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For school students, graduates, experienced professionals, returners and people changing direction. Start with the work you want to do and the life you need—not a fashionable title.
One Compass · four useful routes
Choose one route. The next page will show only the tools for that decision, in a clear order—you do not need to scroll through every part of the Compass.
Answer six questions about the work, values, setting and practical routes that suit you.
Get: career suggestions with clear reasons → 02 · Explore a careerSearch one complete library, then open a role’s skills, work conditions and entry route.
Get: practical career maps and next steps → 03 · Change directionChoose familiar kinds of work from work, study, care, volunteering or projects.
Get: connected careers and only the gaps to build → 04 · Build skillsChoose your stage, strengthen foundations and make a flexible practice plan for one useful skill.
Get: a realistic practice route and proof to create →Find my direction
No test can name your one perfect career. These questions suggest options worth exploring and explain why they may suit you.
Based on your answers
Your decision brief
We temporarily remove one of your selected preferences at a time and compare the results. This helps you see which suggestions are steady and which depend heavily on one answer. It is not a prediction or career verdict.
Your career stage, goal, available route and time stay the same.
Redesigns how people, agents and automation divide work.
Where people add value: Accountability design, job quality, adoption, worker voice and deciding which decisions must remain human.
Tests whether AI outputs are useful, safe, fair and accountable.
Where people add value: Choosing meaningful success and harm criteria, representative tests, release judgment and escalation.
Turns AI laws, standards and risk appetite into working controls.
Where people add value: Proportionate control, legal-operational translation, ownership and challenge when adoption outruns evidence.
Finds how AI systems can be attacked, manipulated or made to leak.
Where people add value: Realistic threat chains, responsible testing, harm prioritisation and proof that mitigations work.
Builds reliable multi-step AI workflows with tools, memory and controls.
Where people add value: Architecture, permission boundaries, failure recovery and responsibility for actions across connected systems.
Fits robots into real workplaces safely and usefully.
Where people add value: Physical safety, operator trust, site adaptation, commissioning and accountable recovery.
Builds virtual models of physical systems to test decisions before reality.
Where people add value: Physical validity, calibration judgment, uncertainty and deciding when a model is safe to act on.
Helps places and organisations prepare for heat, flood and climate disruption.
Where people add value: Local legitimacy, equity, political trade-offs, finance and implementation that survives beyond a model.
Balances a more renewable, electrified and flexible energy system.
Where people add value: Power-system physics, reliability responsibility, regulation and decisions under rare disruption.
Makes digital and AI tools usable, safe and valuable in care.
Where people add value: Clinical safety, patient context, evidence, equity and accountable integration into care.
Helps people verify where digital media came from and how it changed.
Where people add value: Source context, chain of custody, calibrated uncertainty, rights and rapid trust decisions.
Uses computation to interpret biological data and support discovery or care.
Where people add value: Biological interpretation, experimental context, reproducibility, clinical validity and research ethics.
Builds reliable digital products, services and internal systems.
Where people add value: Architecture, problem framing, security, verification and ownership of production consequences.
Turns messy information into decisions people can act on.
Where people add value: Metric definition, causal caution, domain context and decisions under imperfect evidence.
Designs, evaluates and deploys systems that learn from data.
Where people add value: Evaluation strategy, data judgment, safety, system design and scientific accountability.
Protects systems, data and people from digital threats.
Where people add value: Adversarial judgment, incident leadership, identity decisions and business-risk ownership.
Makes digital services deployable, observable, scalable and dependable.
Where people add value: Reliability architecture, safe change, incident command and cost-risk trade-offs.
Removes repetitive work by connecting tools, data and workflows.
Where people add value: Process discovery, exception design, governance and adoption.
Chooses valuable problems and aligns a team to solve them.
Where people add value: Problem selection, customer judgment, taste, trade-offs and accountable prioritisation.
Translates business problems into workable process and system changes.
Where people add value: Contextual discovery, conflicting needs, validation and change adoption.
Turns complex goals into coordinated, delivered outcomes.
Where people add value: Negotiation, sequencing under uncertainty, escalation and shared commitment.
Makes everyday delivery reliable, efficient and scalable.
Where people add value: Exception judgment, people leadership, resilience and frontline trust.
Helps organisations diagnose high-stakes problems and act on them.
