Make extraction pay: How can organizations maximize the value of their data and deliver ROI?

While some enterprises are already reporting AI-driven growth, the complexities of data strategy are proving a big stumbling block for many other businesses. 

Recent research by Vanson Bourne for Iron Mountain found that 93% of organizations are already using genAI in some capacity, while Gartner research suggests that genAI early adopters are experiencing benefits including increases in revenue (15.8%), cost savings (15.2%) and productivity improvements (22.6%), on average.

But on the flip side, the Vanson Bourne survey found that sourcing, protecting and preparing data from physical and digital assets was the second most significant challenge for using genAI. Another Gartner survey found that nearly half (49%) of the organizations surveyed had difficulty estimating and demonstrating the value of their AI projects. 

So, what can businesses do to maximize the value of their data, and ensure their genAI projects are delivering return on investment?

The first and most important step is to take a strategic approach, which means identifying the data being collected and stored while understanding how it ties into existing operations. 

This needs to work across both structured and unstructured data, including data held in physical documents. 

Transformative insight

According to IDC, 90% of the data generated by a business is unstructured. Yet text documents, audio, video, customer feedback, and social media content could hold key transformative insights.  

What’s more, it’s only when you have visibility into all that data that you can prioritize what to scan, retain, make more accessible, or destroy. 

By thinking strategically, businesses can identify the data that might be harnessed to optimize operations, reduce costs, and support new business opportunities as well as making it widely accessible. 

To make that work, the extracted information needs to be stored and organized in ways that make it searchable, centralized, protected and freed from departmental silos. 

This way, it’s open to analysis by genAI models and use by AI assistants. It can be queried by secure, in-house AI-chat services and made more digestible by time-saving genAI auto-summarization features.

Storage and organization need to be an ongoing process where data is identified and prioritized as it comes into business systems. 

This is where the features of Iron Mountain InSight^® Digital Experience Platform (DXP) can be so useful, with intelligent document processing capabilities that classify and extract key information from both digital and physical sources, adding searchable metadata to make it easier for genAI tools to find. 

AI-powered data enrichment and automation processes handle the brunt of the workload while reducing costs and errors, bringing all your information into a single, unified platform, complete with integrated genAI tools to securely search and deliver insights. 

And while InSight DXP comes with ready-made workflows, rules, prompts and connectors, APIs and a low-code development environment make it easy to develop bespoke workflows and genAI applications.  to support industry-specific processes or regulatory requirements, or just empower a new wave of innovation.  

To find out more about maximizing the value of your data with InSight DXP, visit www.ironmountain.com/insight