Artificial intelligence is moving beyond chatbots and experiments into the routine systems that keep European companies running. In Greece, AI-powered document processing has reduced some insurance and banking tasks from hours or days to minutes, offering a clear example of how automation is changing office work across the European Union.
The shift is not limited to one industry. Insurance claims, environmental assessments, accounting, data entry and administrative support are among the areas most likely to be affected as businesses adopt systems that can read documents, extract information and complete multi-step workflows.
AI cuts insurance claims processing from days to minutes
At one of Greece’s largest insurance companies, a health insurance claim previously took about 14 days to process. Employees had to review medical opinions, test results, invoices and policy conditions before authorising compensation.
That process now takes roughly one minute using AI Flows, a document-processing and workflow-automation system developed by Greek company Archeiothiki. The tool handles approximately 1,500 claims each day, identifies relevant information in documents and checks it against policies and company rules. Compensation can then be paid the following day.
One significant change is the ability to review every case rather than examining only a sample. That wider coverage can help insurers identify potential inconsistencies or fraud that might previously have been missed.
Banking work is also being automated
Similar technology is being used in banking to assess the environmental, social and governance performance of companies applying for finance. These assessments can affect the interest rate offered to a business.
The review may involve around 300 questions and require employees to search through corporate reports hundreds of pages long. Information can include workforce data, environmental performance and internal policies.
Tasks that once required about 16 hours of human work can now be supported by AI systems that locate relevant passages in reports of 400 or 500 pages and organise the information much faster. Human oversight remains important, particularly where assessments influence lending decisions, but the administrative burden is being reduced.
Which office jobs are most exposed?
The International Labour Organization and Polish research institute NASK identified administrative and clerical occupations as the job category most exposed to generative AI in their 2025 report, Generative AI and Jobs: A Refined Global Index of Occupational Exposure.
Roles with significant exposure include:
- Data-entry clerks
- Accounting and bookkeeping staff
- Administrative secretaries
- Document-processing workers
- Routine compliance and records staff
The report’s measure of “exposure” does not mean that all these jobs will disappear. Most occupations combine tasks that can be automated with responsibilities requiring judgement, communication, accountability or specialist knowledge.
In high-income economies, approximately one in three jobs shows some degree of exposure to generative AI. The likely short-term effect is therefore job transformation: employees may spend less time searching, copying and checking information, and more time handling exceptions, reviewing decisions and dealing with customers or colleagues.
AI use is already widespread in European workplaces
Artificial intelligence has already entered many workplaces in the EU. A Joint Research Centre study published in October 2025 found that 30% of workers surveyed used AI tools in their jobs, with adoption particularly visible in office-based work.
The technology also has a gender dimension. ILO research indicates that occupations dominated by women are almost twice as likely to be exposed to generative AI as occupations where men are the majority: 29% compared with 16%. This reflects the large number of women working in administrative, clerical and support positions.
That pattern does not determine the outcome for individual workers, but it highlights why reskilling, transparent workplace policies and consultation with employees will matter as automation expands.
Automation does not always mean fewer employees
Businesses adopting AI may use it to reduce staffing in some processes, but the technology can also make previously impractical work possible. Archeiothiki says it applies AI Flows to about 100 workflows for ten clients, mainly in banking, insurance and healthcare.
In one example, roughly 50 employees worked on a single process while a backlog still accumulated over a year. Automation can help address such delays by processing large document volumes and directing human attention to difficult cases.
This distinction is central to the debate about AI and employment. A system that processes documents does not necessarily replace every worker involved in the process. It may instead change the skills required, alter team sizes or allow organisations to offer a broader service.
Public-sector archives are the next major opportunity
Greece’s public sector may become an important testing ground for the next stage of document automation. Large volumes of government records have already been digitised, but many files remain little more than searchable electronic copies.
The first phase of digitisation converted paper documents into digital files and added basic metadata. The next phase involves turning the contents of those files into structured information that can be searched, compared and used in administrative workflows.
AI systems can potentially extract information, cross-check records and trigger parts of a process. Any public-sector deployment would need safeguards for accuracy, privacy, security and accountability, particularly when documents concern health, benefits or legal rights.
What happens next for European office workers?
The spread of AI will depend on more than technical capability. Employers will need to decide which tasks should be automated, how decisions are checked and how workers are trained. Employees will also need opportunities to develop digital, analytical and interpersonal skills that complement automated systems.
For policymakers, the challenge is to ensure that productivity gains do not come at the expense of fair treatment, data protection or meaningful human oversight. The European Union’s broader rules on artificial intelligence, employment and privacy form part of that framework, but workplace implementation will also depend on national law, collective agreements and company practice.
Conclusion
AI is already transforming Europe’s back office, with insurance and banking providing some of the clearest examples. The most immediate change is not necessarily the disappearance of entire professions, but the redesign of everyday tasks and the expansion of what organisations can process. The key question for European workers and employers is whether the transition is managed through training, safeguards and human accountability alongside automation.