Where people add value: Executive judgment, stakeholder alignment, original synthesis and implementation politics.
Creates and operates a solution people will pay for.
Where people add value: Customer trust, risk-bearing, offer judgment and responsibility for outcomes.
Builds measurable attention, demand and customer growth online.
Where people add value: Brand judgment, customer understanding, experimentation integrity and channel strategy.
Helps organisations buy solutions to meaningful business problems.
Where people add value: Trust, discovery, negotiation, political context and commercial accountability.
Helps customers achieve value and stay successful with a product.
Where people add value: Relationship judgment, teaching, escalation and customer outcome ownership.
Explains what people need, choose and believe using rigorous research.
Where people add value: Question quality, bias control, interpretation and inconvenient findings.
Builds a coherent voice and content system that earns attention and trust.
Where people add value: Positioning, editorial taste, cultural context and accountable authorship.
Designs useful, usable and coherent digital experiences.
Where people add value: Observation, accessibility, interaction judgment and responsibility for user outcomes.
Makes ideas understandable and memorable through visual systems.
Where people add value: Distinctive direction, cultural judgment, systems consistency and accountable craft.
Shapes moving-image stories from idea through final delivery.
Where people add value: Story, consent, authenticity, direction and production leadership.
Makes complex products and processes clear enough to use.
Where people add value: Information architecture, user testing, accuracy ownership and domain understanding.
Helps people build understanding and capability that lasts.
Where people add value: Diagnosis, motivation, relationships, safeguarding and responsive teaching.
Helps people make informed education, work and transition decisions.
Where people add value: Deep listening, contextual judgment, ethics and confidence-building without prescribing.
Builds fair people systems and helps employees grow.
Where people add value: Fairness, confidential judgment, manager influence and organisational trust.
Supports mental health and behaviour through evidence-based professional practice.
Where people add value: Therapeutic relationship, clinical judgment, ethics, empathy and accountable care.
Uses financial evidence to evaluate performance, risk and investment choices.
Where people add value: Assumption challenge, capital judgment, narrative and responsibility for recommendations.
Keeps financial records accurate, controlled and decision-ready.
Where people add value: Controls, standards interpretation, anomaly judgment and professional accountability.
Helps organisations act safely, legally and responsibly.
Where people add value: Proportionality, challenge, accountability and navigating ambiguity in real operations.
Uses evidence to improve public or organisational rules and programs.
Where people add value: Public values, stakeholder legitimacy, implementation judgment and democratic accountability.
Helps test medical interventions safely and rigorously.
Where people add value: Protocol judgment, participant safety, scientific integrity and regulated accountability.
Designs and delivers programs that improve health at population scale.
Where people add value: Community legitimacy, equity, ethics and resource decisions under uncertainty.
Makes care services safer, smoother and more accessible.
Where people add value: Patient-safety judgment, clinical coordination, workforce trust and incident ownership.
Measures environmental impact and helps organisations improve it credibly.
Where people add value: Boundary choices, greenwashing challenge, transition judgment and operational influence.
Keeps materials and products moving through uncertain systems.
Where people add value: Disruption judgment, supplier relationships, resilience and multi-objective trade-offs.
Installs, tests and maintains clean-energy equipment safely.
Where people add value: Physical diagnosis, safe work, site adaptation and accountable repair.
Keeps automated machinery and control systems working reliably.
Where people add value: Hands-on fault isolation, functional safety, commissioning and production recovery.
Turns a social mission into a program that delivers measurable benefit.
Where people add value: Community voice, safeguarding, power awareness and ethical field judgment.
Delivers skilled, person-centred care across hospitals, clinics and communities.
Where people add value: Context, relationships, ethics, safety and accountable decisions in the real world.
Supports older, disabled or vulnerable people to live with dignity and agency.
Where people add value: Context, relationships, ethics, safety and accountable decisions in the real world.
Helps people navigate complex life circumstances, rights, risks and services through accountable professional practice.
Where people add value: Relationship, rights, consent, contextual assessment, safeguarding and accountable legal or ethical judgment.
Builds safe, playful environments where young children develop and belong.
Where people add value: Context, relationships, ethics, safety and accountable decisions in the real world.
Creates dependable guest experiences while coordinating fast-moving service operations.
