# ADP Research describes a dashboard for tracking AI and employment [Canonical reading](https://escapemeridian.com/readings/adp-research-describes-a-dashboard-for-tracking-ai-and-083fff04) ADP Research published this account on June 16, 2026, describing the Canaries Dashboard, developed with Stanford’s Digital Economy Lab to track employment patterns by occupation, age, and AI exposure. Built from a curated sample of ADP payroll data, the dashboard is intended to detect changes that may not yet appear in broader labor statistics. ADP Research reports that employment growth differs by occupation and career stage: among workers aged 22 to 25, employment in highly AI-exposed occupations has been shrinking, while the least-exposed jobs have grown. It also says occupations where AI augments work have shown more enduring employment growth than occupations where AI automates tasks. The account’s central argument is that AI’s effects on work vary by task, and that tracking those differences can help employers, workers, and policymakers make more informed decisions. ADP Research says the dashboard can help show where AI’s value and risk lie, especially where it amplifies people’s abilities. The reported patterns do not by themselves establish that AI caused the employment changes, and the account does not say whether those patterns will persist. Headline and summary by Escape Meridian, prepared by Luna from the attributed source. A source check is not independent confirmation of the source’s claims. ## Original source ADP Research · Article Original source date: Jun 16, 2026 (2026-06-16). Date basis: Date stated on the publisher’s page. Added to Escape Meridian: 2026-11-06T13:38:23.113Z. First observed: 2026-10-27T16:25:50.197Z. Retrieved: 2026-10-30T08:54:05.836Z. - [Taking the guesswork out of AI prognostications](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Limits Text as retrieved on October 30, 2026; originally published June 16, 2026. The account reports employment patterns but does not establish that AI caused them. The account does not report whether the observed patterns persist over time. ## Open question Will the reported employment differences by age, occupation, and type of AI use persist as the dashboard tracks them over time? ## Source-stated ADP Research says it collaborated with Stanford’s Digital Economy Lab to launch a career-focused measure of AI’s labor-market impact. > the Stanford Digital Economy Lab and ADP Research have collaborated to launch the first career-focused measure of AI’s impact on the labor market. - [Supporting source](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Source-stated ADP Research says the dashboard uses a curated sample of ADP payroll data to track employment across employers, workers, and occupations. > a curated sample of ADP payroll data of 25,000 employers, 4 million workers, and more than 730 occupations - [Supporting source](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Source-stated ADP Research reports that employment in highly AI-exposed occupations has been shrinking for workers aged 22 to 25, while the least-exposed jobs have grown. > For workers aged 22 to 25, employment in highly AI-exposed occupations has been shrinking by 3.8 percent a year, while the least-exposed jobs continue to grow at an annual rate of 2 percent. - [Supporting source](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Source-stated ADP Research says occupations where AI augments work have shown more enduring employment growth than occupations where AI automates work. > Occupations primed for AI augmentation have shown more enduring employment growth than occupations where AI is used to automate. - [Supporting source](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Source-stated ADP Research argues that AI’s effects on work operate at the task level and says the dashboard can support more informed decisions. > With this value in mind, the Canaries Dashboard can help employers, workers, and policymakers move from guesswork to informed decision-making to shape the future of work, one task, one occupation, and one career stage at a time. - [Supporting source](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Source and contributor context ADP Research · Publisher The publisher is identified here. No individual author has been inferred. ## Source media Media retrieval status: unchecked. ## Terms and references Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement. ## AI exposure In labor economics, how much of a job's tasks an AI system could in principle perform; it is not a forecast of job loss. - [Definition reference](https://arxiv.org/abs/2303.10130) ## TIME TIME is a news magazine publishing reporting on world affairs, business, technology and the workers behind digital services. - [Explore this context](/entities/time) - [Reference](https://time.com/) ## Editorial provenance Version 1. Publication ID: add020bb-155c-baf0-1c05-67f99f9c20cb. Prepared by openai/gpt-6-luna; grounding review by anthropic/claude-opus-5.5. Source check: uncertain by anthropic/claude-opus-5.5 on 2026-11-06T13:33:26.808Z. This checks fidelity to the source, not whether its claims are independently true. Editorial selection: accept; reasons: bridge\_admitted\_by\_model. Observation: d8843976aa751e3ee2ea5395f39fa9fd2b2a68b10929698054aeb53ca9be4a6b. Source text hash: 5043f0635f6850eba889c4895ff40c437b51dcc1f246bb30cc9bf63cb1851dda. ## Revision and source-check history ### Version 1 — 2026-11-06T13:38:23.113Z ADP Research published this account on June 16, 2026, describing the Canaries Dashboard, developed with Stanford’s Digital Economy Lab to track employment patterns by occupation, age, and AI exposure. Built from a curated sample of ADP payroll data, the dashboard is intended to detect changes that may not yet appear in broader labor statistics. ADP Research reports that employment growth differs by occupation and career stage: among workers aged 22 to 25, employment in highly AI-exposed occupations has been shrinking, while the least-exposed jobs have grown. It also says occupations where AI augments work have shown more enduring employment growth than occupations where AI automates tasks. The account’s central argument is that AI’s effects on work vary by task, and that tracking those differences can help employers, workers, and policymakers make more informed decisions. ADP Research says the dashboard can help show where AI’s value and risk lie, especially where it amplifies people’s abilities. The reported patterns do not by themselves establish that AI caused the employment changes, and the account does not say whether those patterns will persist. ## Original source ADP Research · Article Original source date: Jun 16, 2026 (2026-06-16). Date basis: Date stated on the publisher’s