How an Olympic Trademark Battle Would Look in the Age of AI
What the SFAA v. USOC Case Teaches Us About Speed, Precision, and Modern eDiscovery
In the late 1980s, a dispute over the use of the word “Olympic” became a widely cited Supreme Court case illustrating how organizations protect valuable brands through statutory rights and enforcement mechanisms. San Francisco Arts & Athletics (SFAA), organizers of an LGBTQ athletic event, attempted to use the name “Gay Olympics.” The United States Olympic Committee (USOC) objected, relying on a federal statute granting it unique protections over Olympic-related marks. The case, SFAA v. USOC, ultimately reached the Supreme Court, which sided with the USOC.
While the legal outcome is well known, the operational reality of litigating this type of dispute in the 1980s tells an even more compelling story. The case highlights how much time, effort, and manual coordination were required before modern discovery platforms, analytics, and AI existed. If this dispute unfolded today, the legal questions might be similar, but the workflows supporting them would be fundamentally transformed.
This case provides a useful lens for understanding how AI, generative AI, and modern eDiscovery platforms have reshaped the way legal teams and their service providers manage complex, high stakes matters involving branding, sponsorships, and enforcement.
1. What the Litigation Operations Looked Like in the 1980s
When SFAA and the USOC litigated their dispute, service providers and litigation support teams operated in an overwhelmingly manual environment. Discovery and case preparation required extensive physical handling of information and long turnaround times.
Evidence Collection
Litigation support teams were responsible for:
Collecting printed marketing materials, flyers, brochures, and promotional items
Organizing letters, contracts, affidavits, and organizational records by hand
Retrieving legislative history and background materials from physical law libraries
Searching news coverage and prior brand usage through microfilm and printed archives
Although early electronic systems existed, there was no centralized digital ecosystem comparable to today’s email, collaboration platforms, cloud storage, or structured review environments. As a result, evidence collection was slow, fragmented, and labor intensive.
From a service provider perspective, collection alone could span months, with significant effort dedicated simply to locating, transporting, and organizing materials.
Research, Review, and Coordination
Workflow challenges extended beyond collection:
Review teams manually sorted and categorized documents
Exhibits were labeled, tracked, and updated physically
Communication between law firms, experts, and vendors relied on phone calls, mail, and couriers
Revisions and updates required rework rather than iteration
The absence of scalable technology meant that accuracy, consistency, and speed were constrained by human capacity and physical process.
2. How Modern eDiscovery and AI Change the Equation Today
If the SFAA v. USOC dispute were litigated today, the most dramatic changes would not be legal theory, but operational execution. Modern discovery workflows allow service providers to support legal teams with speed, structure, and defensibility that simply did not exist decades ago.
A. Evidence Collection at Scale
Modern service providers can now:
Collect data across email, documents, chat platforms, cloud repositories, and marketing systems
Preserve metadata and relationships automatically
Identify relevant branding and usage materials early in the process
What once required weeks or months of physical handling can now be executed in days through coordinated, technology-driven collection workflows.
B. Search, Analytics, and Early Insight
Advanced analytics enable teams to:
Rapidly surface references to protected terms across large data sets
Identify early drafts, internal discussions, and decision-making records
Analyze images and branding elements at scale
This early insight allows legal teams to assess risk, scope, and strategy sooner, while service providers help reduce downstream cost and delay.
The research process that previously took weeks could be completed in minutes with greater clarity and depth.
C. AI-Driven Review and Case Organization
With modern platforms such as RelativityOne and AI capabilities like aiR:
Documents are prioritized using analytics rather than linear review
Communications are grouped by topic, theme, or issue
Privilege indicators are surfaced earlier and more consistently
Timelines and fact patterns are generated dynamically
AI does not replace human judgment, but it dramatically improves consistency, transparency, and efficiency when combined with experienced review and project management teams.
D. Trial and Hearing Readiness
Once review is complete, modern workflows support:
Automated timelines based on document metadata and content
Rapid generation of witness summaries and deposition prep materials
Faster iteration as new facts emerge
For service providers, this means supporting legal teams with structured, defensible outputs rather than raw document piles.
3. A Side-by-Side Timeline: 1980s Litigation vs Modern AI Workflows
| Stage | 1980s Operation | Modern eDiscovery Operations |
|---|---|---|
| Evidence collection | Manual, physical, fragmented | Centralized, digital, scalable |
| Search and filtering | Manual sorting | Analytics and AI-assisted |
| Document review | Linear, time intensive | Prioritized and clustered |
| Case Organization | Static and manual | Dynamic and continuously updated |
| Overall readiness | Months of preparation | Weeks with earlier insight |
These comparisons are illustrative, but the direction is consistent across modern discovery matters: technology-enabled workflows reduce manual effort, improve defensibility, and allow teams to focus on strategy rather than logistics.
4. Why This Still Matters for Legal Teams and Their Providers
Brand protection and enforcement matters continue to arise, especially around major global events and sponsorship cycles. What has changed is the expectation for speed, accuracy, and defensibility.
Modern legal teams rely on service providers to:
Execute collections cleanly and defensibly
Manage large, diverse data sets efficiently
Apply analytics and AI responsibly
Deliver organized, review-ready outputs
The value of a service provider today is not just technology access, but the ability to operationalize that technology at scale.
5. Where Page One Fits In
Page One operates at the intersection of technology and execution. By combining modern eDiscovery platforms with experienced project management and defensible workflows, we help legal teams:
Gain early clarity into complex matters
Reduce friction across discovery phases
Maintain consistency and transparency throughout review
Move faster without sacrificing accuracy
In matters like high-profile branding and enforcement disputes, success depends on how efficiently evidence is handled, not just how arguments are made.
Conclusion
If the SFAA v. USOC case were litigated today, the most profound difference would not be the law itself, but how the work gets done. Modern eDiscovery and AI have transformed discovery from a bottleneck into a strategic advantage.
For legal teams and the service providers who support them, the evolution of technology has redefined what is possible. With the right workflows and partners, even the most complex disputes can be managed with clarity, confidence, and speed.