Where people add value: Context, relationships, ethics, safety and accountable decisions in the real world.
Produces safe, consistent food while coordinating time, quality, cost and people.
Where people add value: Physical-world validity, safety, integration and responsibility for consequences.
Connects customer needs, product presentation and reliable store or omnichannel delivery.
Where people add value: Context, relationships, ethics, safety and accountable decisions in the real world.
Keeps heating, cooling, ventilation and building services safe, efficient and reliable.
Where people add value: Physical-world validity, safety, integration and responsibility for consequences.
Coordinates people, materials, quality and safety so physical projects progress responsibly.
Where people add value: Physical-world validity, safety, integration and responsibility for consequences.
Combines crop or livestock knowledge with practical machinery, sensing and resource management.
Where people add value: Physical-world validity, safety, integration and responsibility for consequences.
Keeps goods moving safely, accurately and on time through physical operations.
Where people add value: Physical-world validity, safety, integration and responsibility for consequences.
Diagnoses, maintains and repairs vehicles so people and goods move safely.
Where people add value: Physical-world validity, safety, integration and responsibility for consequences.
Protects people during urgent incidents and helps communities prepare and recover.
Where people add value: Context, relationships, ethics, safety and accountable decisions in the real world.
Solves practical household or business problems through trusted skilled service.
Where people add value: Physical-world validity, safety, integration and responsibility for consequences.
One complete career library
Search by title, skill, task or industry. This single library includes emerging AI-era roles alongside established careers; use the future-position filter when that is useful.
Redesigns how people, agents and automation divide work.
Draft task inventories, map candidate handoffs and simulate workflow alternatives.
Accountability design, job quality, adoption, worker voice and deciding which decisions must remain human.
Tests whether AI outputs are useful, safe, fair and accountable.
Generate test cases, cluster failure patterns and monitor defined quality signals.
Choosing meaningful success and harm criteria, representative tests, release judgment and escalation.
Turns AI laws, standards and risk appetite into working controls.
Discover AI use, map common obligations and automate evidence checks.
Proportionate control, legal-operational translation, ownership and challenge when adoption outruns evidence.
Finds how AI systems can be attacked, manipulated or made to leak.
Generate attack variants, scan common weaknesses and correlate model or agent traces.
Realistic threat chains, responsible testing, harm prioritisation and proof that mitigations work.
Builds reliable multi-step AI workflows with tools, memory and controls.
Scaffold integrations, draft routing logic and summarise execution traces.
Architecture, permission boundaries, failure recovery and responsibility for actions across connected systems.
Fits robots into real workplaces safely and usefully.
Accelerate simulation, calibration suggestions and predictive maintenance alerts.
Physical safety, operator trust, site adaptation, commissioning and accountable recovery.
Builds virtual models of physical systems to test decisions before reality.
Create surrogate models, detect anomalies and generate scenario variations.
Physical validity, calibration judgment, uncertainty and deciding when a model is safe to act on.
Helps places and organisations prepare for heat, flood and climate disruption.
Downscale hazard signals, analyse geospatial exposure and generate scenario options.
Local legitimacy, equity, political trade-offs, finance and implementation that survives beyond a model.
Balances a more renewable, electrified and flexible energy system.
Improve forecasts, optimise dispatch scenarios and detect operational anomalies.
Power-system physics, reliability responsibility, regulation and decisions under rare disruption.
Makes digital and AI tools usable, safe and valuable in care.
Draft documentation, scan evidence and support bounded administrative or triage tasks.
Clinical safety, patient context, evidence, equity and accountable integration into care.
Helps people verify where digital media came from and how it changed.
Check credentials and metadata, detect duplicates and flag synthetic-media signals.
Source context, chain of custody, calibrated uncertainty, rights and rapid trust decisions.
Uses computation to interpret biological data and support discovery or care.
Draft pipeline code, extract features and accelerate pattern or structure discovery.
Biological interpretation, experimental context, reproducibility, clinical validity and research ethics.
Builds reliable digital products, services and internal systems.
Draft boilerplate, routine tests, migrations, documentation and first-pass debugging.
Architecture, problem framing, security, verification and ownership of production consequences.
Turns messy information into decisions people can act on.
Draft queries, clean common patterns, produce routine charts and summarise dashboards.
