Will AI make corporate communication sound the same?

Imagine a group of investors visiting multiple companies in the same sector to decide which one(s) they want equity in. If these companies rely heavily on artificial intelligence-assisted writing tools, each pitch might become practically indistinguishable, thus lessening the value of presentations.

This is what Jujun Huang, assistant professor of Management Information Systems (MIS) at Binghamton University's School of Management , is discovering through her research. She recently teamed up with professors from Kennesaw State University and Arizona State University to publish a paper titled “The Penalty of AI-assisted Disclosure: Language Convergence, Innovation, and Market Reaction.”

The team studied a large sample of transcripts made during quarterly earnings calls from public companies. Each consisted of two main parts: the prepared presentation and a live Q&A session.

They found strong similarities across the presentations because of the widespread availability of AI. The live Q&As, on the other hand, tended to be distinct and unique, due to the unplanned nature of the questions and responses.

“This difference is important, because it is consistent with our explanation: AI is more likely to influence communication that can be prepared, revised, and polished in advance than communication that is delivered spontaneously,” Huang said.

Huang also found that stylistic convergence is associated with more negative initial market reactions. When the language becomes more convergent, investors may perceive the disclosure as more boilerplate and infer that it contains less new or firm-specific information. As a result, the disclosure may appear less informative, leading investors to react less favorably.

“I have always been interested in how technologies such as AI change not only how we work, but also how we communicate," Huang said. “AI-assisted writing tools can make communication clearer and more efficient, but they may also smooth away the details and individual voice that make a message informative and credible. That tension is what draws me to this research.”

The next steps for Huang are to extend this research to other forms of corporate disclosure, such as annual reports, press releases, and sustainability reports, to see whether similar patterns emerge.

She hopes that her research can help understand the long-term effects of AI-assisted communication.

“I do not see this research as an argument against AI,” Huang said. “AI can be a very useful tool. The important question is how to use it thoughtfully.”