Over on the Cooley’s “Governance Beat,” Broc recently blogged about how analysts and investors use AI to review corporate earnings releases. Here’s a selection of some of the uses he identified:

Sentiment analysis: AI analyzes the tone of management’s language in earnings calls, MD&A sections and press releases. AI measures optimism, uncertainty, hedging, confidence or risk language. It can help predict stock movements based on management sentiment shifts.

Keyword and phrase tracking: Investors use AI to flag specific words or disclosures that signal risk or opportunity. For example, the terms “supply chain disruption,” “macroeconomic uncertainty” or “beat guidance” might be flagged.

Trend and anomaly detection: AI compares current earnings disclosures against past filings or peer disclosures. AI helps to identify outliers in margins, CapEx trends or unexpected shifts in accounting policies.

Financial metric extraction: AI automates the pulling of KPIs (e.g., EPS, EBITDA and revenue growth) from text, tables and footnotes. One benefit is quicker ingestion into models and dashboards without manual review.

In June, Dave blogged about how companies are responding to AI-induced pressure when it comes to the language they use in their MD&A discussions.  Based on Broc’s blog, it looks like that the same dynamic is likely at work when it comes to drafting earnings releases.

– John Jenkins