What are the best AI tools for summarizing US earnings calls?

VerityData, FactSet Transcript Intelligence, and AlphaSense are the industry leaders. They offer specialized finance-tuned models that outperform general chatbots.

How accurate are AI summaries compared to manual review?

Finance-specific models are highly accurate for data extraction (revenue, EPS) and generally achieve 70-90% alignment with human analysts on sentiment. However, human review is still recommended for complex strategic nuances.

Can AI tools integrate earnings summaries with Excel financial models?

Yes. Tools like AlphaSense and specialized APIs allow for the direct export of extracted data into Excel, updating models automatically with new line items and assumptions.

Are there free AI options like ChatGPT for earnings analysis?

Yes, you can paste transcripts into ChatGPT, but it lacks the real-time access, specific training on financial jargon, and security compliance of dedicated platforms like FactSet or Verity.

How much time do AI summaries save during earnings season?

They can reduce the time required to review a call from 45-60 minutes down to 2-5 minutes, allowing analysts to cover more companies in less time.

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Summarizing Earnings Calls with AI: The 2026 Guide

ByHuzaifa Zahoor February 27, 2026February 27, 2026

The New Standard in Investment Research

AI dashboard summarizing earnings call data with holographic financial metrics

If you have ever stared at a 20-page transcript at 4:30 PM during the peak of earnings season, you know the feeling. It is a firehose of information. Management is spinning the narrative, analysts are asking multi-part questions, and the stock price is already moving before you have finished the CEO’s opening remarks. This is where summarizing earnings calls with AI has moved from a novelty to an absolute necessity.