School Psychologists

19-3034.00

Median wage $95,990/yr63,940 employed (US)Rank #664 of 923 scored · top 72% by substitution

Diagnose and implement individual or schoolwide interventions or strategies to address educational, behavioral, or developmental issues that adversely impact educational functioning in a school. May address student learning and behavioral problems and counsel students or families. May design and implement performance plans, and evaluate performance. May consult with other school-based personnel.

Sub-scores

0–100 · band = confidence interval from rater disagreement

Substitution20

Exposure19

Augmentation56

Substitution — the headline: capability discounted by cost, barriers and adoption.

Exposure — technical capability alone, regardless of whether anyone deploys it.

Augmentation — how much AI assists without replacing. High here + moderate substitution = a changing job, not a disappearing one.

Tasks on the substitution scale

19 rated tasks, binned by substitution score.

Position among all scored occupations

Distribution of 923 occupation scores; the marker is this occupation.

Tasks with substitution ≥ 70

Run 1.0.0-draft.1 · computed 2026-08-05 · rater panel: claude-sonnet-5, claude-haiku-4-5-20251001 · intervals span rater disagreement.

Why this score

The five weighted dimensions of the composite, averaged across this occupation's tasks (importance-weighted, panel mean). Exact weights and formulas: /api/v1/methodology.

Task automatabilityw 35%19

panel mean rating 1.8/5 → substitution pressure 19/100

Technical feasibility todayw 20%19

panel mean rating 1.7/5 → substitution pressure 19/100

Cost vs. human wagew 15%21

panel mean rating 1.9/5 → substitution pressure 21/100

Adoption barriersw 20%inverted — strong barriers lower the score23

panel mean rating 4.1/5 (barrier strength) → substitution pressure 23/100

Sector adoption velocityw 10%19

panel mean rating 1.8/5 → substitution pressure 19/100

Task breakdown (19 tasks)

Substitution pressure per task, weighted by O*NET importance in the composite. Expand a task for the full rater audit trail — every rating, every model, every rationale.

Maintain student records, including special education reports, confidential records, records of services provided, and behavioral data.

CI 25–43 · exposure 38 · augmentation 63 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Schools are low-digitization environments with fragmented IT infrastructure; adoption of AI for regulated record-keeping is slow and pilot-focused, with most districts still relying on manual or basic EHR systems.
Sector adoption velocity	claude-sonnet-5	2/5	K-12 education, especially special education services, is a comparatively low-digitization, slow-adopting sector for AI compared to finance or professional services, with pilots emerging but limited deep integration.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist by auto-populating templates, flagging missing fields, organizing data chronologically, and suggesting record structures, which meaningfully speeds the mechanical aspects of record maintenance while the psychologist retains full responsibility and review.
Augmentation potential	claude-sonnet-5	4/5	AI tools can meaningfully speed up drafting, summarizing, and organizing behavioral data and reports, letting psychologists focus more on interpretation and decision-making while maintaining oversight.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can assist with data entry, organization, and formatting of records, the task requires legal compliance with FERPA/IDEA regulations, clinical judgment about what to record, and verification of accuracy—elements that demand human oversight and cannot be fully automated without significant liability risk.
Task automatability	claude-sonnet-5	3/5	AI can draft, format, and organize records and behavioral data logs, but final compilation of special education reports requires human judgment, verification, and legal compliance checks, limiting full end-to-end automation.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Strong legal barriers exist: FERPA, IDEA, and state licensure laws require that a qualified school psychologist or licensed professional review, certify, and maintain accountability for special education records and behavioral documentation.
Adoption barriers	claude-sonnet-5	4/5	Special education records are governed by strict confidentiality laws (FERPA, IDEA) requiring qualified professionals to prepare, verify, and be accountable for accuracy, creating strong legal and liability barriers to full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI-assisted record management tools exist but require substantial setup, compliance integration, and human oversight costs that approach or exceed the marginal cost of direct school psychologist labor for this clerical component.
Cost vs. human wage	claude-sonnet-5	3/5	AI-assisted documentation tools reduce time spent on formatting and data entry, but human oversight, data verification, and confidentiality safeguards keep overall costs only moderately lower than fully manual record-keeping.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Document management and basic record-keeping systems exist, but no off-the-shelf AI system reliably handles the full compliance, confidentiality, and clinical judgment requirements of special education records in production school settings.
Technical feasibility today	claude-sonnet-5	3/5	Existing EHR/IEP software and AI-assisted documentation tools help maintain and structure records in schools, but reliable, autonomous handling of confidential compliance-sensitive records at scale is not yet standard practice.

Collect and analyze data to evaluate the effectiveness of academic programs and other services, such as behavioral management systems.

CI 25–43 · exposure 33 · augmentation 75 · importance 4.2/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	School districts adopt data dashboards and analytics tools, but adoption is uneven and often limited to basic reporting; the specialized clinical judgment required for program evaluation means psychologists remain central to the workflow in most public and private school systems.
Sector adoption velocity	claude-sonnet-5	2/5	K-12 education is a slower-adopting sector for AI-driven analytics compared to finance or tech, with pilots more common than full production deployment for such specialized psychological program evaluation.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI-assisted data visualization, statistical summaries, flagging of outliers, and automated report generation can substantially enhance a school psychologist's productivity in interpreting large datasets and communicating findings to stakeholders while the professional retains clinical oversight.
Augmentation potential	claude-sonnet-5	4/5	AI-powered data analysis and visualization tools can substantially speed up data collection, statistical processing, and drafting of effectiveness reports while the psychologist retains interpretive and decision-making responsibility.
Task automatability	claude-haiku-4-5-20251001	2/5	Data collection and descriptive analysis of program outcomes can be partially automated (dashboards, SQL queries), but school psychologists must contextualize results within complex institutional, developmental, and behavioral frameworks that require human judgment and subjective interpretation of student performance and intervention appropriateness.
Task automatability	claude-sonnet-5	3/5	AI can process and statistically analyze educational data and generate summary reports quickly, but interpreting effectiveness in context of student needs, ethics, and program design requires human judgment that current systems cannot fully replace.
Adoption barriers	claude-haiku-4-5-20251001	4/5	School psychologists are state-licensed professionals with specific legal authority to conduct educational evaluations and interpret psychological/behavioral data; accountability and liability for program effectiveness assessments rest on the licensed practitioner, creating a hard barrier to full automation.
Adoption barriers	claude-sonnet-5	3/5	School psychologists often need credentialing for certain interpretations and recommendations, and there's institutional reliance on qualified professionals for high-stakes evaluations affecting students and IEPs.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Analytics software reduces some data-processing labor, but school psychologists' expertise in interpreting results and designing evaluation frameworks remains essential; the all-in cost of AI systems plus required professional oversight is comparable to hiring experienced school psychologists.
Cost vs. human wage	claude-sonnet-5	3/5	AI tools can cheaply handle data aggregation and statistical analysis, but the interpretive and consultative components still require paid professional time, keeping overall costs comparable.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Automated data pipeline tools and analytics software exist, but deployed products typically handle only structured data aggregation and basic reporting; the evaluation of program effectiveness requires clinical expertise and stakeholder consultation that remains largely manual in production school settings.
Technical feasibility today	claude-sonnet-5	2/5	Data analytics and BI tools are used in education, but no deployed AI product specifically performs holistic program-effectiveness evaluation for school psychology services at scale.

