Activate enterprise intelligence: Gaining a competitive edge with AI-powered document enrichment

From data transformation pains to AI-readiness gains

Across the enterprise, physical and digital data assets hold massive, untapped competitive advantages. Yet, this information is often trapped in silos, locked in unstructured formats, or is otherwise difficult to access. These assets also play a critical role in any successful AI strategy. For today’s leaders, this combination of potential and obstacle defines the data transformation journey.

The key questions are:

• How can data be made accessible in a way that is cost-effective, fast, and scalable?
• How can an organization equip itself with AI-ready data right now?

The answer lies in AI-powered document enrichment technologies like intelligent document processing (IDP) and agentic AI. IDP automates document classification and performs data extraction with high accuracy, integrating digital and physical asset management to prepare all data for AI. As a result, organizations can quickly turn unstructured data into actionable insights and empower intelligent decision-making.

Answering the AI imperative with document-centric process automation and innovation

Every IT transformation introduces complexity. Pressured to get AI solutions running, leaders must navigate between feeding applications with insufficient data and falling behind in the race for AI-driven efficiency.

A clear path forward exists. By applying AI-powered document enrichment, organizations can strategically transform their data assets. This approach facilitates the seamless integration of physical and digital content, elevates document-centric process automation, and builds a rich foundation of unstructured data for pioneering AI innovation. This strategy leads to better business outcomes, including faster processing times, reduced costs, and improved scalability.

The data transformation journey follows a clear path: unstructured data becomes structured information, which combines with other data to generate intelligence. This intelligence ultimately evolves into knowledge. This knowledge becomes the memory for AI agents, empowering them to operate as agentic AI systems that autonomously support decision-making and execute complex operational objectives. It turns AI from a concept into a digital workforce that accelerates business and overcomes challenges of scale, cost, and compliance.

This flow is only achievable with a solution that is flexible, full-featured, and secure. The solution must be user-friendly and support both model evaluation and human-in-the-loop (HITL) workflows.

Iron Mountain, a company with a decades-long reputation as the gold standard in information management, delivers on this need. Here, we will discuss key considerations, explore how the solution works, and demonstrate the return on investment (ROI) organizations see when partnering with Iron Mountain to achieve data transformation and unlock value.

Leaders building an AI strategy naturally ask fundamental questions:

• What data do we need?
• How is it stored?
• How will we manage data quality and security?
• What process adjustments are needed?
• How capable is our in-house infrastructure and expertise?
• How can we foster cross-departmental collaboration and prove ROI?

They consider these questions while designing a low-risk strategy that also provides go-to-market agility and boosts capacity for AI innovation, where digital teammates can autonomously manage entire workflows. To better understand the obstacles, we explore seven common pain points organizations face.