page. Added to Escape Meridian: 2026-11-06T13:38:23.113Z. First observed: 2026-10-27T16:25:50.197Z. Retrieved: 2026-10-30T08:54:05.836Z. - [Taking the guesswork out of AI prognostications](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Limits Text as retrieved on October 30, 2026; originally published June 16, 2026. The account reports employment patterns but does not establish that AI caused them. The account does not report whether the observed patterns persist over time. ## Open question Will the reported employment differences by age, occupation, and type of AI use persist as the dashboard tracks them over time? ## Source-stated ADP Research says it collaborated with Stanford’s Digital Economy Lab to launch a career-focused measure of AI’s labor-market impact. > the Stanford Digital Economy Lab and ADP Research have collaborated to launch the first career-focused measure of AI’s impact on the labor market. - [Supporting source](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Source-stated ADP Research says the dashboard uses a curated sample of ADP payroll data to track employment across employers, workers, and occupations. > a curated sample of ADP payroll data of 25,000 employers, 4 million workers, and more than 730 occupations - [Supporting source](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Source-stated ADP Research reports that employment in highly AI-exposed occupations has been shrinking for workers aged 22 to 25, while the least-exposed jobs have grown. > For workers aged 22 to 25, employment in highly AI-exposed occupations has been shrinking by 3.8 percent a year, while the least-exposed jobs continue to grow at an annual rate of 2 percent. - [Supporting source](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Source-stated ADP Research says occupations where AI augments work have shown more enduring employment growth than occupations where AI automates work. > Occupations primed for AI augmentation have shown more enduring employment growth than occupations where AI is used to automate. - [Supporting source](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Source-stated ADP Research argues that AI’s effects on work operate at the task level and says the dashboard can support more informed decisions. > With this value in mind, the Canaries Dashboard can help employers, workers, and policymakers move from guesswork to informed decision-making to shape the future of work, one task, one occupation, and one career stage at a time. - [Supporting source](https://www.adpresearch.com/main-street-macro/taking-the-guesswork-out-of-ai-prognostications) ## Source and contributor context ADP Research · Publisher The publisher is identified here. No individual author has been inferred. ## Source media Media retrieval status: unchecked. ## Terms and references Reference context selected by Escape Meridian; separate from source evidence. Entity mentions do not establish authorship, involvement or endorsement. ## AI exposure In labor economics, how much of a job's tasks an AI system could in principle perform; it is not a forecast of job loss. - [Definition reference](https://arxiv.org/abs/2303.10130) ## TIME TIME is a news magazine publishing reporting on world affairs, business, technology and the workers behind digital services. - [Explore this context](/entities/time) - [Reference](https://time.com/) ## Editorial provenance Version 1. Publication ID: add020bb-155c-baf0-1c05-67f99f9c20cb. Prepared by openai/gpt-6-luna; grounding review by anthropic/claude-opus-5.5. Source check: uncertain by anthropic/claude-opus-5.5 on 2026-11-06T13:33:26.808Z. This checks fidelity to the source, not whether its claims are independently true. Editorial selection: accept; reasons: bridge\_admitted\_by\_model. Observation: d8843976aa751e3ee2ea5395f39fa9fd2b2a68b10929698054aeb53ca9be4a6b. Source text hash: 5043f0635f6850eba889c4895ff40c437b51dcc1f246bb30cc9bf63cb1851dda. ### uncertain — 2026-11-06T13:33:26.808Z — anthropic/claude-opus-5.5 Publication: add020bb-155c-baf0-1c05-67f99f9c20cb attribution — pass: The page is a single ADP Research Main Street Macro piece with its own argument, including a 'My take' section. The reading attributes its claims to ADP Research and credits the collaboration with the Stanford Digital Economy Lab as the source states. No unnamed individual author is misattributed. > the Stanford Digital Economy Lab and ADP Research have collaborated to launch the first career-focused measure of AI’s impact on the labor market. summary — pass: The reading identifies the actor (ADP Research with Stanford), the tool (Canaries Dashboard), its data basis, the age-22-to-25 finding, the augmentation-versus-automation contrast and the task-level argument. 'AI exposure' is defined on the page. Augment and automate are understandable in context. The question follows from the evidence and is not leading. Omitting the modest aggregate figures and the 'first' framing does not distort the meaning. > AI acts from the bottom up, at the task level, rather than the top down. date — pass: The displayed date of June 16, 2026 is at day precision and is consistent with the piece's own scheduling note about a June 23 release. The reading does not use later material or hindsight framing, and it reports no forecast as an outcome. The evidence is a publisher page, so no archive disclosure is needed. > The NER Pulse will be released as scheduled on June 23. support — uncertain: The claims and excerpts match the source. One problem: the summary and limitations say the patterns do not establish that AI caused the employment changes. That is an unlabeled Escape Meridian caveat, and the source itself asserts the dashboard has 'already shown us AI’s effects' in high-exposure jobs. The caveat flattens the source's causal conviction rather than reporting it. Smallest repair: state that ADP Research says the dashboard has shown AI's effects, then label any causal caveat as Escape Meridian interpretation. > It has already shown us AI’s effects on software development, customer service, and other high-exposure occupations media — pass: No media is selected, and no verified media candidates were supplied, so there is no identity or relevance problem. ## Recorded references Explicit citations in public readings and public file attachments to this reading. Shared topics are not citations. Other artifact types need an explicit reference adapter. No public references recorded here yet. [Reference data (JSON)](/readings/083fff04d6084fca714920a8fe5717a1e28c63c66b35e7440a75526e00788863/references.json) ## Corrections and challenges [Send a correction or an opposing source](https://escapemeridian.com/corrections/) [JSON record](https://escapemeridian.com/readings/adp-research-describes-a-dashboard-for-tracking-ai-and-083fff04.json)