Metric definition, causal caution, domain context and decisions under imperfect evidence.
Designs, evaluates and deploys systems that learn from data.
Generate prototype code, tune common pipelines and accelerate literature or experiment setup.
Evaluation strategy, data judgment, safety, system design and scientific accountability.
Protects systems, data and people from digital threats.
Triage routine alerts, correlate logs and draft incident summaries.
Adversarial judgment, incident leadership, identity decisions and business-risk ownership.
Makes digital services deployable, observable, scalable and dependable.
Draft infrastructure code, diagnose common failures and automate repetitive operations.
Reliability architecture, safe change, incident command and cost-risk trade-offs.
Removes repetitive work by connecting tools, data and workflows.
Generate connectors, mappings and simple workflow logic.
Process discovery, exception design, governance and adoption.
Chooses valuable problems and aligns a team to solve them.
Summarise research, draft requirements and create rapid prototypes.
Problem selection, customer judgment, taste, trade-offs and accountable prioritisation.
Translates business problems into workable process and system changes.
Draft process maps, requirements, user stories and routine gap analysis.
Contextual discovery, conflicting needs, validation and change adoption.
Turns complex goals into coordinated, delivered outcomes.
Draft plans, status updates, dependency summaries and meeting follow-ups.
Negotiation, sequencing under uncertainty, escalation and shared commitment.
Makes everyday delivery reliable, efficient and scalable.
Forecast routine demand, monitor exceptions and generate standard operating material.
Exception judgment, people leadership, resilience and frontline trust.
Helps organisations diagnose high-stakes problems and act on them.
Accelerate research, modelling, synthesis and presentation production.
Executive judgment, stakeholder alignment, original synthesis and implementation politics.
Creates and operates a solution people will pay for.
Draft market research, content, support and operational automations.
Customer trust, risk-bearing, offer judgment and responsibility for outcomes.
Builds measurable attention, demand and customer growth online.
Generate campaign variants, target segments, reports and routine optimisation.
Brand judgment, customer understanding, experimentation integrity and channel strategy.
Helps organisations buy solutions to meaningful business problems.
Research accounts, draft outreach, summarise calls and update pipeline records.
Trust, discovery, negotiation, political context and commercial accountability.
Helps customers achieve value and stay successful with a product.
Draft onboarding, health summaries, responses and renewal risk signals.
Relationship judgment, teaching, escalation and customer outcome ownership.
Explains what people need, choose and believe using rigorous research.
Draft instruments, transcribe interviews, code basic themes and summarise responses.
Question quality, bias control, interpretation and inconvenient findings.
Builds a coherent voice and content system that earns attention and trust.
Generate variants, repurpose assets and draft routine editorial material.
Positioning, editorial taste, cultural context and accountable authorship.
Designs useful, usable and coherent digital experiences.
Generate interface variants, research summaries and first-pass prototypes.
Observation, accessibility, interaction judgment and responsibility for user outcomes.
Makes ideas understandable and memorable through visual systems.
Generate commodity imagery, resize assets and produce early visual directions.
Distinctive direction, cultural judgment, systems consistency and accountable craft.
Shapes moving-image stories from idea through final delivery.
Create rough cuts, captions, translations, cleanup and synthetic production elements.
Story, consent, authenticity, direction and production leadership.
Makes complex products and processes clear enough to use.
Draft standard explanations, restructure content and maintain routine variants.
Information architecture, user testing, accuracy ownership and domain understanding.
Helps people build understanding and capability that lasts.
Draft lesson variants, practice questions, feedback and administrative material.
Diagnosis, motivation, relationships, safeguarding and responsive teaching.
Helps people make informed education, work and transition decisions.
Summarise information, draft resources and support routine exploration prompts.
Deep listening, contextual judgment, ethics and confidence-building without prescribing.
Builds fair people systems and helps employees grow.
Draft job material, learning content, skills mappings and workforce summaries.
Fairness, confidential judgment, manager influence and organisational trust.
Supports mental health and behaviour through evidence-based professional practice.
Support administration, note structuring and supervised low-risk educational material—not clinical accountability.
Therapeutic relationship, clinical judgment, ethics, empathy and accountable care.
Uses financial evidence to evaluate performance, risk and investment choices.
Draft models, extract data, create scenarios and summarise routine variance.
