companies must extract value from their data while laying the foundations for trustworthy, scalable AI. As McKinsey advises organizations to shift from scattered AI experiments to strategic programs, unstructured data stands in the way. 

Resolving the data dilemma

No conversation about AI is complete without calling out unstructured data. For Shared Services and GBS, that discussion inevitably leads to the back office, where unstructured data often creates bottlenecks. 

Back‑office teams across finance, HR, procurement, operations, and compliance rely heavily on documents: PDFs, emails, contracts, memos, and scanned forms. When the information inside these documents remains unstructured and unmanaged, it can’t effectively power AI use cases. It also can’t support end‑to‑end workflow automation or deliver the insights needed for better decision‑making.

So, what can GBS leaders do? The path forward has two key components.

• Accelerate value realization: Turn data from siloed systems into a unified knowledge layer that can drive smarter business operations. Unstructured data stops being a liability and becomes an asset. 
• Automate risk detection and remediation: Upgrade operations with the ability to autonomously detect non-compliance issues and automatically initiate action. This establishes a rapid and defensible pathway to risk reduction.

What’s possible and what’s at stake?

AI fuels innovation, opening the door to smarter operations and more satisfying customer experiences, but only for those who can clean up their back-office messes. The business advantages are huge, and the cost of inaction is just as great. 

1. Faster decisions and more time for meaningful work through automated content analysis

When AI can access unstructured data at scale, teams gain instant clarity from information that used to take hours or days to review. Today, AI can handle large volumes of unstructured data, automatically pulling out designated information and summarizing content. Natural language processing and computer vision can help automate sentiment analysis, speech-to-text conversion, and image recognition. These capabilities allow quicker decisions and more responsive operations. Without them, slow manual processes limit agility. 

2. Sharper foresight and smarter choices with predictive and prescriptive analytics

By combining unstructured and structured data, companies improve their predictive analytics, making it easier to anticipate trends and risks, and identify opportunities. AI can spot patterns in documents, conversations, images, and reports that humans would never see. Unstructured data also powers prescriptive analytics, suggesting the best actions to achieve better outcomes. Without it, blind spots persist and early signals go unnoticed, giving competitors an edge.

3. Natural, personalized customer experiences through enhanced interaction

Unstructured data provides the foundation for intelligent chatbots and intuitive virtual assistants that can interpret and respond to natural language. These AI-driven tools can analyze interactions, provide personalized recommendations, and solve problems autonomously. They can understand context and respond naturally in real time. This makes customer service not only faster but also more effective. Without the right data, companies are left with generic, scripted interactions that feel outdated and require more human intervention.

4. Stronger protections and more efficient operations

When unstructured content is made ready for AI analysis, it can quickly reveal risks before they escalate. For example, AI sifts through regulatory filings, news articles, and social media to spot compliance issues or signs of fraud. When unstructured data feeds automation, document-heavy workflows transform into streamlined operations. If the data remains inaccessible, risk increases along with operational drag.

5. A foundation for true automation and innovation

A recent survey of GBS organizations revealed that the majority are increasingly focused on developing next-gen capabilities and accelerating digital initiatives. A critical step will be to organize and govern data. This is what enables automation and AI applications to scale across the business and not languish in isolated pilots. If companies don’t make this shift, they limit their ability to compete in an AI-driven economy.

Proof points: Leading organizations move beyond simple automation

Once data governance is in place, agentic AI and other innovations can be deployed. These evolutions in AI move beyond generating content and automating processes to reasoning and executing tasks autonomously. 

For information professionals, the era presents specific opportunities. It’s a chance to rethink how workflows are designed and executed. Each AI-driven process invites stronger governance with oversight, accountability, and policy enforcement. Each technological advance further accelerates progress in human-AI collaboration. 

“Always start with the people, always start with the processes first, and then you back your way into the technology bits,” advises Swami Jayaraman, SVP and Enterprise CTO at Iron Mountain. 

Leading organizations partner with Iron Mountain, leveraging the information management technology and professional services to achieve this next level of AI-readiness. Consider the real-world outcomes:

• A global IT company made its data audit-ready and AI-ready worldwide, increasing efficiencies 70X and transforming its data management.
• A national consumer retailer automated its HR processes to increase efficiency and streamline workflows.
• A national leader in payment management solutions expanded its processing footprint while enhancing security and compliance to protect client data and transactions.

Iron Mountain’s software and services are designed to tackle information lifecycle management with end-to-end workflows across GBS domains. The Iron Mountain platform leverages the latest advancements in AI, including generative and agentic AI. For leaders in Shared Services and GBS, the path forward is clear. Those who can tame their unstructured data today will be the ones to scale AI with confidence tomorrow. By transforming data chaos into an AI-ready foundation, they unlock the data goldmine and extract real value.

Discover how Iron Mountain InSight DXP can help you unlock the full potential of your unstructured data and build a foundation for AI-driven innovation.