Litigation management and claims teams are under increasing pressure to review growing volumes of legal invoices accurately, consistently, and efficiently. The way organizations approach legal bill review—whether manual, rules-based automation, or software driven by artificial intelligence (AI)—directly affects cost control, operational efficiency, and oversight of outside counsel.

Understanding these differences is essential when evaluating legal bill review software and determining which approach best supports long-term legal spend management.

Manual legal bill review: Thorough but resource-intensive

Manual legal bill review relies on experienced reviewers to evaluate invoices line by line against billing guidelines and internal standards. While this approach allows for judgment and context, it becomes increasingly difficult to scale as invoice volume grows.

In practice, manual review is often:      

• Time-intensive and labor-dependent
• Prone to inconsistency across reviewers
• Limited in its ability to identify repeat patterns across firms, matters, or jurisdictions

Even skilled reviewers can miss systemic billing behaviors when review is performed invoice by invoice rather than across a broader data set.

Rules-based automation: Efficiency with limitations

Rules-based automated legal billing systems apply predefined checks to invoices, helping organizations process bills more quickly and flag clear guideline violations.

However, the data show that this approach has meaningful limitations:

• Rules must be created and maintained manually.
• Static rules struggle to adapt to changing billing behavior.
• More nuanced inefficiencies often go undetected.

While rules-based systems improve efficiency, they typically provide limited insight into broader legal spend drivers.

AI-driven legal bill review software: Scale, consistency, and insight

AI-enabled legal bill review software builds on automation by applying machine learning and advanced analytics to invoice data. Rather than relying solely on predefined rules, AI models learn from historical billing patterns to identify anomalies, inconsistencies, and emerging trends.

In related Milliman research and analysis, AI-driven legal bill review approaches are shown to:

• Apply consistent standards across all invoices.
• Scale efficiently as invoice volume increases.
• Identify patterns that manual and rules-based reviews often miss.

This enables litigation management and claims teams to move beyond transactional invoice approval and toward proactive oversight of legal spend and attorney behavior.

Why the review method matters for legal spend management

The method used to review legal invoices influences far more than processing speed. It affects:

• Consistency in enforcing billing guidelines
• Visibility into what is driving legal costs
• The ability to make informed, data-driven decisions

Organizations relying solely on manual or basic automation often lack a comprehensive view of legal spend trends. AI-driven software transforms invoice data into a strategic asset rather than a purely administrative task.

Choosing legal bill review software

When evaluating legal bill review software, organizations should consider:

• How well the solution scales with invoice volume
• Whether it adapts as billing behaviors and legal strategies evolve
• The depth of insight it provides beyond rule enforcement
• Its ability to support consistent, repeatable review outcomes

As legal and claims environments continue to grow in complexity, the data make clear that how invoices are reviewed plays a critical role in controlling costs and improving outcomes.

Milliman’s Datalytics-Defense is designed to support legal bill review by combining deep litigation data with advanced analytics and AI-driven workflows. Rather than focusing solely on invoice compliance, Datalytics-Defense helps organizations understand why costs vary and where opportunities for improvement exist.

Key differentiators include:

• Attorney-level and firm-level benchmarking based on extensive historical litigation data
• Pattern detection across matters, jurisdictions, and firms, not just individual invoices
• Objective, data-driven insight to support more informed oversight and defense strategy decisions
• Scalable analytics that complement existing billing and claims workflows

By turning legal billing data into actionable insight, Datalytics-Defense helps insurers move beyond invoice review toward more comprehensive, and ultimately more effective, legal spend management