Promote an understanding of child development and its relationship to learning and behavior.

CI 25–34 · exposure 25 · augmentation 63 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	School districts are resource-constrained and digitization-laggard relative to information-sector employers. Adoption of AI for school psychologist functions remains minimal in production; most districts still rely on traditional psychologist staffing and supplement with basic digital resources rather than AI agents.
Sector adoption velocity	claude-sonnet-5	2/5	K-12 education and school psychology are relatively slow-adopting sectors for AI-driven interpersonal consultation work, with pilots more common in administrative tasks than direct psychoeducational communication.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist school psychologists by generating evidence summaries on child development topics, creating visual explanations, drafting parent communications, and organizing reference materials. These supports raise efficiency in content preparation, but the psychologist must retain full responsibility for understanding, messaging tailoring, and relationship-building with families and staff.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully help school psychologists prepare materials, summarize research on child development, and draft communications to parents/teachers, enhancing their efficiency while they retain the interpersonal delivery role.
Task automatability	claude-haiku-4-5-20251001	2/5	AI can generate educational content and summaries about child development concepts, but cannot meaningfully perform the core promotional task of building understanding through relationship, dialogue, and tailored communication to diverse audiences (parents, teachers, students). The task requires adaptive, interpersonal engagement that current AI systems cannot replicate at scale.
Task automatability	claude-sonnet-5	2/5	This task involves live psychoeducational communication, relationship-building, and tailoring explanations to specific children, parents, and teachers, which current AI cannot fully replace despite being able to draft educational content on child development topics.
Adoption barriers	claude-haiku-4-5-20251001	4/5	School psychologists are typically licensed professionals whose role includes legal responsibility for student welfare and informed recommendations to educators and parents. Liability, duty-of-care requirements, and the need for professional judgment and accountability create strong barriers to full automation. Human sign-off and professional credibility are often organizationally and legally necessary.
Adoption barriers	claude-sonnet-5	3/5	While no license is strictly required to explain developmental concepts, school psychologists' credentialing, trust relationships with families/staff, and institutional expectations create moderate friction against full AI substitution.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI content generation is inexpensive per output unit, but the task requires specialized professional judgment, ongoing relationship-building, and accountability that human school psychologists provide. A school district cannot substitute AI chatbots for school psychologist expertise at lower total cost while meeting actual promotional and developmental support needs.
Cost vs. human wage	claude-sonnet-5	3/5	AI can cheaply produce informational content and handouts, but the interpersonal consultation and real-time explanation components still require paid human time, keeping overall cost comparable rather than dramatically cheaper.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No mature product reliably performs this task end-to-end. While AI can produce educational materials and fact-based explanations about child development, deployed systems lack the ability to assess comprehension, adjust messaging for audience context, or engage in the sustained dialogue necessary to genuinely promote understanding among educators and families.
Technical feasibility today	claude-sonnet-5	2/5	AI products can generate general child development information or psychoeducational materials, but no deployed product reliably conducts the interactive, context-sensitive promotion of understanding required across parents, teachers, and administrators.

Provide educational programs on topics such as classroom management, teaching strategies, or parenting skills.

CI 25–30 · exposure 25 · augmentation 75 · importance 3.2/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	K–12 education sectors adopt technology slowly and remain skeptical of replacing human-delivered mental health and behavioral programs. Adoption is in pilot and supplementary stages; core program delivery remains human-led due to regulatory, parental, and professional norms.
Sector adoption velocity	claude-sonnet-5	2/5	K-12 education is a relatively slow-adopting sector for AI-driven training delivery, with pilots more common than scaled deployment.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI can significantly assist by generating curriculum materials, creating presentation slides, suggesting evidence-based strategies tailored to classroom scenarios, and providing real-time reference support. These augmentations meaningfully raise a school psychologist's productivity while keeping them in control of program design and delivery.
Augmentation potential	claude-sonnet-5	4/5	AI can significantly help school psychologists draft materials, generate slide decks, tailor content to reading levels, and brainstorm strategies, meaningfully boosting prep efficiency.
Task automatability	claude-haiku-4-5-20251001	2/5	AI can generate educational content outlines and materials, but delivering effective programs requires real-time audience adaptation, building rapport, managing group dynamics, and responding to questions—capabilities that current systems lack. Meaningful automation would require replacing the interactive, relational core of program delivery.
Task automatability	claude-sonnet-5	2/5	Designing and delivering educational programs involves live facilitation, audience adaptation, and relationship-building that current AI cannot fully replicate end-to-end, though content creation portions can be assisted.'
Adoption barriers	claude-haiku-4-5-20251001	4/5	School psychologists hold state licensure and are expected to provide direct service and program oversight; districts typically require licensed personnel to lead evidence-based interventions. Liability, accountability for program outcomes, and legal requirements for credentialed staff create substantial adoption barriers.
Adoption barriers	claude-sonnet-5	3/5	No strict licensing barrier prevents AI-assisted content, but schools and parents generally expect a credentialed professional to lead such training, creating moderate organizational and trust-based friction.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI content generation and delivery may lower the marginal cost of materials, but professional-grade program delivery still requires human facilitation, training oversight, and customization to school context. The all-in cost remains comparable to or higher than employing the human expertise.
Cost vs. human wage	claude-sonnet-5	2/5	Content generation is cheap, but delivering an interactive workshop still requires a human facilitator, so overall cost savings versus a psychologist's time are limited.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	AI systems can draft educational materials and scripts, but no deployed product reliably delivers full educational programs with the pedagogical nuance, audience engagement, and real-time responsiveness that school psychologists provide. Chatbots and content generators exist but do not perform this task reliably in school settings.
Technical feasibility today	claude-sonnet-5	2/5	AI tools can generate slides, curricula, or talking points, but no deployed product independently runs parenting or classroom-management trainings for school stakeholders reliably in production.

Conduct research to generate new knowledge that can be used to address learning and behavior issues.