Assumption challenge, capital judgment, narrative and responsibility for recommendations.
Keeps financial records accurate, controlled and decision-ready.
Classify transactions, reconcile common items, prepare routine reports and flag anomalies.
Controls, standards interpretation, anomaly judgment and professional accountability.
Helps organisations act safely, legally and responsibly.
Monitor rules, draft mappings, scan evidence and flag routine control exceptions.
Proportionality, challenge, accountability and navigating ambiguity in real operations.
Uses evidence to improve public or organisational rules and programs.
Accelerate literature review, scenario drafting and consultation synthesis.
Public values, stakeholder legitimacy, implementation judgment and democratic accountability.
Helps test medical interventions safely and rigorously.
Draft documents, monitor routine data quality and support literature or site administration.
Protocol judgment, participant safety, scientific integrity and regulated accountability.
Designs and delivers programs that improve health at population scale.
Summarise surveillance, draft outreach variants and support resource planning.
Community legitimacy, equity, ethics and resource decisions under uncertainty.
Makes care services safer, smoother and more accessible.
Forecast demand, draft schedules and detect recurring flow exceptions.
Patient-safety judgment, clinical coordination, workforce trust and incident ownership.
Measures environmental impact and helps organisations improve it credibly.
Collect disclosures, draft reports, map standards and analyse routine metrics.
Boundary choices, greenwashing challenge, transition judgment and operational influence.
Keeps materials and products moving through uncertain systems.
Forecast, monitor routes and inventory, and generate routine scenarios.
Disruption judgment, supplier relationships, resilience and multi-objective trade-offs.
Installs, tests and maintains clean-energy equipment safely.
Support diagnostics, remote monitoring and predictive maintenance recommendations.
Physical diagnosis, safe work, site adaptation and accountable repair.
Keeps automated machinery and control systems working reliably.
Generate control logic drafts, diagnostic suggestions and maintenance predictions.
Hands-on fault isolation, functional safety, commissioning and production recovery.
Turns a social mission into a program that delivers measurable benefit.
Draft reports, analyse routine survey data and support grant administration.
Community voice, safeguarding, power awareness and ethical field judgment.
Delivers skilled, person-centred care across hospitals, clinics and communities.
AI supports documentation, monitoring and decision prompts; hands-on assessment, trust, escalation and accountable clinical judgment remain human.
Context, relationships, ethics, safety and accountable decisions in the real world.
Supports older, disabled or vulnerable people to live with dignity and agency.
Scheduling and records automate, while presence, safeguarding, subtle observation and respectful human support remain central.
Context, relationships, ethics, safety and accountable decisions in the real world.
Helps people navigate complex life circumstances, rights, risks and services through accountable professional practice.
Support resource search, case-record structuring, administrative triage and bounded draft summaries.
Relationship, rights, consent, contextual assessment, safeguarding and accountable legal or ethical judgment.
Builds safe, playful environments where young children develop and belong.
AI can draft activities and records, but attunement, play observation, safety, family trust and developmental judgment stay human.
Context, relationships, ethics, safety and accountable decisions in the real world.
Creates dependable guest experiences while coordinating fast-moving service operations.
Self-service and automated pricing grow; recovery, local knowledge, coordination and memorable human service differentiate.
Context, relationships, ethics, safety and accountable decisions in the real world.
Produces safe, consistent food while coordinating time, quality, cost and people.
Forecasting, ordering and menu ideation automate; sensory judgment, safe execution, coordination and distinctive craft remain physical.
Physical-world validity, safety, integration and responsibility for consequences.
Connects customer needs, product presentation and reliable store or omnichannel delivery.
Checkout, forecasting and routine recommendations automate; trust, recovery, local demand sensing and team leadership persist.
Context, relationships, ethics, safety and accountable decisions in the real world.
Keeps heating, cooling, ventilation and building services safe, efficient and reliable.
Sensors predict faults and optimise controls; physical diagnosis, compliant repair and responsibility at the site remain human.
Physical-world validity, safety, integration and responsibility for consequences.
Coordinates people, materials, quality and safety so physical projects progress responsibly.
Planning, measurement and reporting digitise; site sequencing, hazard recognition, trade coordination and accountability stay embodied.
Physical-world validity, safety, integration and responsibility for consequences.
