Building trust in AI through information governance
How Iron Mountain helps agencies establish secure, AI-ready
data foundations through comprehensive lifecycle management
There’s no question that artificial intelligence is transforming how the public sector collects, processes and acts on information. But as agencies race to harness its potential, many are realizing that AI is only as strong as the data behind it. Without proper hygiene and disciplined governance, the promise of automation can quickly give way to risk.
“Whether it’s in the federal or state space, the biggest challenge for any kind of enterprise is security and privacy,” said Stephen Cho, senior director of software and digital solutions professional services at Iron Mountain. “In many ways, ChatGPT and other AI models out there are easier, because they’re dealing with public information. They don’t have to worry about segregating data based on the audience.”
For agencies managing highly sensitive data, protecting privacy while unlocking the value of information is a constant balancing act that becomes even more complex as AI enters the picture.
“With AI, you can now have a truly contextual view based on the meaning of documents and identify which documents align to certain taxonomy or categories,” Cho explained. “But they’ve not seen the precision that they’d like to see, and that’s a concern.”
STEPHEN CHO | SENIOR DIRECTOR, SOFTWARE AND DIGITAL SOLUTIONS PROFESSIONAL SERVICES, IRON MOUNTAIN
Rethinking data strategy
in the age of AI
Turning information
chaos into clarity
Building a foundation for
AI-ready data
Rethinking data strategy in the age of AI
In the early 2000s, organizations faced a similar reckoning around information management as federal and financial regulations required digital content retention and public access compliance. At the time, many agencies sought to centralize all content and records in one unified hub to meet these new regulatory demands.
“The desire to move toward a single, unified content repository was certainly there,” Cho said. “But that strategy proved difficult for many vendors, because the rise of tools like Sharepoint, email and file nets rapidly made a single repository unachievable.”
That challenge persists today, only amplified by the influx of unstructured data and limitations of traditional search methods. Identifying records has long been a manual, labor-intensive task requiring data custodians to comb through information and rely largely on keyword searches to surface what they need. AI changes that equation.
“With AI, you can now have a truly contextual view based on the meaning of documents and identify which documents align to certain taxonomy or categories,” Cho explained. “But they’ve not seen the precision that they’d like to see, and that’s a concern.”
When each decision affects mission and compliance, agencies need AI systems that are explainable and trustworthy. One of the most valuable advances in AI-enabled information management is the ability to audit and understand how models arrive at specific outcomes.
“That is really key in the federal space — to be able to align the results with the methods or the path it took to get there,” Cho said. For CIOs and CISOs, those capabilities will determine how confidently they can deploy AI in their environments.
"The benefit we have is that we manage our customers’ content, a large portion of which is physical records. That distinguishes us from other software vendors, where they provide the software, but it’s up to the customer to implement it. They don’t manage the information, whereas we do."
STEPHEN CHO | SENIOR DIRECTOR, SOFTWARE AND DIGITAL SOLUTIONS PROFESSIONAL SERVICES IRON MOUNTAIN
Turning information chaos into clarity
Agencies today contend with a patchwork of physical and digital records scattered across file rooms, cloud drives and legacy systems. To bring structure to that fragmentation, Iron Mountain draws on more than 80 years of experience managing and securing content across every format, giving it a unique vantage point at the intersection of physical storage, digital transformation and information governance.
“The benefit we have is that we manage our customers’ content, a large portion of which is physical records,” Cho explained. “That distinguishes us from other software vendors, where they provide the software, but it’s up to the customer to implement it. They don’t manage the information, whereas we do.”
That foundation underpins Iron Mountain’s Information Governance Advisory Service, a phased approach that blends consulting expertise, specialized tools and technology platforms. The service helps agencies gain visibility and control over their data, ensuring the information feeding AI systems is clean, connected and compliant from the start.
The process begins by mapping the full scope of an agency’s physical and digital information footprint. This first step is critical for identifying gaps or inconsistencies that could otherwise undermine AI accuracy.
"Oftentimes, the most important thing is really advising or understanding our customers' data," Cho said. "In the federal space, it's about understanding their data and, depending on their objectives, aligning the appropriate taxonomy in which you can catalog that information."
Building a foundation for AI-ready data
For CIOs and CISOs assessing their agency's data governance maturity, Cho's advice is straightforward: Start by enabling visibility.
"Oftentimes, when we have these opportunities in the C-suite, they're not technical," he said. "First and foremost, they want a single place where they can go and discover all their information, regardless of where it resides."
With the ability to search across the enterprise, agencies can build on that transparency to create cost-cutting efficiencies and new value streams — though getting there requires full coordination across teams and systems, Cho stated.
“The challenge has been to get them to understand that a unified approach could replace a lot of those things they've invested money in,” he said. “It's about convincing all these groups that this benefits not only the company, but them as well."
Ultimately, the agencies that will harness AI most effectively are those that invest in governance first. By strengthening data quality, structure, security and lifecycle management, organizations create the conditions for automation to thrive and deliver workflows that are efficient, reliable and mission-aligned.
“Our push is to provide that unified interface that allows you to discover across all your content,” Cho said. “We’re never going to manage every piece of an organization’s data, but our goal is to connect and manage information wherever it lives, securely, efficiently and at scale.”
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Enterprise discovery
Profiling and categorization
Iron Mountain’s team uses advanced profiling tools to classify and group content by context or topic, ensuring the same information is represented uniformly across systems. But technology is only half the challenge.
"It's not so much being able to profile the data, as it is the decision-making," Cho noted. "Each group has its own view. Some try to tackle it enterprise-wide, others let departments define their own policies, which can make things a bit muddled."
Policy alignment and implementation
Acting as both a mediator and guide, Iron Mountain works with teams to identify the best path forward and integrate data strategies accordingly. Meanwhile, Policy Center codifies the rules of engagement to support security, maintain consistent compliance with federal mandates and establish the governance controls that AI systems depend on.
“We say, ‘Based on what you want to do, here’s an example of how it’s been deployed elsewhere,’” Cho explained. “Once we have the group consensus, we’re able to implement those solutions pretty easily.”
Digitization and intelligent transformation
As agencies become more aligned, the focus shifts to sustainable tools and techniques that provide long-term governance success. Iron Mountain’s Insight® platform ingests physical and digital records, using intelligent document processing to extract metadata and classify content. This supports strong lifecycle management and unified visibility, helping AI systems access current, relevant information.
In addition to its document-level AI capabilities, Iron Mountain is layering in generative AI, large language models and agentic AI to enhance search, insight and decision-making for agencies.
This comprehensive governance framework gives agencies a secure foundation of quality data that turns enterprise information into a trustworthy asset for effective AI deployment.
Rethinking data strategy in the age of AI
Turning information chaos into clarity
Building a foundation for AI-ready data
Learn More