CI 25–30 · exposure 25 · augmentation 63 · importance 3.0/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	School psychology adoption of AI-driven research tools is nascent; most school districts lack the technical infrastructure and research culture to pilot such systems at scale. Adoption remains concentrated in research-heavy university clinics rather than operational school settings.
Sector adoption velocity	claude-sonnet-5	2/5	Academic and applied psychology research sectors are adopting AI tools for literature review and data analysis, but full research automation remains rare and mostly pilot-stage.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can meaningfully assist with literature synthesis, data management, and statistical reporting, saving a psychologist time on routine aspects. However, the core research conceptualization and translation to school practice remain human-dependent, limiting transformative augmentation potential.
Augmentation potential	claude-sonnet-5	4/5	AI significantly boosts literature review speed, hypothesis generation, statistical analysis, and drafting, meaningfully increasing researcher productivity while humans retain control over design and interpretation.
Task automatability	claude-haiku-4-5-20251001	2/5	School psychologists must design research addressing complex, context-dependent learning and behavior issues specific to individual schools and student populations. While AI can assist with literature review, data analysis, and report generation, the core research design and problem framing require human judgment and extensive field knowledge that current systems cannot replicate autonomously.
Task automatability	claude-sonnet-5	2/5	AI can assist with literature review, data analysis, and drafting but original research design, data collection, and generating genuinely new psychological knowledge require human expertise and judgment that current AI cannot fully replace.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Research involving minors faces strict IRB approval requirements, informed consent protocols, and ethical guardrails. School districts maintain control over research conducted on students, and liability for flawed research rests with licensed professionals, creating legal and regulatory barriers to full automation.
Adoption barriers	claude-sonnet-5	3/5	No strict licensing barrier prevents AI-assisted research, but institutional review boards, research ethics standards, and professional credentialing create moderate friction around who can conduct and publish psychological research.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI-assisted analysis is inexpensive, but research design oversight, participant interaction, and synthesis of findings still require skilled psychologists. The total integrated cost (AI plus substantial human oversight) approaches or exceeds the cost of having a trained school psychologist conduct the research directly.
Cost vs. human wage	claude-sonnet-5	2/5	AI can cheaply handle literature searches and statistical analysis support, but the overall research process still requires substantial human time for design, ethics, data collection, and interpretation, keeping costs comparable to human-led work.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	AI tools exist for literature mining and statistical analysis, but no deployed system reliably conducts the full research lifecycle—from identifying locally-relevant problems, through ethical study design with minors, to generating actionable knowledge for a school context. Products lack the domain specificity and stakeholder integration required.
Technical feasibility today	claude-sonnet-5	2/5	AI research assistants and literature synthesis tools exist and are used in academic settings, but no deployed product independently conducts psychological research on learning/behavior issues end-to-end.

Interpret test results and prepare psychological reports for teachers, administrators, and parents.

CI 25–29 · exposure 25 · augmentation 63 · importance 4.4/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Schools are typically low-digitization, risk-averse sectors with strong professional licensing traditions and budget constraints. Adoption of AI-assisted reporting is pilot-stage in few districts; most continue relying on human psychologists for clinical judgment and legal accountability.
Sector adoption velocity	claude-sonnet-5	2/5	School psychology and K-12 special education services are a low-digitization, highly regulated sector with slow AI tool adoption relative to corporate professional services.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can usefully assist by auto-scoring tests, suggesting report structure, and flagging anomalies in data, allowing psychologists to focus on interpretation and clinical insight. However, the augmentation is moderate because the core interpretive task still demands deep human expertise.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully speed up drafting of report narratives, summarizing scores, and formatting language for different audiences, while the psychologist retains interpretive responsibility.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can assist with scoring standardized tests and generating initial report drafts, interpreting results requires nuanced clinical judgment about individual student contexts, development, and comorbidities that current systems cannot reliably perform end-to-end. Human psychologists must validate interpretations and tailor recommendations, preventing the 50% time-saving threshold from being met.
Task automatability	claude-sonnet-5	2/5	AI can draft narrative summaries from test scores, but valid interpretation requires clinical judgment integrating behavioral observation, context, and ethical considerations that current systems cannot reliably replicate end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	School psychologists are licensed professionals in most jurisdictions; reports must be signed by a licensed psychologist, and liability for diagnostic/clinical recommendations falls on the licensed practitioner. Legal and regulatory requirements establish hard barriers to full automation.
Adoption barriers	claude-sonnet-5	4/5	Psychological reports typically require a licensed school psychologist's professional judgment and signature, with legal/ethical accountability for interpretation accuracy.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI tools for test scoring and report templating cost hundreds to thousands annually, but require significant human oversight and clinical expertise to validate and refine outputs, keeping total system cost comparable to or higher than having a psychologist perform the task directly.
Cost vs. human wage	claude-sonnet-5	3/5	AI drafting can cut time on report writing substantially, but a licensed psychologist must still review, interpret, and sign off, limiting net cost savings.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No deployed product reliably performs full psychological report interpretation and writing in production. Automated scoring tools exist for some tests, but comprehensive clinical interpretation—synthesizing multiple data sources, contextualizing results, and generating actionable recommendations—remains research-stage or very narrow in scope.
Technical feasibility today	claude-sonnet-5	2/5	Some report-writing assistants exist for psychologists, but no deployed product independently produces clinically valid psychological interpretations at scale in schools today.

Refer students and their families to appropriate community agencies for medical, vocational, or social services.

CI 25–25 · exposure 25 · augmentation 50 · importance 3.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	School districts have low digitization of case management and referral workflows relative to other sectors; adoption of AI-assisted referral systems remains minimal and mostly pilot-stage. Most referrals still occur through manual lists, institutional knowledge, and personal outreach.
Sector adoption velocity	claude-sonnet-5	2/5	K-12 school psychology is a slow-adopting, resource-constrained sector with limited AI tool integration in casework and referral processes.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can meaningfully assist by surfacing available agencies, flagging eligibility criteria, and organizing service options by category, which reduces search friction and helps psychologists catch services they might otherwise miss. However, the core clinical matching decision remains the psychologist's.
Augmentation potential	claude-sonnet-5	3/5	AI can help by quickly surfacing relevant community resources, drafting referral documentation, and organizing case notes, improving efficiency while the psychologist retains decision authority.
Task automatability	claude-haiku-4-5-20251001	2/5	AI can help compile and present lists of local agencies and match student profiles to service categories, but the task fundamentally requires clinical judgment about appropriate referrals, family circumstances, and coordination with school systems that AI cannot reliably perform end-to-end. The human psychologist must still assess, decide, and ensure the referral is contextually sound.
Task automatability	claude-sonnet-5	2/5	Identifying and connecting families to appropriate services requires judgment about specific student/family circumstances, though drafting referral letters or compiling resource lists could be partially automated.The core relational and judgment work resists full automation.
Adoption barriers	claude-haiku-4-5-20251001	4/5	School psychologists are licensed professionals in most states; referral authority and responsibility often rest legally with the licensed psychologist. Liability for inappropriate or missed referrals creates a strong barrier to full automation, and family contact/consent is typically required.
Adoption barriers	claude-sonnet-5	4/5	School psychologists often have legal/ethical responsibilities for student welfare and confidentiality, and referrals often require professional judgment and signed documentation, creating meaningful institutional and liability barriers.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI tools for agency lookup and matching are relatively inexpensive, but the psychologist's oversight, verification, and family communication still dominates the cost structure. Overall cost savings per referral remain modest given the human expertise required.
Cost vs. human wage	claude-sonnet-5	2/5	AI could cheaply generate resource lists, but the human cost of case management, relationship-building, and liability oversight dominates total cost, keeping the ratio close to comparable.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	Limited products exist for automated referral matching; those that do rely on rule-based databases or simple keyword matching with narrow scope. No mature production system demonstrably performs reliable end-to-end referral decisions across diverse student needs, family situations, and regional service availability.
Technical feasibility today	claude-sonnet-5	2/5	No deployed product performs comprehensive case-appropriate referrals with follow-through; some resource-matching directories exist but require human validation and contextual judgment.