Combines crop or livestock knowledge with practical machinery, sensing and resource management.
Remote sensing and prediction expand, while local observation, equipment care, responsible input decisions and biological judgment remain vital.
Physical-world validity, safety, integration and responsibility for consequences.
Keeps goods moving safely, accurately and on time through physical operations.
Robotics and optimisation change tasks; exception handling, safe human-machine flow, coaching and accountable operations remain.
Physical-world validity, safety, integration and responsibility for consequences.
Diagnoses, maintains and repairs vehicles so people and goods move safely.
Diagnostics become software-rich and fleets electrify; physical verification, repair quality and safety sign-off remain human.
Physical-world validity, safety, integration and responsibility for consequences.
Protects people during urgent incidents and helps communities prepare and recover.
Prediction, dispatch and situational data improve, while scene judgment, trust, physical action and command accountability remain human.
Context, relationships, ethics, safety and accountable decisions in the real world.
Solves practical household or business problems through trusted skilled service.
Scheduling, quoting and diagnostics gain digital support; trustworthy hands-on work, accountability and local reputation remain differentiators.
Physical-world validity, safety, integration and responsibility for consequences.
Remove one constraint or use a broader search. A near match can still reveal an adjacent route.
Change career without discarding your experience
Choose up to three experience themes from work, study, care, volunteering or projects. This suggests careers worth investigating; it does not declare you qualified or decide what suits you.
Your existing-experience route
Start broad. You can add a precise skill only when you can describe a real example of using it.
Choose an experience theme that sounds like work you have done.
See careers where related transferable skills appear.
Open a career to check the real work, route and gaps.
Search across all 186 transferable skills.
Try a broader word such as “planning”, “people”, “writing”, “risk” or “research”.
No skills added. Choose only skills you can explain with a real example.
Build skills for life, work and career change
These help you learn, decide, communicate, recover and create value across roles. Start with one that would improve your work or life now, then explore transferable skills connected to real careers.
Browse role-related transferable skills ↓Know your strengths, limits, values, energy patterns and non-negotiables.
Keep a weekly energy-and-evidence log: what gave energy, what drained it, and what you did well.
Useful proof: Keep the output, feedback and the change you made after reflection.
Learn, unlearn and transfer knowledge as tools and roles change.
Run a two-week learning sprint that ends in a visible output, not a certificate.
Useful proof: Keep the output, feedback and the change you made after reflection.
Check evidence, spot assumptions and make sound decisions under uncertainty.
For one decision each week, write the claim, evidence, alternatives and what would change your mind.
Useful proof: Keep the output, feedback and the change you made after reflection.
Write, speak, listen and adapt a message to the person receiving it.
Explain one complex idea in a one-minute voice note and a five-sentence memo.
Useful proof: Keep the output, feedback and the change you made after reflection.
Work through different perspectives, feedback, conflict and shared ownership.
Ask for feedback on one behaviour, restate it without defending, then apply one change.
Useful proof: Keep the output, feedback and the change you made after reflection.
Manage attention, time, energy, commitments and recovery sustainably.
Plan one week around three outcomes, two deep-work blocks and protected recovery time.
Useful proof: Keep the output, feedback and the change you made after reflection.
Use modern tools safely while verifying outputs, privacy, bias and limitations.
Use AI on a real task, fact-check every important output, and record where human judgment mattered.
Useful proof: Keep the output, feedback and the change you made after reflection.
Build proof, relationships, negotiation ability and basic money resilience.
Update a proof-of-work file and calculate your minimum, comfortable and growth monthly income needs.
Useful proof: Keep the output, feedback and the change you made after reflection.
Then choose a transferable skill
Search 186 reusable capabilities or filter by the kind of activity you enjoy. Make a flexible practice plan when you find one worth practising.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Practise it on a real task, ask for specific feedback, revise once and keep the before-and-after example.
Try a broader word such as “planning”, “people”, “writing”, “risk” or choose another activity.
Personalise your skills route
Choose your current stage—not your age. You can explore, return, lead or change direction at any point in life.
Focus on: Subject choices as doors to keep open, not permanent identity labels.
Try not to: Choosing only from marks, family familiarity or one salary headline.
Focus on: Courses, clubs, volunteering, part-time work and internships as experiments.
