Anthropic releases new Economic Index report showing AI use in the workplace

So far we’ve heard from Microsoft that Artificial Intelligence (AI) damaging people’s critical thinking abilities, and is reshaping the modern workplace. But until now, its impact on individual tasks and occupations has been difficult to quantify. A new report from Anthropic, the AI startup behind Claude, offers a data-driven view of how businesses and professionals are integrating AI into their work.

The Anthropic Economic Index, released this week, provides a detailed analysis of AI usage across industries, drawing from millions of anonymized conversations with Claude, Anthropic’s AI assistant. The report finds that while AI is not yet broadly automating entire jobs, it is being widely used to augment specific tasks - especially in software development, technical writing, and business analysis.

“AI usage primarily concentrates in software development and writing tasks, which together account for nearly half of all total usage,” the report states. “However, usage of AI extends more broadly across the economy, with ~36% of occupations using AI for at least a quarter of their associated tasks.”

Unlike previous studies that have relied on expert predictions or self-reported surveys, Anthropic’s research is based on direct analysis of how workers are actually using AI. The company leveraged its privacy-preserving analysis tool Clio to examine more than four million user conversations with Claude. These interactions were then mapped to occupational categories from the US Department of Labor’s O*NET database.

The data suggests that AI is playing a significant role as a collaborative tool rather than simply serving as an automation engine. In fact, 57% of AI usage in the dataset involved “augmentation,” meaning AI was assisting workers rather than replacing them. This includes tasks such as brainstorming, refining ideas and checking work for accuracy. The remaining 43% of usage fell into the category of direct automation, where AI performed tasks with minimal human involvement.

This balance between augmentation and automation is a crucial indicator of how businesses are deploying AI today.

“We find that 57% of interactions show augmentative patterns (back-and-forth iteration on a task) while 43% suggest automation (fulfilling a request with minimal human involvement),” the report states.

One of the report’s most striking conclusions is that AI is not rendering entire job roles obsolete. Instead, it is being adopted selectively, assisting with specific tasks rather than fully automating occupations.

“Only ~4% of occupations exhibit AI usage for at least 75% of their tasks, suggesting the potential for deep task-level use in some roles,” the report notes. “More broadly, ~36% of occupations show usage in at least 25% of their tasks, indicating that AI has already begun to diffuse into task portfolios across a substantial portion of the workforce.”

This selective adoption suggests that while AI is transforming work, it is not yet leading to widespread job displacement. Instead, professionals are using AI to enhance productivity, offload repetitive work and improve decision-making.

The report identifies software engineering as the field with the highest AI adoption, accounting for 37.2% of the analyzed conversations. These interactions typically involved tasks like debugging code, modifying software and troubleshooting networks.

The second-highest category of use was in creative and editorial work, including roles in media, marketing and content production (10.3% of queries). AI is widely used to draft and refine text, assist with research and generate ideas.

However, AI usage was significantly lower in fields that require physical labor, such as healthcare, transportation and agriculture. For example, only 0.1% of analyzed conversations were related to farming, fishing and forestry tasks.

This disparity highlights the current limitations of AI, which excels at text-based and analytical tasks but struggles with jobs that require hands-on work, manual dexterity or complex interpersonal interactions.

One of the most intriguing findings of the report is that AI usage does not follow a simple pattern when correlated with wages. Rather than being concentrated in either low- or high-wage jobs, AI adoption peaks in the mid-to-high salary range.

“AI use peaks in the upper quartile of wages but drops off at both extremes of the wage spectrum,” the report notes. “Most high-usage occupations clustered in the upper quartile correspond predominantly to software industry positions, while both very high-wage occupations (physicians) and low-wage positions (restaurant workers) demonstrate relatively low usage.”

This means that AI is being adopted most aggressively in roles that require analytical and technical skills but not necessarily the highest levels of specialized expertise. It also raises important questions about whether AI will exacerbate or mitigate existing economic inequalities — particularly if lower-wage workers have less access to AI’s productivity-boosting benefits.

For technical decision-makers, the report provides a roadmap for where AI is likely to have the greatest near-term impact. The data suggests that businesses should focus on AI adoption in knowledge-based professions where augmentation, rather than outright replacement, is the dominant pattern.

The report also provides an early warning for policymakers: While AI is not yet replacing entire jobs at scale, its increasing presence in high-value tasks could have a profound impact on workforce dynamics.

“AI has already begun to diffuse into task portfolios across a substantial portion of the workforce,” the report states. “While our data reveals where AI is being used today, inferring long-term consequences from these early usage trends poses significant empirical challenges.”

Anthropic has open-sourced the dataset behind its analysis, inviting researchers to further explore how AI is shaping the economy.

The Anthropic Economic Index provides one of the most comprehensive snapshots yet of how AI is being used in the workplace — not in theory, but in practice. Its findings suggest that AI is not leading to the mass job displacement that many have feared; but it is changing the nature of work in meaningful ways.

For companies, this means AI adoption isn’t just about cutting costs — it’s about unlocking new efficiencies and creativity. For policymakers, it raises urgent questions about how to ensure that AI’s benefits are distributed equitably, rather than deepening existing economic divides.

The challenge ahead lies not just in measuring these changes, but in preparing for them. If AI continues to expand its role in the workforce, the businesses and workers that learn how to use it effectively will thrive. Those who ignore it risk being left behind.