Provide consultation to parents, teachers, administrators, and others on topics such as learning styles and behavior modification techniques.

CI 23–25 · exposure 25 · augmentation 63 · importance 4.0/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	School psychology remains highly credential-gated and relationship-dependent; adoption of AI for primary consultation is minimal, with schools preferring to use AI only for administrative tasks or supplementary information, reflecting both regulatory caution and stakeholder preference for human expert guidance.
Sector adoption velocity	claude-sonnet-5	2/5	K-12 education is a slower-adopting sector for AI in professional consultation roles, with pilots for administrative tasks more common than for direct psychological consultation.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can usefully assist school psychologists by drafting consultation summaries, suggesting evidence-based strategies, organizing research on learning interventions, and generating talking points, thereby saving preparation time while the psychologist retains responsibility for customization and delivery.
Augmentation potential	claude-sonnet-5	4/5	AI can help school psychologists draft consultation materials, summarize research on learning styles, and suggest behavior modification frameworks, meaningfully speeding preparation while the professional retains direct interaction.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can generate generic consultation materials and talking points on learning styles and behavior modification, the task requires nuanced, context-specific, relationship-based guidance tailored to individual students, families, and organizational dynamics that current systems cannot reliably handle end-to-end. Significant human judgment, rapport-building, and follow-up adaptation remain essential.
Task automatability	claude-sonnet-5	2/5	Consultation requires synthesizing context-specific behavioral observations, building trust, and adapting advice interactively, which current AI cannot fully replicate end-to-end despite being able to draft general guidance.
Adoption barriers	claude-haiku-4-5-20251001	4/5	School psychologists are credentialed professionals whose recommendations carry legal and ethical weight; parents and administrators expect licensed expertise, and liability for advice on behavior modification and learning support falls on the qualified professional, creating strong licensing and accountability barriers to full substitution.
Adoption barriers	claude-sonnet-5	4/5	School psychologist consultations often involve confidential student information, professional licensure standards, and legal/ethical accountability, creating substantial barriers to full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI-generated consultation templates are cheap to produce, but the oversight, customization, and liability management required to integrate them safely into school psychology practice offset cost savings, making the all-in cost comparable to or higher than a school psychologist's time on many engagements.
Cost vs. human wage	claude-sonnet-5	2/5	While AI-generated informational content is cheap, the actual consultation requires human judgment, relationship management, and liability oversight, keeping effective cost comparable to or higher than automation savings.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No deployed product reliably performs personalized consultation to parents and educators on behavioral and learning interventions at scale; chatbots can provide general information but lack the diagnostic specificity, credibility, and accountability required in school contexts where recommendations affect children's welfare.
Technical feasibility today	claude-sonnet-5	2/5	AI chatbots can offer generic advice on learning styles or behavior strategies, but no deployed product reliably conducts nuanced, case-specific professional consultation with parents/teachers/administrators.

Attend workshops, seminars, or professional meetings to remain informed of new developments in school psychology.

CI 13–35 · exposure 13 · augmentation 50 · importance 3.6/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	School psychology remains a human-intensive, relationship-driven field with limited digitization in core professional development practices; organizations have shown slow adoption of fully remote or AI-mediated alternatives to live professional development engagement.
Sector adoption velocity	claude-sonnet-5	2/5	School psychology and education sectors show slow, uneven AI adoption, with professional development still largely delivered via traditional live or virtual events.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist by summarizing conference materials, flagging relevant sessions, organizing notes, or generating follow-up reading lists, moderately enhancing a psychologist's efficiency in synthesizing new developments after or alongside attendance.
Augmentation potential	claude-sonnet-5	3/5	AI can help by curating relevant sessions, summarizing content, and generating notes or follow-up materials, aiding but not replacing the attendance task.
Task automatability	claude-haiku-4-5-20251001	1/5	This task fundamentally requires human presence and subjective judgment—attending events, networking, and synthesizing novel domain knowledge require contextual understanding and social engagement that AI cannot replicate. AI cannot meaningfully replace a human's attendance and learning experience at professional events.
Task automatability	claude-sonnet-5	2/5	Attending live professional development events requires human presence and engagement; AI can summarize content but cannot substitute for attendance and participation itself.','placeholder'
Adoption barriers	claude-haiku-4-5-20251001	2/5	While there are no formal legal or licensing barriers preventing organizations from replacing this with AI-assisted summaries, strong professional norms and accreditation requirements typically expect practitioners to engage directly with ongoing professional development, creating modest organizational and cultural friction.
Adoption barriers	claude-sonnet-5	3/5	Continuing education and licensure renewal often require documented attendance at approved professional events, creating structural barriers to full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The task is fundamentally about human professional development and attendance, so AI cost comparisons are not applicable; a human must attend. Any AI supplementation (e.g., summarizing materials) is a minor overhead, not a substitute for the core task cost.
Cost vs. human wage	claude-sonnet-5	2/5	AI summarization is cheap, but the task inherently involves human attendance and networking, so cost comparison for the actual task is not favorable to AI substitution.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI system can attend live workshops or seminars, participate in discussions, or perform the full task autonomously. AI can summarize published materials or retrieve information, but that differs materially from the task of attending and learning from live professional events.
Technical feasibility today	claude-sonnet-5	2/5	AI tools exist to summarize recorded talks or papers, but no deployed product replaces attending workshops/seminars as a professional obligation.

Develop individualized educational plans in collaboration with teachers and other staff members.