Try not to: Waiting until the final semester to meet the world of work.
Focus on: Adjacent roles, apprenticeships, internships and projects as valid starts.
Try not to: Treating the first title as a lifelong lock-in.
Focus on: Stretch assignments and lateral moves to test specialist and leadership paths.
Try not to: Collecting courses without using the skill at work.
Focus on: Existing domain knowledge as transition capital.
Try not to: Throwing away all prior experience to “start over”.
Focus on: Mentoring, advisory work, portfolio careers and selective reskilling.
Try not to: Competing only on the newest tool.
Focus on: Care, community, freelance and life administration as evidence when relevant.
Try not to: Apologising for a break or assuming all skills expired.
Focus on: Small tests and adjacent moves before an expensive reset.
Try not to: Falling in love with a title without sampling its routine.
Focus on: A narrow offer and direct customer evidence before a broad brand.
Try not to: Building for months before testing demand.
Future & AI · updated July 2026
These roles are emerging where organisations need people to redesign work with AI, check system quality, keep automated tools secure, connect robotics with real operations and protect public trust.
Redesigns how people, agents and automation divide work.
Accountability design, job quality, adoption, worker voice and deciding which decisions must remain human.
Tests whether AI outputs are useful, safe, fair and accountable.
Choosing meaningful success and harm criteria, representative tests, release judgment and escalation.
Turns AI laws, standards and risk appetite into working controls.
Proportionate control, legal-operational translation, ownership and challenge when adoption outruns evidence.
Finds how AI systems can be attacked, manipulated or made to leak.
Realistic threat chains, responsible testing, harm prioritisation and proof that mitigations work.
Builds reliable multi-step AI workflows with tools, memory and controls.
Architecture, permission boundaries, failure recovery and responsibility for actions across connected systems.
Fits robots into real workplaces safely and usefully.
Physical safety, operator trust, site adaptation, commissioning and accountable recovery.
Builds virtual models of physical systems to test decisions before reality.
Physical validity, calibration judgment, uncertainty and deciding when a model is safe to act on.
Helps places and organisations prepare for heat, flood and climate disruption.
Local legitimacy, equity, political trade-offs, finance and implementation that survives beyond a model.
Balances a more renewable, electrified and flexible energy system.
Power-system physics, reliability responsibility, regulation and decisions under rare disruption.
Makes digital and AI tools usable, safe and valuable in care.
Clinical safety, patient context, evidence, equity and accountable integration into care.
Helps people verify where digital media came from and how it changed.
Source context, chain of custody, calibrated uncertainty, rights and rapid trust decisions.
Uses computation to interpret biological data and support discovery or care.
Biological interpretation, experimental context, reproducibility, clinical validity and research ethics.
Continue with stage-relevant AI guidance
Your selected stage above opens the most relevant guidance. You can still inspect another stage whenever it is useful.
Watch: Letting AI complete work before you build reading, writing, maths, research and self-regulation.
Your advantage: Time to develop strong foundations and learn how tools fail before career decisions become expensive.
Watch: Producing polished assignments without gaining the underlying skill employers need you to verify.
Your advantage: Access to labs, faculty, peers, internships and projects where supervised experimentation is possible.
Watch: The routine junior tasks that once trained beginners are increasingly automated or compressed.
Your advantage: You can enter with modern workflows before older habits harden.
Watch: Becoming a fast tool operator without developing customer, system or domain judgment.
Your advantage: You already know enough workplace reality to redesign a bounded task and measure it.
Watch: Discarding years of domain capital to compete as a generic AI beginner.
Your advantage: Pattern recognition, stakeholder trust and operational context are exactly what AI projects often lack.
Watch: Delegating AI understanding entirely to vendors or junior technical teams.
Your advantage: Authority to redesign roles, protect learning pathways and set accountable operating norms.
Watch: Assuming a career break erased prior value while rushing into generic tool certificates.
Your advantage: Prior work plus care, coordination and life experience can create strong human and domain leverage.
Watch: Choosing an “AI career” title before testing its ordinary work, entry cost and competition.
Your advantage: A cross-domain combination can be more distinctive than starting from zero.
Watch: Automating an unclear offer or exposing client data through unmanaged tools.
Your advantage: Small operators can combine deep client context with fast, carefully governed delivery.
