Methodology

Overview

DisruptRating evaluates public companies through two lenses: downside risk (how much revenue is at risk from AI disruption) and upside potential (how well positioned a company is to benefit from AI). We score eight proprietary factors, combine them into a single Disrupt Rating score, and classify each company into one of six quadrants.

Downside Rent Factors (5)

Each scored 1-10. Higher scores mean more protection from disruption.

Upside Factors (3)

Each scored 1-10. Higher scores mean more benefit from AI adoption.

Composite Scores

Letter Grades

Disrupt Rating scores map to letter grades using the following thresholds:

ROE Bridge Methodology

For each company, we model the impact of AI agents on return on equity (ROE). The "Agent-Adjusted ROE" represents our estimate of what ROE would be in a world where AI agents are widely deployed across the company's value chain. The difference between current ROE and agent-adjusted ROE is the "ROE at Risk" — positive values indicate margin compression from AI, while negative values indicate margin expansion.

We translate ROE impact into "Earnings at Risk" by applying the ROE delta to the company's equity base. This gives investors a dollar-denominated view of AI's potential P&L impact.

Quadrant Classification

Companies are classified into one of six quadrants based on their factor profiles, business model analysis, and relationship to AI disruption. The quadrant provides qualitative context that complements the quantitative Disrupt Rating score.