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The Task Graph

Understand how AI is changing work — built from public government databases with transparent methods and plain-language explanations.

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Browse roles/Human Resources Specialists
Role-specific view26 role tasks

Role summary

Human Resources Specialists

AI changes this role most around employment data, records, and first-draft communication, while interviews and people decisions stay human-led.

Recruit, screen, interview, or place individuals within an organization. May perform other activities in multiple human resources areas.

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Work impacted by AI

High AI support45%+

A large share of this role can change when AI is used for preparation, drafting, analysis, review, or workflow support.

10 tasks most likely to change

AI may reach parts of the task, not erase the task.

26 tasks have external evidence

Task-level matches are marked in the details.

Not a job-loss prediction or a claim that this work should be fully automated.

Source coverage and task evidence are shown in the task section and evidence section below.

How this estimate is calculated

The estimate averages the analyzed task-level AI impact signals for this role. Each task starts with stored task analysis, then uses direct public task evidence when an exact task match is available.

26 tasks are included; 26 have matched external task evidence. Role-level benchmarks are shown below as context, not pushed into individual task estimates.

Tasks in this role

Which tasks may change with AI support

Scan the work areas, choose a task, then inspect what changes, what stays human-led, and which source signals are attached.

List and detail viewExternal evidence

Reviewed task path

Start with the reviewed examples, then explore every task in the role.

Find tasks

26 of 26 tasks

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7 strong AI-support tasks26 tasks with direct evidence

Selected task

Analyze employment-related data and prepare required reports.

Strong AI work-change signal
Narrow automationAI impact 68%2 source signals

Why this task is shown

i

Select a node; details update below.

Selected task: Analyze employment-related data and prepare required reports.. Click a node to inspect the source path for this task.

9 path nodes2 evidence

Task

The selected work activity

Work concept

Plain-language bridge

Estimate

AI work-change read

Evidence

Matched public support

Source

Where signals came from

Evidence path

Select a node to inspect the evidence path.

Selected node

This section updates when you choose a node in the path.

Task

Analyze employment-related data and prepare required reports.

The work appears structured and repeatable enough to standardize. It relies on structured information, but interpretation still matters. Formal accountability pressure looks limited. Human interaction is limited enough that automation should be easier to adopt. This task is mostly analytical reasoning work. This task mixes technical limits with delivery constraints, so the best first move is usually narrow AI assistance rather than full automation.

Why linked

maps to

AI work-change
68%
Workflow automation
58%

Connected path

  1. Analyze employment-related data and prepare required reports.
  2. Analytical Reasoning
  3. AI work-change estimate
  4. Workflow automation estimate
  5. Anthropic Economic Index
  6. OpenAI GPTs are GPTs
  7. Anthropic Economic Index
  8. OpenAI GPTs are GPTs

Supporting details

2

Where AI reaches

2 matched public source signals are visible for this task. The AI work-change signal is strongest around information handling, drafting, analysis, checking, or repeatable digital steps.

What changes

The work appears structured and repeatable enough to standardize.

What stays human

No major automation blocker is visible from the current task data.

Next move

Start with narrow automation

Start with narrow, repeatable workflow steps where evidence, rules, and review paths are clearest.

Sources

Evidence attached to this task

2 matched

OpenAI GPTs are GPTs

Exact O*NET task-id match

high

How this source is linked

This source row is matched to the same O*NET occupation task used in The Task Graph. It is an exact task-id match, not a fuzzy text guess.

Confidence
95%
What the value means
Model exposure signal; it does not mean full task automation.

OpenAI records a high public AI source signal for this task (75 / 100). This is best read as model exposure and possible AI assistance, not as a guarantee of full automation.

View source

Anthropic Economic Index

Exact normalized task-title match

medium

How this source is linked

This source row is matched by exact task title after simple normalization such as casing, spacing, and punctuation cleanup. It is deterministic exact-title matching, not semantic inference.

Confidence
78%
What the value means
Observed-use signal; absence or low use is not the same as no future AI effect.

Anthropic records high observed AI-use penetration around matching task text (raw observed-use signal: 100 / 100). The Task Graph treats this as a cautious 55 / 100 public source signal because observed use is not a direct automation estimate.

View source

Why this signal is shown

2 external source signals matched to this task. The visible signal combines stored task analysis with matched public task evidence when a direct match exists.

Evidence trail

Work concepts

Analytical Reasoning

Evidence records

OpenAI GPTs are GPTs

OpenAI records a high public AI source signal for this task (75 / 100). This is best read as model exposure and possible AI assistance, not as a guarantee of full automation.

high

Anthropic Economic Index

Anthropic records high observed AI-use penetration around matching task text (raw observed-use signal: 100 / 100). The Task Graph treats this as a cautious 55 / 100 public source signal because observed use is not a direct automation estimate.

medium

Sources

OpenAI GPTs are GPTsAnthropic Economic IndexThe Task Graph analysis

Evidence

What the page is grounded in

The task view keeps task-level evidence close to each task. This section keeps broader role context and source records available when you want to inspect them.

Role-level benchmarks

These records describe the occupation as a whole. They provide context for the top estimate, but task-level evidence is only used on a task when it directly matches that task.

AI USAGE

ANTHROPIC

Mapped directly to this occupation.

medium

AI USAGE

MICROSOFT

Mapped directly to this occupation.

low

AI EXPOSURE

OPENAI

Mapped directly to this occupation.

high

Supporting role signals

AI EXPOSURE

INTERNAL · INTERNAL MODEL

low

ROUTINE INTENSITY

OECD · GROUP MAPPING

low

HUMAN INTERACTION LEVEL

INTERNAL · INTERNAL MODEL

medium

TASK COMPLEXITY

INTERNAL · INTERNAL MODEL

high

Occupation source records

These are the occupation records used for the role structure. Public AI evidence links are shown beside the matched task evidence above.

ONET

O*NET

View source record

Important to know

Task-level evidence can shape a task estimate only when it is matched directly to that task. Role-level benchmarks stay as context because they describe the occupation as a whole.

Task sources

Tasks

O*NET · O*NET Task Statements.txt · db_30_0_text

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