AI is connected to automation because it enables digital systems to perform tasks that previously required human cognitive or creative work. This can cause job displacement when fewer workers are needed, but it does not mean that entire occupations automatically disappear.
Automation is the use of a digital system to complete a process with limited human input. AI extends automation by recognizing patterns, interpreting language, generating outputs, or making predictions in less predictable situations.
The key IB distinction is between a task and a job. AI usually automates tasks first, so it may replace some activities while changing other responsibilities. This can produce augmentation, where AI supports human work, or displacement, where demand for human labour falls. New roles may also emerge in AI oversight, data governance, and maintenance.
A specific example is Klarna's AI customer-service assistant, introduced in 2024, after the 2022 coursebook. Klarna reported that the system handled many customer interactions and performed work comparable to hundreds of full-time agents. The impact could include reduced demand for routine support roles and faster customer service. The implications are contested: businesses may gain efficiency, while workers may face insecurity, reduced bargaining power, or pressure to develop new skills. Employees, customers, regulators, and labour organizations may assess these trade-offs differently.
This illustrates change, power, and values and ethics. AI can transform how work is organized, but outcomes depend on employer decisions, regulation, training, and the economic context. The misconception to avoid is that AI independently causes unemployment. Displacement results from the interaction of AI capabilities, human choices, and institutions.
For an IB response at SL or HL, distinguish automation, augmentation, and displacement, then evaluate impacts on at least two stakeholder groups. For HL, this also links to global well-being, particularly the future of work.