CI 21–25 · exposure 25 · augmentation 63 · importance 4.4/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	School psychology remains a slow-adopting sector with fragmented digitization, budget constraints, and ingrained workflow habits. Pilot AI tools exist but production adoption for IEP authoring is minimal; regulatory and professional-culture friction slows deployment.
Sector adoption velocity	claude-sonnet-5	2/5	K-12 special education is a moderately low-digitization, highly regulated public sector with slow, cautious AI adoption compared to corporate or professional service sectors.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can meaningfully assist by organizing assessment data, suggesting IEP language templates, checking compliance checklist items, and surfacing relevant prior notes, thereby reducing rework and freeing the psychologist to focus on collaboration and judgment; however, the psychologist remains fully in the loop and must validate all output.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully assist by drafting goal language, summarizing assessment data, and suggesting accommodations, significantly speeding up the psychologist's and team's work while they retain final judgment and compliance responsibility.
Task automatability	claude-haiku-4-5-20251001	2/5	Developing individualized educational plans (IEPs) requires synthesizing assessments, legal compliance (IDEA), and collaborative negotiation with teachers and parents. While AI could draft sections from assessment data, the multistakeholder negotiation, judgment about student needs, and legal-compliance review necessitate human expertise and signature; AI cannot reliably handle the full end-to-end task at >50% time savings without material human rework.
Task automatability	claude-sonnet-5	2/5	IEP drafting involves synthesizing assessment data, legal compliance, and nuanced clinical/educational judgment about a specific child, which current AI cannot fully replicate end-to-end despite being able to help draft goal language.
Adoption barriers	claude-haiku-4-5-20251001	4/5	Strong legal barriers exist: federal IDEA law requires a qualified professional (school psychologist) to evaluate and develop the IEP, and parent/guardian consent is mandatory. Liability for misplacement or inadequate accommodations is substantial, and most districts require the licensed psychologist's signature.
Adoption barriers	claude-sonnet-5	4/5	IEPs are legally mandated documents requiring signatures from certified professionals and parental/team involvement under special education law (IDEA), creating strong regulatory and liability barriers to full automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The school psychologist's labor remains the dominant cost (licensing, liability, accountability). AI tooling adds infrastructure expense without displacing the core professional, and regulatory requirements mandate human review and signature, eliminating cost savings.
Cost vs. human wage	claude-sonnet-5	2/5	AI can cheaply generate draft text, but the overall process still requires extensive psychologist and teacher time for meetings, data review, and legal sign-off, keeping all-in costs comparable to human-driven work.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No deployed product reliably performs IEP development end-to-end in production. AI can assist with data organization or draft language, but school districts still require a licensed psychologist to author, review, and sign the IEP; current systems are research-stage or narrow assistants, not autonomous performers.
Technical feasibility today	claude-sonnet-5	2/5	Some ed-tech products offer IEP goal-writing assistance or templates, but no deployed product reliably generates full compliant, individualized IEPs collaboratively with staff at scale.

Compile and interpret students' test results, along with information from teachers and parents, to diagnose conditions and to help assess eligibility for special services.

CI 20–25 · exposure 25 · augmentation 63 · importance 4.7/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Education, particularly special services administration, is a laggard sector for AI adoption due to budget constraints, regulatory caution, and the high-stakes nature of disability determination; while some districts pilot data tools, meaningful displacement of school psychologists' diagnostic work remains minimal.
Sector adoption velocity	claude-sonnet-5	2/5	K-12 education and school psychology are historically slow to adopt AI tools for high-stakes assessments due to regulatory, ethical, and liability constraints.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can meaningfully assist by automating test data extraction, flagging patterns in scores, organizing parent and teacher observations, and prompting systematic review of relevant criteria, reducing administrative burden and improving completeness of information synthesis without replacing the psychologist's clinical judgment.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully assist by compiling test scores, summarizing teacher/parent input, and drafting report sections, significantly speeding up the psychologist's workflow while they retain diagnostic responsibility.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can assist with data aggregation and pattern recognition in test scores, the core task requires clinical judgment synthesizing multiple qualitative and quantitative inputs, contextual understanding of individual students, and professional accountability that current systems cannot reliably replicate end-to-end at equal quality. The interpretation and diagnosis elements remain heavily dependent on human expertise.
Task automatability	claude-sonnet-5	2/5	AI can help aggregate and summarize test data, but diagnosing conditions and eligibility determinations require professional clinical judgment, cross-source synthesis, and legal accountability that current AI cannot fully replicate end-to-end.'
Adoption barriers	claude-haiku-4-5-20251001	4/5	School psychologists operate under state licensure, professional ethics codes, and federal special education law (IDEA) that place accountability and legal responsibility on the licensed practitioner; diagnosis and eligibility determinations have high error-cost asymmetry and typically require professional sign-off, creating substantial regulatory and liability barriers to full automation.
Adoption barriers	claude-sonnet-5	5/5	Special education eligibility determinations are legally regulated (e.g., IDEA) and require a credentialed school psychologist's professional judgment and signature, creating a hard licensing barrier.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	Integration of AI tools for data compilation is relatively inexpensive, but the specialized domain expertise, oversight, and liability insurance required to deploy such systems at scale remain substantial, making the all-in cost comparable to or potentially higher than the marginal human cost for this high-stakes clinical task.
Cost vs. human wage	claude-sonnet-5	2/5	AI tools can cheaply summarize data, but the human psychologist's time for judgment, interviews, and legally required sign-off remains the dominant cost, keeping overall savings modest.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No deployed product reliably performs full diagnostic interpretation and eligibility assessment for special services; existing AI tools offer limited support for scoring or data organization but lack the clinical decision-making maturity, liability coverage, and regulatory acceptance for standalone use. Research systems exist, but production-grade reliable systems are not yet established.
Technical feasibility today	claude-sonnet-5	2/5	Products exist for data aggregation and report drafting, but no deployed system reliably performs full diagnostic interpretation and eligibility determination in production without a licensed psychologist's judgment.

Select, administer, and score psychological tests.

CI 18–25 · exposure 25 · augmentation 50 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	School districts are traditionally slower to adopt automation in clinical or diagnostic roles due to regulatory constraints, liability concerns, and the importance of human-clinician relationships in assessment. Current adoption of AI for test administration in schools remains minimal.
Sector adoption velocity	claude-sonnet-5	2/5	School psychology and educational assessment are a lower-digitization, highly regulated public-sector niche with slow, cautious adoption of AI tools compared to fast-moving information/finance sectors.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist by automating routine scoring, flagging anomalies, and organizing data for interpretation, raising clinician efficiency on the administrative component. However, the core task of selecting tests and interpreting findings still requires the psychologist, limiting the scope of augmentation.
Augmentation potential	claude-sonnet-5	3/5	AI-assisted scoring, report-writing templates, and administrative support can meaningfully speed up parts of the workflow, though the core clinical judgment tasks remain human-led.
Task automatability	claude-haiku-4-5-20251001	2/5	Test administration involves adaptive decision-making based on client responses, rapport-building, and behavioral observation that AI cannot fully replicate. Scoring of objective tests can be partly automated, but interpretation of results and determining which tests to select requires clinical judgment that current AI cannot reliably perform end-to-end at equal quality.
Task automatability	claude-sonnet-5	2/5	Test selection requires clinical judgment about the student's presenting concerns, and administration often requires observing behavior and building rapport; only scoring (especially for standardized, machine-scorable instruments) is easily automated today.
Adoption barriers	claude-haiku-4-5-20251001	4/5	School psychologists are often required to hold state licensure and certification to administer and interpret psychological tests; legal and professional liability attaches to test selection and scoring decisions. Regulations typically mandate that licensed professionals conduct assessments, creating hard barriers to full automation.
Adoption barriers	claude-sonnet-5	5/5	Administration and interpretation of psychological/educational tests typically require licensure/certification and adherence to test publisher and legal/ethical standards (e.g., IDEA requirements), making unsupervised AI substitution legally impermissible.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI systems for psychological testing require significant integration with clinical workflows, human oversight of test selection and interpretation, and liability coverage. The all-in cost (inference, integration, clinical review) likely exceeds the cost of a school psychologist performing the full task.
Cost vs. human wage	claude-sonnet-5	2/5	Scoring software is cheap, but the overall task still requires a licensed psychologist's time for selection, administration, and interpretation, so total cost savings versus the human professional are limited.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	While AI can score some standardized tests computationally, no deployed product reliably handles test selection, adaptive administration, behavioral monitoring during assessment, and clinical interpretation together. Research prototypes exist but production systems in school settings remain minimal and narrow in scope.
Technical feasibility today	claude-sonnet-5	2/5	Software exists for scoring standardized tests (e.g., computer-scored achievement/IQ subtests) and is used in practice, but AI systems do not reliably select appropriate batteries or administer many tests requiring direct observation and interaction.

