Benchmarking in the Age of AI

AI is transforming industries across the economy. How will it affect benefits administration—and what does it mean for benchmarking?

Where AI Is Appearing

Early AI applications in benefits:

Employee-facing:
• Chatbots answering benefits questions
• AI-powered plan selection tools
• Virtual assistants during open enrollment
• Natural language claims status inquiries

Administration:
• Automated claims processing
• Fraud detection
• Document processing and data extraction
• Eligibility verification

Analytics:
• Predictive modeling for healthcare costs
• Risk stratification
• Trend identification
• Anomaly detection

These applications are real but still early. Impact varies widely by implementation quality.

What AI Can't Do

Despite the hype, AI has limitations in benefits:

Judgment calls: Deciding which benefits to offer, how to structure contributions, when to change strategy—these require human judgment AI can't replicate.

Relationship management: Carrier negotiations, consultant relationships, employee communication—human skills remain essential.

Context understanding: Why does this employer value this benefit? What's the culture? What are the unspoken priorities? AI struggles with organizational context.

Data it doesn't have: AI can only work with available data. Proprietary datasets, like Bnchmrk's verified plan documents, aren't accessible to general-purpose AI.

Implications for Benchmarking

AI makes data more accessible but doesn't replace the need for good data:

What changes:
• Faster analysis of benchmarking results
• Natural language queries against datasets
• Automated report generation
• Pattern recognition at scale

What doesn't change:
• Need for verified, accurate source data
• Importance of relevant peer group selection
• Requirement for human interpretation
• Value of consultant expertise

Our Perspective

AI will make our platform more powerful, not obsolete. We're exploring AI applications for:

• Faster data extraction from plan documents
• Natural language benchmarking queries
• Automated insight generation
• Pattern detection across the dataset

But the foundation—verified data from actual employer documents—remains unchanged. AI makes it easier to use good data; it doesn't create good data from nothing.

The Bottom Line

Benefits professionals should embrace AI tools that make them more effective while recognizing the enduring value of human judgment, relationships, and trustworthy data.

The consultants who thrive will be those who use AI as a force multiplier, not those who fear it or over-rely on it.