Can Deep Data Transform Industry Growth?

The COVID-19 pandemic and accompanying policy steps triggered economic disturbance so plain that advanced statistical techniques were unneeded for many concerns. Joblessness jumped dramatically in the early weeks of the pandemic, leaving little space for alternative explanations. The impacts of AI, however, may be less like COVID and more like the web or trade with China.

One common approach is to compare outcomes in between basically AI-exposed workers, companies, or markets, in order to separate the impact of AI from confounding forces. 2 Direct exposure is usually defined at the job level: AI can grade homework but not handle a class, for example, so instructors are thought about less disclosed than workers whose entire task can be performed remotely.

3 Our method integrates information from 3 sources. Task-level direct exposure price quotes from Eloundou et al. (2023 ), which measure whether it is theoretically possible for an LLM to make a task at least two times as fast.

Analyzing Market Movements in 2026

Some jobs that are theoretically possible may not show up in usage because of model constraints. Eloundou et al. mark "Authorize drug refills and provide prescription details to pharmacies" as totally exposed (=1).

As Figure 1 shows, 97% of the jobs observed throughout the previous four Economic Index reports fall into classifications rated as theoretically feasible by Eloundou et al. (=0.5 or =1.0). This figure reveals Claude use distributed across O * internet tasks grouped by their theoretical AI direct exposure. Jobs rated =1 (fully feasible for an LLM alone) account for 68% of observed Claude use, while jobs rated =0 (not practical) represent simply 3%.

Our brand-new procedure, observed exposure, is meant to measure: of those tasks that LLMs could in theory accelerate, which are actually seeing automated usage in expert settings? Theoretical capability encompasses a much broader variety of jobs. By tracking how that gap narrows, observed exposure supplies insight into financial changes as they emerge.

A job's direct exposure is higher if: Its tasks are theoretically possible with AIIts tasks see considerable usage in the Anthropic Economic Index5Its tasks are performed in job-related contextsIt has a fairly greater share of automated use patterns or API implementationIts AI-impacted jobs comprise a bigger share of the overall role6We provide mathematical information in the Appendix.

Building In-House Innovation Hubs for Better ROI

The task-level coverage steps are balanced to the occupation level weighted by the portion of time spent on each job. The procedure shows scope for LLM penetration in the bulk of tasks in Computer system & Math (94%) and Workplace & Admin (90%) professions.

Claude presently covers simply 33% of all jobs in the Computer system & Mathematics classification. There is a large exposed location too; numerous tasks, of course, remain beyond AI's reachfrom physical agricultural work like pruning trees and operating farm machinery to legal jobs like representing customers in court.

In line with other information showing that Claude is thoroughly used for coding, Computer Programmers are at the top, with 75% coverage, followed by Customer Service Agents, whose primary jobs we increasingly see in first-party API traffic. Data Entry Keyers, whose main job of checking out source files and entering information sees substantial automation, are 67% covered.

Key Growth Statistics to Watch in 2026

At the bottom end, 30% of workers have zero coverage, as their tasks appeared too infrequently in our data to fulfill the minimum threshold. This group includes, for example, Cooks, Motorbike Mechanics, Lifeguards, Bartenders, Dishwashers, and Dressing Space Attendants.

A regression at the occupation level weighted by current employment finds that growth forecasts are somewhat weaker for tasks with more observed direct exposure. For every single 10 percentage point boost in protection, the BLS's growth forecast drops by 0.6 portion points. This provides some recognition because our steps track the independently derived price quotes from labor market experts, although the relationship is small.

Each strong dot shows the average observed direct exposure and forecasted work modification for one of the bins. The dashed line reveals an easy direct regression fit, weighted by current work levels. Figure 5 programs qualities of workers in the leading quartile of exposure and the 30% of employees with zero exposure in the three months before ChatGPT was launched, August to October 2022, utilizing information from the Existing Population Study.

The more uncovered group is 16 percentage points more most likely to be female, 11 portion points most likely to be white, and nearly twice as most likely to be Asian. They earn 47% more, on average, and have greater levels of education. Individuals with graduate degrees are 4.5% of the unexposed group, but 17.4% of the most revealed group, a nearly fourfold difference.

Brynjolfsson et al.

( 2022) and Hampole et al. (2025) use job utilize task publishing Burning Glass (now Lightcast) and Revelio, respectively. We focus on joblessness as our concern outcome due to the fact that it most straight captures the potential for financial harma worker who is out of work wants a task and has not yet found one. In this case, task posts and employment do not always signal the need for policy responses; a decline in task posts for a highly exposed role may be combated by increased openings in an associated one.