Collaborate with other educational professionals to develop teaching strategies and school programs.

CI 11–30 · exposure 13 · augmentation 75 · importance 4.0/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Educational institutions are slower adopters of automation compared to finance or tech; school districts have limited digitization, budgets, and change management capacity, resulting in pilot-stage rather than production-scale AI integration for instructional strategy work.
Sector adoption velocity	claude-sonnet-5	2/5	K-12 education is a comparatively slow-adopting sector for AI-driven collaboration tools, with pilots emerging but limited integration into interpersonal professional processes.
Augmentation potential	claude-haiku-4-5-20251001	4/5	AI can substantially augment school psychologists by generating evidence-based strategy drafts, summarizing research on interventions, and organizing stakeholder input, allowing the human professional to focus on high-judgment consensus-building and tailoring to local context.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully assist by drafting strategy documents, summarizing student data, and suggesting evidence-based interventions that professionals then discuss and refine together.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can help generate teaching strategy frameworks and program outlines, the core task requires deep understanding of individual students, stakeholder consensus, and contextual institutional knowledge that AI cannot independently synthesize into actionable strategies at scale without substantial human oversight and revision.
Task automatability	claude-sonnet-5	1/5	This is a live, interpersonal collaboration task involving negotiation, professional judgment, and relationship-building among educators, which current AI cannot substitute for end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	School psychologists operate under licensing requirements and regulatory oversight; strategy and program development require credentialed professional judgment, and schools typically prefer human accountability for educational decisions affecting student outcomes and liability.
Adoption barriers	claude-sonnet-5	3/5	No strict licensing barrier for the collaborative act itself, but school psychologists' credentialing, liability for student outcomes, and institutional norms favor human-led collaboration and oversight.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	The cost of AI systems capable of nuanced educational program design, plus the human expert time needed to validate and refine outputs, approaches or exceeds the salary cost of a school psychologist's strategic planning hours.
Cost vs. human wage	claude-sonnet-5	2/5	Human collaboration meetings and consensus-building require professional salaries with no scalable AI substitute, though AI can cheaply generate supporting drafts, keeping overall cost comparable to human-only cost.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	AI tools can draft program proposals and strategy documents, but no deployed system reliably performs the collaborative refinement and stakeholder negotiation inherent in this task; most school applications remain proof-of-concept or supplementary rather than autonomous.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs collaborative program/strategy development among educational professionals autonomously; at best AI produces draft materials that humans then discuss.

Design classes and programs to meet the needs of special students.

CI 16–25 · exposure 17 · augmentation 63 · importance 3.9/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	Educational institutions, especially special education departments, are slow to adopt AI for core program design due to regulatory constraints, risk-aversion around student outcomes, and entrenched professional practices.
Sector adoption velocity	claude-sonnet-5	2/5	Education sector, especially special education services, has historically slow and cautious AI adoption due to compliance, ethical, and data privacy concerns.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist by generating initial accommodation ideas, organizing assessment data, or drafting preliminary program templates, raising school psychologist productivity in documentation and brainstorming phases while they retain final design authority.
Augmentation potential	claude-sonnet-5	4/5	AI can meaningfully assist by drafting program outlines, summarizing assessment data, and suggesting evidence-based interventions, significantly speeding up the psychologist's planning work.
Task automatability	claude-haiku-4-5-20251001	1/5	Designing classes and programs for special students requires individualized assessment, understanding of diverse learning disabilities, and tailored pedagogical approaches that demand human judgment and contextual knowledge. Current AI cannot end-to-end replace this process with the required precision and legal compliance.
Task automatability	claude-sonnet-5	2/5	Designing individualized programs requires clinical judgment, knowledge of specific student needs, and legal compliance (IEPs), which AI cannot fully replicate end-to-end today.'
Adoption barriers	claude-haiku-4-5-20251001	4/5	Special education design is heavily regulated under IDEA and Section 504, requiring licensed school psychologists to lead IEP/504 plan development. Legal liability and mandatory professional sign-off create substantial barriers to automation.
Adoption barriers	claude-sonnet-5	4/5	Special education programming is governed by legal requirements (IDEA, IEP mandates) requiring credentialed professionals to evaluate and approve plans, creating strong regulatory and liability barriers.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI tools for educational planning are relatively inexpensive, but the task still requires significant human oversight, revisions, and professional validation, keeping total cost close to or exceeding direct human design time.
Cost vs. human wage	claude-sonnet-5	2/5	While AI drafting tools are cheap, the human psychologist's assessment, meetings, and legal sign-off remain necessary, keeping overall cost comparable to fully human-driven processes.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	While AI can generate template lesson plans or suggest accommodations, no deployed product reliably designs complete, legally-compliant special education programs from scratch. Existing tools offer narrow assistance but lack the comprehensive assessment and program design capability needed in production.
Technical feasibility today	claude-sonnet-5	2/5	Some AI tools assist with drafting IEP goals or curriculum suggestions, but no deployed product reliably designs complete special education programs autonomously in production.

Assess an individual child's needs, limitations, and potential, using observation, review of school records, and consultation with parents and school personnel.

