TL;DR: Legal teams are adopting specialized generative AI platforms like RelativityOne to manage escalating data volumes, which are projected to reach 221 zettabytes globally by 2026. Real-world applications from companies like Cummins Law and KPMG demonstrate that AI-driven document review reduces manual attorney hours by thousands and shrinks massive breach datasets by 90%. These efficiencies directly lower operational costs and improve legal financial management for global organizations.

How RelativityOne and Legal AI Control Corporate Costs in 2026

Global business leaders use specialized AI platforms like RelativityOne to manage the financial pressures of modern corporate litigation and compliance. According to projections from International Data Corporation (IDC), global data creation will reach 221 zettabytes in 2026, up from just two zettabytes in 2010. This surge in unstructured data means corporate legal departments must find efficient ways to analyze information without expanding their hourly legal spend. For a deeper look into budgeting, See our Full Guide. By deploying AI tools, organizations are moving away from traditional billing structures to automated workflows that secure defensible results in minutes instead of weeks.

How Does AI Reduce Corporate E-Discovery and Case Strategy Costs?

AI reduces corporate e-discovery and case strategy costs by automating the analysis of unstructured data, allowing legal teams to bypass manual document review. Traditional review processes require teams of attorneys to read thousands of transcript pages, which increases billable hours and delays strategic decisions. By replacing manual workflows with machine learning and generative models, firms can identify key facts quickly and allocate their budgets to high-value strategic analysis.

Real-World Savings at Cummins Law

Cincinnati-based law firm Cummins Law LLC experienced these cost reductions when managing a complex financial services case. The litigation involved dozens of deposition transcripts, each exceeding 200 to 300 pages. Instead of paying attorneys for hundreds of hours of manual compilation, Cummins Law partnered with Page One Legal and Bright Line Counsel to deploy Relativity aiR for Case Strategy. The generative AI tool extracted key facts from the transcripts in minutes. The legal team validated the AI outputs against the original transcripts to ensure accuracy and prevent hallucinations. This validation process allowed them to transition to a "trust and confirm" protocol. The implementation saved Cummins Law thousands of hours of attorney billable time on a single matter.

Can AI Reduce Financial Exposure in Corporate Data Breach Responses?

AI reduces financial exposure in data breach responses by identifying compromised records in large datasets, which accelerates regulatory notification and limits non-compliance penalties. Manual extraction of personally identifiable information (PII) from terabytes of unstructured files is slow and expensive, often requiring offshore review teams. AI tools isolate high-risk documents automatically, allowing corporations to meet strict regulatory deadlines and avoid costly legal disputes.

How KPMG Automated PII Discovery

Professional services firm KPMG demonstrated this efficiency when responding to a cyber incident at a global restaurant chain. The firm had to analyze 1.5 terabytes of unstructured data, consisting of over one million documents and 15 million potential breach records under tight regulatory deadlines. KPMG deployed Relativity aiR for Data Breach Response to automate the search. The software reduced the target dataset by 90%, leaving approximately 150,000 high-risk records for human review. This automation allowed KPMG to secure reliable results, meet compliance deadlines, and lower the overall cost of the breach investigation.

Automating Confidential Business Information Identification Lowers Regulatory Risk

Automating the identification of confidential business information (CBI) lowers regulatory risk by eliminating human review errors that lead to accidental disclosure or over-redaction. Over-redacting documents during regulatory requests slows down investigations and harms corporate credibility with courts and regulators. AI classification models analyze policy drafts, pricing sheets, and email threads to apply precise redactions based on context.

Cimplifi Streamlines Broad Redaction Audits

Legal service provider Cimplifi used CBI Analysis in Relativity aiR for Review to address overinclusive confidentiality designations. The firm faced a strict deadline to reassess 40,000 documents that had been flagged too broadly for confidentiality. Using the AI tool, Cimplifi categorized and analyzed the files, generating automated rationales and citations for every designation. This automated audit verified the status of the documents, removed unnecessary redactions, and ensured compliance with regulatory disclosure rules without delaying the litigation schedule. The system identified precise text matches and context clues, confirming which files contained genuine commercial secrets. This process protected proprietary intellectual property while avoiding the delays associated with manual auditing.

Legal AI shifts corporate spending from linear review to strategic advisory by automating repetitive analytical tasks and freeing up resources for higher-value counsel. As the Legal Data Intelligence initiative states, "Every legal challenge contains a legal data challenge." When corporations reduce the time spent searching for facts, they can focus their budgets on risk mitigation and trial preparation. This shift changes the relationship between corporate legal departments and outside counsel, moving from hourly billing for discovery to flat-fee or value-based billing structures.

Financial Predictability in Corporate Litigation

Corporate legal departments benefit from increased predictability when budgeting for litigation. Historically, discovery costs were highly volatile due to unpredictable document volumes. By using platforms like RelativityOne, corporate legal departments can project their e-discovery expenditures based on data volume rather than open-ended attorney billable hours. This budget certainty allows Chief Financial Officers to manage litigation reserves more effectively and allocate capital to business growth initiatives. It also allows companies to plan their legal expenses for the 2026 fiscal year with high precision, removing the financial unpredictability that typically accompanies major commercial disputes.

Key Takeaways

  • Deploy Generative AI for Case Analysis: Use tools like Relativity aiR for Case Strategy to summarize hundreds of pages of deposition transcripts in minutes, reducing billable hours and accelerating case preparation.
  • Accelerate Data Breach Response: Implement specialized AI software to shrink unstructured breach datasets by up to 90%, helping corporate legal departments meet strict regulatory notification deadlines and avoid non-compliance fines.
  • Control Confidentiality Redactions: Audit broad confidentiality designations using automated review tools to generate clear rationales, avoiding over-redaction and maintaining credibility with regulatory bodies.