Benchmark Job

Mental Health Counselors

Mental Health Counselors is currently AI-resistant due to physical, trust-based, or high-judgment responsibilities.

Counsel and advise individuals and groups to promote optimum mental and emotional health, with an emphasis on prevention. May help individuals deal with a broad range of mental health issues, such as those associated with addictions and substance abuse; family, parenting, and marital problems; stress management; self-esteem; or aging.

20% exposure • High confidenceToday

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Category: Community and Social Service • Industry: Executive Offices (92)

Why this score

How we calculate

Top 3 drivers

Routine process execution: 32% task weight, 34% automation potential.
Documentation and reporting: 28% task weight, 24% automation potential.
Stakeholder communication: 22% task weight, 10% automation potential.

Top 2 blockers

Exception handling: Edge cases and accountability ownership.
Stakeholder communication: Empathy, negotiation, and situational nuance.

Confidence reasons

1,016 benchmark role descriptions are mapped across O*NET + NAICS sources.
Coverage spans 23 categories and 1,012 industries.
Adjacent role consistency band is ±2 points for this benchmark family.

Task Mix

Routine process execution (32% weight • 11 contribution)34%

High judgment, trust, or contextual complexity keeps this human-led.

Documentation and reporting (28% weight • 7 contribution)24%

High judgment, trust, or contextual complexity keeps this human-led.

Stakeholder communication (22% weight • 2 contribution)10%

High judgment, trust, or contextual complexity keeps this human-led.

Exception handling (18% weight • 0 contribution)0%

High judgment, trust, or contextual complexity keeps this human-led.

Recommended Stack

Click a stack item to open setup difficulty, time-to-value, and workflow details.

Replaceable tasks vs human tasks

AI-suitable tasks

Routine process execution34% automation potential • Workflow automation + RPA
Documentation and reporting24% automation potential • Document AI + reporting automation
Stakeholder communication10% automation potential • Template assistant + CRM automation

Human-needed tasks

Exception handlingAI struggles because edge cases and accountability ownership.
Stakeholder communicationAI struggles because empathy, negotiation, and situational nuance.
Documentation and reportingAI struggles because liability and audit-quality requirements.

Tools coverage meter

This stack covers 20% of automatable tasks.

Remaining gaps: exceptions, communication, edge cases.

Automation timeline

Current mode: Today • Exposure estimate: 20% • tools now

What to pivot into

Compare roles

Safer adjacent roles

Higher-paying adjacent roles

MathematiciansExposure: 27% • Salary: $160,000 • +$66,500 • Exposure tradeoff: +11 pts
LawyersExposure: 19% • Salary: $149,000 • +$55,500 • Exposure tradeoff: +3 pts
PhysicistsExposure: 24% • Salary: $119,500 • +$26,000 • Exposure tradeoff: +8 pts
Environmental Science Teachers, PostsecondaryExposure: 17% • Salary: $97,500 • +$4,000 • Exposure tradeoff: +1 pts
Forestry and Conservation Science Teachers, PostsecondaryExposure: 17% • Salary: $97,500 • +$4,000 • Exposure tradeoff: +1 pts
Special Education Teachers, PreschoolExposure: 17% • Salary: $97,500 • +$4,000 • Exposure tradeoff: +1 pts

Related roles

Environmental Science Teachers, Postsecondary17% exposure • Educational Instruction and Library
Forestry and Conservation Science Teachers, Postsecondary17% exposure • Educational Instruction and Library
Special Education Teachers, Preschool17% exposure • Educational Instruction and Library
Physics Teachers, Postsecondary18% exposure • Educational Instruction and Library
Health Specialties Teachers, Postsecondary19% exposure • Educational Instruction and Library
Lawyers19% exposure • Legal

Examples of automations

Scheduling automation examples

Capture requests from form/email into one queue
Auto-propose slots using Scheduling automation
Send reminders and update status automatically
Escalate conflicts to a supervisor with context

Reporting automation examples

Aggregate daily operations into one reporting table
Generate dashboards with Reporting automation
Create weekly summary narratives with risk flags
Distribute summaries by role with required actions

Communication templating examples

Classify inbound messages by intent and urgency
Draft replies with Communication copilot
Insert policy-approved language and context snippets
Queue sensitive drafts for manager approval

Escalation handling examples

Detect exception triggers from job events
Route to specialist based on severity policy
Attach timeline, customer context, and prior actions
Track closure and feed outcomes into playbooks

Benchmark data source

Last updated: March 4, 2026

Benchmarked descriptions used: 1,016 role descriptions mapped across 1,012 industries.

Data references for this role

Role profile and task mix
Job title, SOC 21-1014.00, role description, task statements, and job-zone context.
Source: O*NET Database 29.0 (Occupation Data + Job Zones) • O*NET Resource Center / U.S. Department of Labor
Industry and sector mapping
Industry code 921110, sector 92, and category mapping shown on this role.
Source: NAICS 2022 6-Digit Codes • U.S. Census Bureau
Exposure score, confidence, and timeline views
Deterministic benchmark scoring, confidence tiers, stack coverage, and timeline projections derived from role/task inputs.
Source: replaced.fyi methodology • replaced.fyi
Related roles and pivot recommendations
Adjacent-role comparisons and safer/higher-pay pivot suggestions computed from the same benchmark catalog.
Source: replaced.fyi rankings dataset • replaced.fyi

Primary source list

O*NET Database 29.0 (Occupation Data + Job Zones) • O*NET Resource Center / U.S. Department of Labor
NAICS 2022 6-Digit Codes • U.S. Census Bureau

Confidence definition: High confidence means broad role coverage, benchmark consistency across adjacent roles, and stable task-level scoring signals.

Methodology • Rankings