CI 15–25 · exposure 20 · augmentation 50 · importance 4.4/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	2/5	School districts remain digitally fragmented with limited capital for automation; adoption of AI-assisted assessment tools is in pilot phase, not production at scale, and cultural reliance on human expert judgment in high-stakes decisions about children slows velocity.
Sector adoption velocity	claude-sonnet-5	2/5	K-12 education and school psychology are historically slow to adopt AI for core clinical/assessment functions, with adoption concentrated in administrative or instructional support rather than psychological evaluation.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI can assist by organizing school records, flagging risk indicators, or suggesting assessment frameworks, enabling the school psychologist to work more efficiently; however, the core diagnostic and relational work—observing the child, reading context, and building rapport—remains human-led and not fundamentally transformed by current AI tools.
Augmentation potential	claude-sonnet-5	3/5	AI can help organize school records, draft observation notes, generate consultation questions, and summarize findings, meaningfully supporting the psychologist without replacing the core judgment-based assessment.
Task automatability	claude-haiku-4-5-20251001	2/5	While AI can assist with data aggregation and pattern-spotting in school records, the core task—synthesizing observation of a child's behavior, inferring unobservable psychological states, and forming judgments about needs and potential—requires nuanced human judgment and contextual understanding that current AI cannot reliably perform end-to-end at equal quality.
Task automatability	claude-sonnet-5	2/5	This task requires in-person observation of a child, sensitive interpersonal consultation with parents and staff, and clinical judgment integrating multiple qualitative sources—AI can assist with parts (record synthesis, drafting questions) but cannot perform the core observational and relational work end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	School psychologists are typically licensed professionals; assessments of children often carry legal weight (special education eligibility, intervention planning) and liability risk, and in many jurisdictions a credentialed psychologist must sign off on or conduct the assessment itself—creating regulatory and liability barriers to full automation.
Adoption barriers	claude-sonnet-5	5/5	School psychologists must be licensed/certified, and assessments often carry legal weight (e.g., special education eligibility under IDEA), requiring a credentialed human to conduct and sign off on evaluations.
Cost vs. human wage	claude-haiku-4-5-20251001	2/5	AI screening or record-review tools have moderate deployment costs, but the full assessment task—requiring trained psychologist time for direct observation, interpretation, and consultation—remains far more economical to staff with humans than to build, integrate, and oversee AI systems at clinical-grade reliability.
Cost vs. human wage	claude-sonnet-5	2/5	While AI tools could cheaply help organize records or draft summaries, the labor-intensive observation and consultation components still require the psychologist's time, so overall cost savings versus the human-delivered service are limited.
Technical feasibility today	claude-haiku-4-5-20251001	2/5	No deployed product reliably performs comprehensive child psychological assessment independently; existing tools (screening apps, record-review aids) assist narrow sub-tasks but cannot replace the integrative diagnostic function or substitute for direct child observation and parental/educator consultation at clinical standards.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs child behavioral observation, stakeholder consultation, and holistic needs assessment; this remains firmly in the domain of licensed human professionals with no production-scale substitute.

Initiate and direct efforts to foster tolerance, understanding, and appreciation of diversity in school communities.

CI 5–5 · exposure 0 · augmentation 50 · importance 3.4/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Schools operate in heavily regulated, relationship-dependent environments with limited digital transformation. Initiatives to foster diversity and inclusion depend on human trust and organizational buy-in, which limits AI adoption velocity.
Sector adoption velocity	claude-sonnet-5	1/5	Education, particularly student support and DEI-related initiatives, shows slow AI adoption for leadership and interpersonal tasks compared to fast-adopting sectors like finance or tech.
Augmentation potential	claude-haiku-4-5-20251001	3/5	AI could assist with research synthesis on best practices, data analysis of school climate surveys, or draft communications about diversity programs. However, the human psychologist must remain central to authentic community engagement and leadership.
Augmentation potential	claude-sonnet-5	3/5	AI can help draft materials, research best practices, or analyze climate survey data to support diversity initiatives, but the core leadership and relational work remains human-driven.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires authentic relationship-building, cultural sensitivity, and judgment about human dynamics that current AI cannot replicate. The core work involves understanding context-specific community needs and directing human-led initiatives, which fundamentally depend on human judgment and presence.
Task automatability	claude-sonnet-5	1/5	This task requires initiating and leading interpersonal and cultural change efforts within a school community, which demands human leadership, relationship-building, and contextual judgment that AI cannot perform end-to-end.
Adoption barriers	claude-haiku-4-5-20251001	4/5	School psychologists hold professional licenses and are expected to build trust and model behavior within school communities. Legal and professional standards, combined with community expectations that a qualified human leads diversity initiatives, create substantial barriers to full automation.
Adoption barriers	claude-sonnet-5	4/5	This work involves professional judgment, community trust, and often legal/ethical responsibilities tied to school psychologist licensure and stakeholder relationships, creating strong barriers to automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The task is inherently labor-intensive and requires continuous human oversight. AI deployment would add cost through integration and monitoring without reducing the need for human leadership, making the all-in cost higher than direct human effort.
Cost vs. human wage	claude-sonnet-5	1/5	There is no AI substitute performing this leadership task, so cost comparison favors the human entirely; any AI use would only be a minor supplement, not a replacement of the labor.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI product can initiate or direct diversity and inclusion efforts in schools. These require leadership, stakeholder engagement, and sustained organizational change—areas where AI lacks agency and credibility with human stakeholders.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI product leads or directs diversity and inclusion initiatives in schools; this remains a human leadership function with no automation precedent in production.

Counsel children and families to help solve conflicts and problems in learning and adjustment.

CI 0–3 · exposure 0 · augmentation 38 · importance 4.3/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	School districts retain traditional staffing; AI counseling is not in production deployment in schools, and regulatory/professional standards severely limit experimental adoption.
Sector adoption velocity	claude-sonnet-5	2/5	K-12 education and school psychology services show slow, uneven AI adoption, with pilots limited mostly to administrative or screening tools rather than direct counseling.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI might assist with preliminary intake forms or suggest evidence-based frameworks, but the interpersonal depth required for therapeutic counseling—especially with vulnerable children—means augmentation is marginal at best.
Augmentation potential	claude-sonnet-5	3/5	AI can help school psychologists with case documentation, drafting intervention plans, and providing psychoeducational resources, offering moderate productivity support alongside the human-led counseling process.
Task automatability	claude-haiku-4-5-20251001	1/5	Counseling requires complex emotional intelligence, personalized relationship-building, and real-time responsiveness to human vulnerability that current AI cannot provide. No meaningful part of therapeutic conflict resolution can be automated end-to-end with equal quality today.
Task automatability	claude-sonnet-5	1/5	Counseling to resolve emotional, behavioral, and family conflicts requires trust-building, nuanced ethical judgment, and in-person relational skill that current AI cannot replicate end-to-end.npm; no product meets the 50% time-saving-at-equal-quality bar for this holistic task.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Licensing (school psychologist credentials), legal liability for mental health outcomes, and regulatory requirement that a qualified human professional deliver and sign off on counseling create hard barriers to substitution.
Adoption barriers	claude-sonnet-5	5/5	School psychologists are licensed professionals bound by ethical, legal, and confidentiality mandates (e.g., IDEA, state licensure) requiring a credentialed human for counseling and safeguarding decisions.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	AI infrastructure for counseling assistance is negligible in cost but cannot replace the core task; the loaded human wage for a qualified school psychologist far exceeds any AI service cost for equivalent outcomes.
Cost vs. human wage	claude-sonnet-5	1/5	Given the near-total lack of AI capability to perform this task, any AI cost is not offsetting a viable human-equivalent output, making the human the only real option today.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI product reliably performs therapeutic counseling independently; this work requires a licensed human clinician legally. Chatbots exist but are not substitutes for professional school psychology counseling in real practice.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product performs full child/family counseling reliably; chatbot mental-health tools remain adjunct, unregulated for this specific clinical role, and not used as substitutes for licensed practitioners.

