METHOD

How Career Risk Lab analyses careers

We do not ask whether a career is ‘safe’. We ask what kinds of risk and opportunity the pathway contains — and how strong the evidence is for each.

CAPABILITY-TO-EMPLOYMENT CHAIN

Capability is not an employment outcome.

The most common error in commentary about AI and careers is jumping directly from technical capability to job loss.

AI capability
Reliability in real conditions
Workflow integration
Economic case
Regulation and accountability
Organisational work redesign
Employment effects

The important question is not only whether AI can perform a task, but what changes between capability and employment.

THE CAREER RISK LENS

Eleven dimensions, considered separately.

Underlying demand

Is the need for the profession expanding, stable or weakening independently of technology?

Task-level AI exposure

Which tasks can current systems perform, and under what conditions?

First-Rung Risk

How might changing junior work affect entry and professional formation?

AI Complementarity

Does technology increase what a capable professional can achieve?

Economic substitution pressure

Is automation sufficiently reliable and economical to replace paid work?

Regulation and accountability

Who remains answerable when a decision or outcome goes wrong?

Training Lock-In

How much time, money and specificity must be committed before a useful exit point?

Career Portability

Which skills and credentials remain useful beyond the intended occupation?

Alternative pathways

Can credible routes reach similar outcomes with less irreversible commitment?

Geographic exposure

How dependent is the pathway on a particular region, labour market or regulatory system?

Evidence confidence

How strong, current and directly relevant is the available evidence?

Four CRL concepts

First-Rung Risk

What happens when technology changes the work through which beginners traditionally learn?

Training Lock-In

How much must be committed before a useful qualification or credible exit point is reached?

AI Complementarity

Does technology substitute for professional value, or increase what a capable professional can achieve?

Option Value

What remains useful if our prediction about the future turns out to be wrong?

Evidence labels

DATA

A claim supported by traceable published evidence.

CRL ANALYSIS

Our interpretation of what the evidence may mean for a decision.

UNKNOWN

A material question the available evidence cannot answer confidently.

Evidence philosophy

CRL prioritises official sources, professional regulators, reputable research, transparent surveys and direct evidence of real deployment.

  • Demonstration is not deployment.
  • Deployment is not employment effect.
  • Stated employer intention is not employment outcome.
  • Dates matter.

Professional regulation, admissions, apprenticeship structures, training costs and labour-market conditions differ between countries. International readers should substitute equivalent institutions and evidence in their own system.

Editorial independence

Organisations being assessed cannot pay to change a CRL conclusion. Read the full editorial standards.