Inside an Olympic-Level Investigation

How AI and Modern Forensics Would Reshape the USA Gymnastics Case Today

Few investigations in modern sports history have carried the scale, complexity, and emotional weight of the Larry Nassar and USA Gymnastics matter. What began as individual reports of abuse ultimately revealed systemic failures across multiple organizations responsible for athlete safety, including USA Gymnastics, the U.S. Olympic Committee, Michigan State University, and oversight bodies at both the state and federal levels. 

Between 2015 and 2020, investigative teams worked through enormous volumes of evidence: electronic medical records, emails, text messages, training logs, organizational documents, device extractions, metadata, and thousands of pages of victim and witness statements. Multiple agencies conducted parallel investigations, each with its own scope, systems, and processes, adding significant operational complexity.  

Even with the digital tools available at the time, evidence processing remained labor intensive, time consuming, and heavily dependent on manual review and coordination. Today, AI, GenAI, and  forensic tools and discovery platforms would materially change how an investigation of this magnitude is executed. 

This blog explores how modern technology would reshape a case like the Nassar investigation from an investigative  and forensic perspective, and why these capabilities matter for any organization responsible for integrity, compliance, and participant safety. 

1. How the Investigation Actually Worked (2015–2020) 

Although the Nassar matter occurred in the digital era, investigative technology was  less mature than what is available today. Forensic & litigation support teams faced challenges across four primary areas:  forensic data collections, communication review, multi-agency coordination, and investigative reporting. 

A. Forensic Collections and Extractions 

Investigators worked with: 

  • Multiple phones and laptops 

  • External drives 

  • Social media platform data  

  • Email data 

  • Extracting data, recovering deleted materials, and maintaining forensic integrity often required  manual effort. Some devices had to be revisited as new leads emerged or as the  capabilities of forensic collections evolved, adding time and complexity to the investigation. 

B. Communication Review 

Reviewing organizational communications required: 

  • Manual export of large email archives, sometimes from legacy systems 

  • Untangling nested PST files and mailbox files 

  • Applying basic keyword searches with limited analytics 

  • Reviewing thousands of messages across multiple custodians 

At the time, technology offered limited ability to surface behavioral patterns, escalation failures, or risk signals across large communication sets. 

C. Multi-Agency Coordination Challenges 

Because multiple entities were involved, including: 

  •  Federal, State, and Local law enforcement agencies 

  • USA Gymnastics 

  • U.S. Olympic Committee 

  • Michigan State University 

  • Independent investigative commissions 

Each  entity operates within its own systems; this  created duplication of effort, delays in alignment, and challenges in maintaining a single, consistent factual record. 

D. Investigative Reporting 

Investigative teams were responsible for producing: 

  • Chronological narratives 

  • Issue and finding summaries 

  • Witness and victim timelines 

  • Policy and procedural analyses 

  • Detailed documentation of organizational responses 

Assembling these materials required stitching together interviews, metadata, communications, and records from multiple sources. Without automation, report development often took weeks or months. 

2. How AI, GenAI, and Modern Forensics Would Transform the Investigation Today 

If an investigation of this scope were conducted today, the most significant change would be in how quickly and clearly investigators could understand what happened, when it happened, and how organizational responses evolved. 

A. AI-Powered Forensic Triage 

Modern forensic platforms allow investigators to: 

  • Process device images in shorter periods 

  • Prioritize content using behavioral and relationship analysis 

  • Cluster communications by individual, topic, or activity 

  • Identify anomalies, gaps, or sudden shifts in communication 

  • Surface  altered content through metadata comparison 

These capabilities dramatically accelerate early-stage understanding without compromising forensic defensibility. 

B. GenAI-Assisted Investigative Reporting 

GenAI can assist investigative teams by: 

  • Drafting chronological narratives from extracted metadata 

  • Summarizing interviews and statements for review 

  • Highlighting inconsistencies or conflicting accounts 

  • Surfacing policy-related risks embedded in organizational documents 

GenAI supports investigators by reducing manual synthesis effort, while human experts validate findings and conclusions. 

C. Enterprise-Wide Discovery and Document Review 

With platforms like RelativityOne and aiR: 

  • Communications across agencies and custodians can be centralized 

  • Analytics prioritize relevant material early 

  • Privilege indicators are applied consistently 

  • Topic clustering surfaces themes such as reporting failures or internal risk awareness 

This allows investigative teams to focus on analysis rather than document logistics. 

D. Pattern and Behavior Analytics 

AI is particularly effective at: 

  • Identifying recurring complaints over extended time periods 

  • Mapping how reports were escalated or delayed 

  • Revealing inconsistencies between internal discussions and external actions 

  • Highlighting systemic issues rather than isolated incidents 

These insights are critical for understanding institutional failures, not just individual actions. 

E. Real-Time Cross-Agency Collaboration 

Secure, cloud-based discovery environments enable: 

  • Multiple investigative teams to work from the same dataset simultaneously 

  • Shared tagging, timelines, and review protocols 

  • Real-time updates as new evidence is introduced 

  • Elimination of duplicate processing and conflicting data sets 

This level of coordination significantly reduces friction across large, multi-party investigations.

3. Then vs. Now: Operational Impact of Modern Investigation Technology


Stage 2015-2020 Operations Modern Investigation Workflows
Device extraction and triage Manual and time intensive AI-assisted prioritization
Communication review Linear and custodian-based Analytics-driven
Document review Months of manual effort Weeks with early insight
Investigative reporting Manual synthesis AI-assisted drafting
Multi-agency coordination Fragmented Centralized and collaborative
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These comparisons are illustrative, but they reflect a clear shift in investigative execution: modern tools improve speed, consistency, and transparency while maintaining defensibility.  

4. Why This Case Matters for Investigations and Organizational Integrity Today 

The Nassar investigation revealed critical breakdowns in reporting structures, communication practices, and institutional accountability. Organizations today face similar risks whenever allegations, complaints, or compliance concerns arise. 

Modern forensic and discovery tools help organizations: 

  • Detect concerning behavior earlier 

  • Improve escalation and response workflows 

  • Analyze communication patterns for systemic gaps 

  • Build defensible, transparent investigative records 

  • Deliver findings with greater clarity and confidence 

These capabilities are no longer optional for organizations with legal, compliance, or oversight obligations. 

5. Where Page One Fits In 

Page One supports high-stakes investigations by combining modern forensic technology with experienced investigative execution. Members of our team have firsthand experience supporting complex, multi-agency investigations of this nature, giving us a practical understanding of the operational challenges involved. 

With modern AI and discovery workflows, we help organizations: 

  • Process and analyze large volumes of digital evidence 

  • Identify communication patterns and risk signals 

  • Produce clear, defensible timelines and findings 

  • Maintain transparency and consistency throughout investigations 

Our role is not to replace investigators, but to ensure the evidence underlying their conclusions is handled with precision, integrity, and clarity. 

Conclusion 

If the USA Gymnastics investigation occurred today, AI, GenAI, and  forensic workflows would dramatically change how the work is executed. The experience and expertise of investigators remain essential, but technology now provides the speed, structure, and defensibility required to manage large-scale investigations. 

For organizations responsible for protecting people and maintaining trust, the evolution of investigative technology has redefined what effective response looks like. By pairing advanced tools with experienced service providers, teams can respond to complex matters with greater confidence, transparency, and accountability. 

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