Knowledge hub
AI and your career, answered directly
Each page answers one question in the first paragraph, then explains the reasoning. No predictions we cannot support, and no statistics we cannot attribute.
Understanding AI exposure
What exposure is, how it is measured, and where your work sits.
How do I know if AI will affect my job?
Audit your week by task, not by job title. List what you actually do, then mark each activity as templated output, judgement work, or physical and relational work. Templated output is where AI lands first. If a large share of your week sits there, AI is already affecting your job, whether or not your employer has said so.
Read the answerHow do I measure AI exposure?
Measure AI exposure by decomposing the role into tasks, judging each task against what AI systems can currently do, weighting by how much of the week each task takes, then aggregating to a role-level score. Scoring the job as a single unit produces unreliable results, because exposure varies sharply between activities inside the same title.
Read the answerWill AI replace my job?
Nobody can reliably answer that for an individual, and anything that claims to is overstating what it knows. What can be assessed is how much of your work AI can currently do, which parts stay defensible, and what you would need to learn to move weight toward the defensible side. That is the useful question, and it is answerable.
Read the answerWhich jobs are most exposed to AI?
The most exposed roles are those built on templated information work: producing routine documents, processing structured data, generating first-draft content, and answering standard queries at volume. What they share is repeatable input-to-output work with clear correctness criteria and little need for physical presence or accountability.
Read the answerWhich careers are least exposed to AI?
The least exposed careers depend on things AI cannot supply: physical presence, legal or professional accountability, negotiation with real stakes, trust built over time, and judgement in messy, poorly documented situations. Skilled trades, hands-on healthcare, complex negotiation roles and accountable professional judgement all sit at this end.
Read the answer
Readiness and skills
Assessing where you stand and deciding what to learn next.
How AI-ready is my career?
Your career is AI-ready when the work that stays valuable outweighs the work being commoditised, and when you can close a new skill gap in weeks rather than years. Assess it with two questions: what share of my week is judgement and accountability, and what have I learned recently that changed how I work?
Read the answerHow can I assess my career's future readiness?
Assess future readiness on two axes: the ratio of defensible to exposed work in your week, and the speed at which you close new capability gaps. A strong position on both means change works in your favour. Weakness on either is specific and fixable - it points at a task mix to shift or a gap to close.
Read the answerHow can professionals identify their AI skill gaps?
Identify your AI skill gaps by comparing what you can evidence today against what your role is starting to assume. The most reliable source is recent job postings for your role one level up, read alongside your own task audit. A gap is real when it appears in those postings, touches a meaningful share of your week, and you cannot point to work that demonstrates it.
Read the answerWhat skills should I learn in the age of AI?
Learn the capability that sits adjacent to the work you already do - typically the ability to direct, review and take responsibility for AI-assisted output in your own domain, plus the judgement and accountability skills that make that review credible. Generic AI courses are low differentiation; domain-anchored capability is not.
Read the answerHow do I future-proof my career?
You future-proof a career by changing the balance of your work, not by finding a safe job. Move weight away from templated output, take accountability for outcomes, deepen one domain, and close the specific capability gaps your role is starting to assume. Doing this inside your current field is usually faster and less costly than switching careers.
Read the answerWhat should I learn to stay competitive in an AI-driven job market?
Competitiveness comes from two things: demonstrable judgement in a specific domain, and the ability to direct, review and be accountable for AI-assisted work in that domain. Learn the capability adjacent to your own work, prove it with a real deliverable, and describe your value as outcomes owned rather than tasks completed.
Read the answerHow should I prepare for AI-driven changes in my industry?
Track three signals in your industry: which tasks are being automated first, how job postings are being rewritten, and which tools your employers and competitors are buying. Then act only on what you control - your task mix, your evidenced capabilities and the outcomes you own. Industry-level forecasting is interesting; personal task-level action is what changes your position.
Read the answer
AI change by profession
How specific fields are being reshaped, task by task.
How is AI changing software engineering careers?
AI is compressing the cost of writing code, which shifts value toward everything around the code: system design, review, debugging unfamiliar failures, and owning what happens in production. Engineers whose contribution is measured in output volume are most exposed; engineers who own systems and decisions are least exposed.
Read the answerHow is AI changing marketing careers?
AI is collapsing the production half of marketing - first drafts, creative variants, routine reporting and basic audience segmentation - while making the judgement half more valuable: positioning, brand decisions, budget accountability and knowing which results were real. Marketers whose value is volume of output are exposed; marketers who own outcomes are not.
Read the answerHow is AI changing finance careers?
In finance, the processing layer is highly exposed - reconciliation, standard reporting, document extraction and variance commentary. The accountable layer is not: advisory judgement, regulatory interpretation, controls ownership and formal sign-off. Careers built on producing the numbers are exposed; careers built on being answerable for them are not.
Read the answerHow is AI changing HR careers?
AI is absorbing HR's administrative layer: screening, scheduling, first-pass policy drafting and routine employee queries. It is not absorbing the accountable layer - investigations, difficult conversations, negotiation, and decisions that carry legal and human consequences. HR roles built on coordination are exposed; roles built on judgement are not.
Read the answerHow is AI changing sales careers?
In sales, AI is automating the mechanical layer: prospect research, outreach drafting, CRM hygiene, call summarisation and pipeline reporting. It is not automating trust, negotiation, reading a room, or navigating a complex buying group. SDR-style volume roles are the most exposed; complex and relationship-led selling is the least.
Read the answerHow is AI changing consulting careers?
Consulting's analyst layer - desk research, data gathering, deck production and first-pass synthesis - is highly exposed, because it is structured information work with clear quality criteria. The partner layer is not: client relationships, judgement under uncertainty, credibility, and making change actually happen inside an organisation.
Read the answer
Start with the core concepts
Your next move
Reading is the easy part. See where you actually stand.
Your AIQ Score, the exposure behind it, your defensible strengths, your gaps and a 14-day plan - built from your own profile.
- Takes about 4 minutes
- Your CV stays private
- Score, report and roadmap