How this tool works
Your preferences, access and real-life needs are considered separately. Career choice is treated as something you explore, test and learn from over time.
O*NET distinguishes interests, worker requirements, activities and work context. The tool therefore shows ordinary tasks and environments—not only titles.
LifeComp, UNICEF, ILO, OECD, DigComp and ESCO inform the foundation and transferable layers; occupation craft remains separate.
Education, licensing, time, safety, adequate income, rest, flexibility and values can constrain fit. Preference alone is insufficient.
Small projects, work exposure, feedback and reflection turn curiosity into proof. Certificates are not treated as demonstrated competence.
What the research changed
Recently updated research
Career information changes, so we show recent sources that led to an update. These sources improve the guidance; they do not guarantee that a field will grow.
British Association of Social Workers, State of Social Work 2025 ↗
What we updated: Created a distinct Social Worker & Case Coordinator map and made caseload, supervision, resources and accountable statutory judgment explicit.Jan 2026IRENA and ILO, Renewable Energy and Jobs Annual Review 2025 ↗
What we updated: Strengthened local pathway verification, vocational entry checks and questions about inclusion, accommodation and training access.16 Jul 2026WEF Future of Jobs + ILO employment evidence ↗
What we updated: Added thirteen care, service, trade, agriculture, logistics and essential-operations career maps.17 Feb 2026OECD + ILO Getting Skills Right ↗
What we updated: Added nursing/allied-health and community-care maps with bridge, return and supervised routes.14 Jul 2026Recent global workforce commentary ↗
What we updated: Strengthened the human-leverage field on every career card.10 Jul 2026Developer workforce research coverage ↗
What we updated: Kept fundamentals, verification and non-AI baselines in technical runways.3 Jul 2026Naukri JobSpeak, India ↗
What we updated: Updated India context, fresher preparation and AI/ML search language.Jun 2026U.S. Chamber of Commerce Foundation ↗
What we updated: Added copyable shortlists, proof targets and evidence-first application sprints.Jun 2026OECD Skills Studies ↗
What we updated: Added vacancy decoding, alternative search language and local credential verification.22 Jun 2026World Economic Forum ↗
What we updated: Created two full emerging-role maps and their skill stacks.18 Jun 2026SHRM automation research ↗
What we updated: Separated task-change exposure from claims about whole-job replacement.15 Jun 2026PwC 2026 AI Jobs Barometer ↗
What we updated: Raised judgment, creativity and leadership in AI-reinvented role maps.May 2026Microsoft Work Trend Index ↗
What we updated: Strengthened human checkpoints, accountable AI use and evidence of judgment.14 Jun 2026World Health Organization ↗
What we updated: Created the Digital Health & Clinical AI role and safety boundary.Jun 2026NISO ↗
What we updated: Created the Content Provenance & Media Integrity role map.2026ILO Workforce 2030 ↗
What we updated: Expanded climate, grid, automation and physical-world skill pathways.16 Feb 2026UNESCO + MeitY ↗
What we updated: Added ethics, inclusion and safe-use actions across all nine stages.How we use videos, blogs and interviews: we use them to understand changing work and hear real examples. We do not make a career claim from one opinion. Important claims must also be supported by labour-market, employer, professional or public evidence.
What people doing the work say
These conversations show how people describe changing work and hiring. We use them to improve questions, small career tests and ways to show your skills—not to promise demand or claim everyone has the same experience.
Southern New Hampshire University ↗
Indeed via The College of St. Scholastica ↗
Food and Agriculture Organization of the United Nations ↗
Indeed via CareerWaves2 ↗
Australian Association of Social Workers ↗
Beyond Coding ↗
Wit + Grit ↗
Data & AI Exchange ↗
Who Ya Know Show ↗
Indeed via The College of St. Scholastica ↗
Singapore Early Childhood Development Agency ↗
Indeed via Northwest-Shoals Community College ↗
U.S. Bureau of Labor Statistics ↗
Hiroshima City North Medical Center Asa Citizens Hospital ↗
Primary frameworks and recent evidence reviewed for this build:
Research reviewed 15 July 2026. Sources guide the structure; role maps are editorial syntheses, not official occupational standards. The tool does not diagnose personality, guarantee employment or replace local licensing and safety requirements.