How AI is changing business & finance work.
TaskExposed currently tracks 14 occupations in the business & finance family, representing approximately 4.7M workers. The group has an average AI exposure score of 65% and an average resilience score of 53.
The most exposed roles usually contain repeatable, text-heavy, data-heavy, or process-driven tasks. The most resilient roles usually depend on judgment, physical presence, trust, real-time decision-making, or cross-functional human coordination.
Use this page as a career map: compare risk levels, explore lower-exposure adjacent paths, and open individual profession reports for task-level detail.
Most AI-exposed business & finance careers
Roles with the highest task-level exposure scores.
Most resilient business & finance careers
Roles with the strongest human resilience scores.
High, moderate, and low exposure roles.
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Explore every business & finance profession.
Bookkeepers sit at the sharp end of automation: transaction categorization, reconciliation, and recurring reporting are core AI strengths, leaving advisory judgment and messy exceptions as the human core.
Financial analysts face high exposure as AI rapidly automates data gathering, modeling, and report generation — the tasks that previously took most of a junior analyst's week.
Insurance underwriting faces high AI exposure in risk scoring and policy pricing, where ML models have matched or exceeded human accuracy. Complex commercial risks and relationship-driven accounts remain more durable.
Tax preparers face heavy exposure on standard returns as AI-native filing tools mature, while complex situations, audit representation, and client trust hold their value.
Investment banking faces heavy exposure in analysis and deck-building, but deal origination, client relationships, and high-stakes negotiation under deadline pressure remain deeply human.
Accounting faces among the highest task-level automation potential of any white-collar profession. Transactional and reporting tasks are highly substitutable; advisory and judgment work is more durable.
Loan officers face strong AI exposure in document intake, credit analysis, and prequalification, while complex borrower counseling, exceptions, and relationship-based origination remain more durable.
Actuaries face high exposure in data processing and model building but retain strong value in regulatory judgment, model governance, and the communication of risk to non-technical stakeholders.
Quants see model implementation, backtesting, and research summaries accelerate sharply with AI, while hypothesis generation, model risk judgment, and accountability for capital stay human.
Mortgage brokers see rate shopping, document collection, and application prep automate end-to-end, while trust, complex borrower situations, and lender relationships preserve the human role.
Supply chain managers see strong AI assistance in demand forecasting and logistics optimisation, while supplier negotiation, risk management, and crisis response remain firmly human.
Financial advisors face significant exposure in planning and analysis tasks, but the behavioural coaching, trust relationship, and judgment required during market stress remain strongly human.
Risk managers see monitoring, reporting, and scenario modeling automate quickly, while accountability for risk appetite, judgment under uncertainty, and board communication stay human.
Forensic accountants gain AI leverage on transaction analysis and document review, while investigative judgment, interview skill, and expert testimony remain firmly human.