Report any pertinent information to the proper authorities in cases of child endangerment, neglect, or abuse.

CI 0–0 · exposure 0 · augmentation 25 · importance 4.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	No sector has adopted AI for autonomous child endangerment reporting. This task sits at the intersection of legal requirement, professional ethics, and liability—adoption is effectively zero and will remain so given regulatory constraints.
Sector adoption velocity	claude-sonnet-5	1/5	School psychology and child welfare reporting are highly regulated, low-digitization contexts with essentially no AI adoption for this specific compliance-driven task.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI could modestly assist by summarizing case notes or flagging patterns in incident data, but augmentation is limited because the core task—professional judgment on what to report and to whom—depends on human discretion, legal knowledge, and accountability that AI cannot share.
Augmentation potential	claude-sonnet-5	2/5	AI could help with documentation, drafting reports, or organizing case notes, but offers minimal assistance for the core judgment and legal reporting action itself.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires professional judgment, legal knowledge, and complex human context assessment that current AI systems cannot reliably perform. AI cannot independently determine what constitutes reportable abuse, interpret state-specific mandated reporter laws, or make the discretionary legal decisions inherent in this task.
Task automatability	claude-sonnet-5	1/5	This task requires professional judgment to identify endangerment/abuse, ethical/legal responsibility to report, and direct interaction with authorities; AI cannot legally or practically perform this end-to-end today.
Adoption barriers	claude-haiku-4-5-20251001	5/5	This task has the highest legal barriers: state mandated reporter laws explicitly require designated licensed professionals (including school psychologists) to make and file reports. A licensed human must legally perform and sign off on the report; automated systems cannot substitute.
Adoption barriers	claude-sonnet-5	5/5	Mandatory reporting laws require a licensed/qualified human professional to make the determination and report abuse; this is a hard legal and ethical barrier that cannot be delegated to AI.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	The task involves legal liability and professional responsibility that cannot be outsourced to AI. Human school psychologists performing this duty have professional licensing and malpractice insurance; AI systems cannot assume these roles, making cost comparison inapplicable.
Cost vs. human wage	claude-sonnet-5	1/5	There is no viable AI substitute performing this task, so cost comparison favors the human entirely; any AI role would only be a minor documentation aid, not a replacement for the reporting act.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed product can autonomously perform the legal and ethical decision-making required to report child abuse/neglect. This remains a human professional responsibility across all jurisdictions, with AI tools at best supporting evidence compilation but not the reporting decision itself.
Technical feasibility today	claude-sonnet-5	1/5	No deployed AI product independently detects abuse cases and files mandatory reports to authorities; this remains a human professional and legal responsibility.

Serve as a resource to help families and schools deal with crises, such as separation and loss.

CI 0–0 · exposure 0 · augmentation 25 · importance 3.5/5 · click for rater detail

Panel ratings per dimension for this task
Dimension	Model	Rating	Rationale
Sector adoption velocity	claude-haiku-4-5-20251001	1/5	Adoption of AI for crisis counseling in schools remains negligible due to liability, regulatory, and ethical barriers. Schools continue to rely on licensed psychologists and counselors; no measurable displacement or pilot adoption at scale is evident in the education sector.
Sector adoption velocity	claude-sonnet-5	1/5	K-12 education and school psychological services are a slow-adopting sector for AI generally, and crisis intervention specifically sees essentially no AI deployment.
Augmentation potential	claude-haiku-4-5-20251001	2/5	AI tools could provide limited assistance—e.g., screening questionnaires, crisis resource suggestions, or documentation aids—but they cannot augment the core task of direct crisis counseling, which requires human presence, accountability, and therapeutic relationship.
Augmentation potential	claude-sonnet-5	2/5	AI might help with scheduling, resource compilation, or informational materials about grief and crisis resources, but offers minimal assistance to the core relational and clinical work involved.
Task automatability	claude-haiku-4-5-20251001	1/5	This task requires deep emotional intelligence, real-time crisis assessment, and personalized intervention tailored to individual family and school contexts. Current AI cannot reliably perform crisis counseling or replace human judgment in trauma situations where safety and therapeutic trust are paramount.
Task automatability	claude-sonnet-5	1/5	This task requires in-person emotional support, trust-building, and real-time human judgment during crisis situations that AI cannot replicate or substitute for at any meaningful scale today.
Adoption barriers	claude-haiku-4-5-20251001	5/5	Regulatory and licensing barriers are substantial: school psychologists are credentialed professionals, and legal liability for crisis mishandling is severe. Most jurisdictions require licensed humans to provide or directly oversee mental health crisis intervention; automated systems cannot fulfill this gatekeeping requirement.
Adoption barriers	claude-sonnet-5	5/5	Crisis intervention involving families and schools typically requires licensed, credentialed professionals bound by ethical and legal duty-of-care standards, creating strong professional and liability barriers to automation.
Cost vs. human wage	claude-haiku-4-5-20251001	1/5	AI crisis support systems are not commercially viable or deployed at scale for this task, making cost comparison premature. Even if partially automated, the human oversight, liability insurance, and clinical supervision required would likely exceed the cost of direct human provision.
Cost vs. human wage	claude-sonnet-5	1/5	Since AI cannot perform this task, any attempted AI substitute would need extensive human oversight and liability coverage, making it more costly than simply employing a qualified psychologist.
Technical feasibility today	claude-haiku-4-5-20251001	1/5	No deployed AI system reliably serves as a crisis resource for families and schools. While chatbots exist, they lack the clinical training, accountability, and contextual understanding required for crisis intervention, and organizations would face liability and ethical concerns deploying them for this purpose.
Technical feasibility today	claude-sonnet-5	1/5	No deployed product provides crisis support to families and schools as a substitute for a school psychologist; existing chatbot mental health tools are narrow, unreliable in crisis contexts, and not used this way in schools.

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How to read this

A high substitution score does not mean this job disappears — it means a large share of its current tasks face replacement pressure, so the mix of tasks is likely to change. High augmentation alongside substitution typically means the occupation reorganizes around the protected tasks. Wide confidence intervals mean the rater panel disagreed: treat those scores as open questions, not verdicts.

What would change this score

New model capabilities (automatability, feasibility), falling inference costs (cost ratio), regulation and licensing shifts (barriers), and measured sector adoption (velocity) all re-enter at every index release. Each release is recomputed, versioned and kept queryable — scores are claims with a date on them, not permanent labels.