AI and Productivity: What Firms Are Saying on Earnings Calls

By  ,  Aakash Kalyani ,  Nicholas Sullivan

Since the release of ChatGPT in late 2022, artificial intelligence (AI) has been widely expected to raise productivity. But aggregate productivity data have so far offered a more muted signal: Utilization-adjusted total factor productivity grew only 0.07% over the four quarters ending with the first quarter of 2026.This reading, from the San Francisco Fed, reflects the June 4, 2026, update, which was current as of July 20, 2026. In this blog post, we use quarterly earnings calls to measure how business executives discuss productivity, AI and the timing of expected productivity improvements.

AI Productivity in Business Executives’ Own Words

Our analysis draws on about 490,000 earnings call transcripts from S&P Global covering 5,198 publicly traded U.S. firms from 2000 through 2025. Earnings calls are useful for this purpose because they occur regularly, cover a broad set of firms, and provide a comparable window into how managers discuss performance, costs, investment and expectations over time.

Finding and interpreting corporate productivity discussions inside millions of sentences of text require a two-step approach:

• First, we scanned every earnings call transcript and extracted each sentence containing words related to productivity—such as “productive” and “efficiency”—along with the sentences immediately before and after for context. This step is intentionally broad; it will catch some irrelevant uses, such as a reference to a “productive meeting.”
• Second, we passed each matched sentence and its context to an open-source large language model (LLM), Qwen3-3B, which extracted several key pieces of information. The LLM determined whether the discussion also involved AI; whether the firm described productivity as rising, falling or unchanged; and whether the speaker was describing something that had already happened, was happening then or was expected in the future. Sentences that turned out not to be about firm productivity were flagged and dropped.

The result was a sentence-level dataset of roughly 910,955 tagged productivity sentences, each linked to a firm and quarter. This let us measure not only how often firms discussed productivity, but also whether AI-related productivity discussions differed from other productivity discussions in timing, tone and substance.

The sections that follow discuss the results of our textual analysis.

The Share of Productivity Discussions Devoted to AI Has Risen Sharply

Before we turn to AI, it is worth noting that discussion in earnings calls about productivity overall has risen during the sample period. The first figure below shows the share of sentences per transcript flagged as productivity-related, smoothed using a four-quarter trailing moving average. The series dipped sharply in 2020, especially in the early months of the COVID-19 pandemic, when earnings calls were dominated by immediate concerns about demand, supply chains and labor-market disruption. As firms moved out of crisis-management mode, productivity discussions rebounded and then continued to rise. By 2025, productivity-related sentences accounted for a larger share of earnings call transcripts than they did before the pandemic.

The composition of productivity discussions has changed even more sharply. (See the next figure.) The share of productivity-related sentences that also mention AI was near zero before ChatGPT’s debut. It rose quickly in 2023, plateaued in 2024, and then accelerated again in 2025, reaching roughly 15% of productivity sentences by the end of that year. In other words, firms are talking somewhat more about productivity overall, but more strikingly, productivity discussions are increasingly being framed through the lens of AI.

Additionally, the way firms talk about AI has evolved. To illustrate this change, we calculated the frequency of certain bigrams (two-word phrases) in our collection of identified sentences. (See the following figure.) In 2023, shortly after LLMs first came out, the most frequently used AI-related bigram was “generative AI.” Starting in 2025, the phrases “using AI” and “AI tools” grew in usage, while the passive and vague “generative AI” fell out of fashion.

AI Discussions Have Focused Largely on Expectations

A natural question is whether firms are reporting productivity gains already realized or expressing optimism about what AI will eventually deliver. The tense classification for AI-related and non-AI-related productivity sentences answers this directly.

The figure below shows most productivity discussions were forward-looking. This pattern was especially pronounced for AI-related sentences. Across all quarters from 2000 through 2025, approximately 95% of AI-related productivity sentences referred to future gains, compared with roughly three-fourths of non-AI-related productivity sentences. The same pattern appeared in both 2023 and 2025, suggesting that AI productivity discussions remained forward-looking even following the initial period after ChatGPT’s release. Firms may be investing, experimenting and reorganizing around AI today, while the measurable productivity effects remain mostly ahead.

AI Productivity Sentiment Is Overwhelmingly Positive

Executives predominantly described AI-related productivity effects in positive terms. (See the final figure.) Among non-AI-related sentences, for all quarters from 2000 through 2025, 75% described productivity as increasing, about 20% described no change, and only a small share described a decrease. AI-related sentences are even more one-sided: 95% described productivity as increasing, and the share describing a decrease was negligible. The picture that emerges is one of strong executive optimism: Firms that discuss AI and productivity in the same breath usually describe AI as a force that will make them more productive.Consistent with this sentiment, AI-positive firms have also increased investment. In a 2026 San Francisco Fed article, Aakash Kalyani and Huiyu Li used earnings call text to identify firms with positive AI sentiment and showed that, by 2025, these firms had substantially higher investment growth (PDF) than other public firms. They found that recent capital spending and research and development growth have been driven largely by AI-positive firms, especially the largest technology firms investing in AI infrastructure. Together with our evidence, this suggests firms not only are talking positively about AI’s productivity potential, but that at least some are making the investments needed to realize those gains.

Conclusion

Taken together, the evidence suggests that AI has already reshaped how firms talk about productivity, even if its effects are not yet clearly visible in aggregate productivity statistics. Executives increasingly connect productivity improvements to AI, and they do so in overwhelmingly positive terms. But these discussions remain largely forward-looking. For now, earnings calls point less to broad realized productivity gains than to a corporate sector actively investing in, experimenting with and expecting future gains from AI. We will continue to monitor whether AI-related productivity discussion in upcoming earnings calls shifts from future-tense expectations to realized gains.

Notes

1. This reading, from the San Francisco Fed, reflects the June 4, 2026, update, which was current as of July 20, 2026.
2. Consistent with this sentiment, AI-positive firms have also increased investment. In a 2026 San Francisco Fed article, Aakash Kalyani and Huiyu Li used earnings call text to identify firms with positive AI sentiment and showed that, by 2025, these firms had substantially higher investment growth (PDF) than other public firms. They found that recent capital spending and research and development growth have been driven largely by AI-positive firms, especially the largest technology firms investing in AI infrastructure. Together with our evidence, this suggests firms not only are talking positively about AI’s productivity potential, but that at least some are making the investments needed to realize those gains.