Roadmap to Smarter Records Management with AI

Executive Summary

Artificial Intelligence (AI) has the potential to reshape how organizations manage electronic records. From accelerating classification and compliance to identifying risks, AI offers real solutions to modern governance challenges. While the benefits of AI are clear, success depends on how thoughtfully automation is implemented. Organizations need a strategic, actionable roadmap to adopt AI in a way that is transparent, responsible, measurable, and effective.

The Promise of LLM and AI

Much promise surrounds Large Language Models (LLM) and AI. Yesterday’s Machine Learning (ML) has been extremely helpful in easing the burden of repetitive tasks and simple review of data.  Utilizing computational infrastructure to examine large data sets has been part of information technology stacks for many years.  ML has enabled us to sift through large quantities of information and make reasoned decisions in a relatively short period.

Today’s LLMs take that further by understanding language, interpreting context, and working with unstructured content. The landscape is quickly evolving with the recent introduction of AI agents; autonomous systems capable of assisting with complex, multi-step workflows like classification, redaction, and compliance monitoring.

Tomorrow’s artificial intelligence will possess even more advanced capabilities, including the ability to automatically identify records subject to litigation holds in real time, continuously learn from user behavior to refine classification, and proactively alert staff when retention deadlines approach. Realizing that promise depends on having high-quality data, clear business rules, and proper human oversight. Organizations that lead in this space will do more than simply deploy AI; they will align it to mission needs through strategy, governance, and measurable outcomes.

Different Tools Require Different Approaches 

Newer, more powerful tools like LLM demand a more strategic approach to adoption.  With these tools, organizations can no longer afford to look at a point solution aimed at a particular issue or repository, organizations now need to consider a holistic solution aimed at organization needs and processes.  This forces a shift in focus.  It is now necessary to look at organizational information and data governance needs in total and develop a true strategic plan and roadmap to realize the greatest gains. Organizations need to cut through the noise, assess their environment, and build a roadmap ensuring AI delivers meaningful, measurable results.

From Pressure to Possibility: AI as an ERM Solution

AI and automation offer practical relief by enhancing records management tasks across the entire lifecycle. When strategically implemented, these technologies can streamline operations, improve accuracy, and free up human capital for higher-value work. Key capabilities include:

• Classification: Records officers often spend numerous hours ensuring content is placed in the right category. Automating classification reduces categorization errors and ensures consistency across repositories.
• Metadata Tagging: Records without good metadata are nearly impossible to retrieve. Automated tagging ensures critical information (dates, subjects, people) is captured upfront, improving accessibility and compliance.
• Intelligent Search: Staff waste significant time searching for records. AI-enabled search surfaces relevant results faster, reducing risk of missed records during audits or legal requests.
• Risk Identification: Unsecured or mismanaged records create exposure. AI can flag vulnerable files before they become a compliance problem.
• Compliance Monitoring: Manual compliance monitoring is a resource-intensive process. AI offers continuous oversight with the ability to generate reports demonstrating adherence to organization policies and external regulations.
• Redaction and Legal/Preservation Hold Prep: Preparing records for litigation or FOIA is time-consuming. Automated redaction saves staff time and lowers the chance of accidentally exposing sensitive data.
• ROT Detection: Redundant, obsolete, and trivial content clutters systems. Identifying ROT allows records officers to defensibly dispose of unnecessary material, cutting storage costs and risk.

These tools save time, reduce errors, and allow staff to focus on higher-value work. A Roadmap for AI implementation can help organizations bridge the gap from where they are today to where they need to be tomorrow, not just in vision but in execution and compliance. Whether an organization is just beginning their AI journey or enhancing an existing effort, a roadmap can help turn policy into action, guide technology decisions, and keep records and information governance at the forefront.

A Roadmap for Responsible Implementation

• Assessment: Identify pain points, gaps, and opportunities.
• Governance Framework: Align AI requirements with updated policies.
• Tool Selection: Identify model needs and align with available tools.
• Pilot and Train: Move toward production environments with purpose, not haste.
• Evaluate and Adapt: Continuous review and release for optimum performance.

Challenges You Will Encounter and How to Address Them.

Microsoft Purview and Industry Leading Toolsets: Finding the Right Fit

Many organizations use Microsoft 365 and its native compliance tool, Purview. Microsoft’s Purview offers integrated compliance features, but it is not the only option. Other leading platforms offer cross-platform support, deeper AI triggers, or more granular lifecycle controls. Tool selection should follow strategy, not dictate it. After assessing your organization’s needs, identify the right mix of technologies for mission success.

Conclusion: Strategic and Ethical AI

The future of records management is intelligent, adaptive, and grounded in ethical implementation. When deployed strategically, AI can help organizations meet compliance obligations, reduce manual workload, and modernize how they deliver value to customers. Tailored strategies, rather than one-size-fits-all solutions, are what deliver real results. From initial assessments to full-scale implementation, organizations can build AI-enabled ERM systems that are transparent, secure, and aligned with mission goals. A roadmap for AI implementation can help organizations achieve measurable, mission-driven outcomes.