The study titled "The Effects of Artificial Intelligence (AI) and Automation in Bács‑Kiskun County" aimed to identify expected labor‑market impacts of AI and automation locally, and to assess firms' digital preparedness, development needs and outlooks. The research paid special attention to how national and international trends manifest among the county's economic actors.
The survey was conducted in spring 2026 with 200 respondents. The sample primarily consisted of entrepreneurial decision‑makers, company executives and owners. Quotas for region, company size and main activity ensured diversity: participants included organizations from the county seat and peripheral districts, service, industrial, construction, agricultural and food companies, as well as micro, small, medium and large enterprises.
Key findings: split readiness and adoption rates
Respondents displayed a marked divide in technological readiness. Approximately 40% of firms already use some form of AI‑based or automation solution in daily operations, while more than one third currently do not plan to adopt such technologies. Sectoral patterns emerged: agricultural and food companies lead in automation, whereas adoption of AI tools is most advanced in the service sector.
There is a strong link between firm size and technology use: among microenterprises, nearly 50% reported they do not plan to implement these technologies.
Main barrier: lack of competencies
The survey identified the primary obstacle not as missing infrastructure or high costs, but as a competence gap. A large share of respondents pointed to a shortage of workers with adequate digital skills, gaps in knowledge required to use AI tools, and shortcomings in the education system as the main constraints on progress.
Company leaders expressed concern that a significant portion of the workforce lacks the skills needed for future jobs. According to responses, the winners of technological change will tend to be younger, digitally trained employees, while 50‑plus workers and employees with lower qualifications face particular risks.
Jobs and objectives: support rather than mass layoffs
Importantly, most firms do not view AI primarily as a means to eliminate jobs. The principal goals of technological development are increasing productivity, alleviating labor shortages, replacing monotonous tasks and improving operational efficiency. Respondents generally did not expect large‑scale personnel reductions.
Recommended interventions: training, support, education‑business cooperation
A central message of the research is that successful technological transition depends on human resource development as much as — or more than — hardware acquisition. Recommendations include:
- Targeted, practice‑oriented training: prioritizing data analysis, use of generative AI tools, algorithmic thinking and digital problem‑solving. Training should move beyond general digital literacy toward immediately workplace‑applicable skills.
- Support for vulnerable groups: short, practice‑focused upskilling programs for workers over 50 and those with lower formal qualifications.
- Integrated support for SMEs: development programs should not only fund hardware or software purchases but also include advisory services, technology mentoring, change‑management support and employee training, since many firms face organizational and knowledge shortfalls rather than purely technological ones.
- Renewal of the education system: vocational and higher education should become more practice‑oriented, with project‑based learning and daily use of digital tools. Students need hands‑on experience in working effectively with AI, including routine prompt use and detecting AI errors — not only theoretical instruction.
- Strengthening cooperation: dual training models and closer links between chambers, companies and educational institutions can better align labor demand and supply.
Strategic outlook: gradual transition and human–machine collaboration
The study recommends a gradual transition strategy: AI should primarily be applied as an intelligent assistant and productivity enhancer that reduces routine burdens and enables higher value‑added activities. Promoting and teaching human–machine collaboration should be a central element of the county's economic development and employment policies in the coming years.
Authors and context
The study was prepared by Vasárus Gábor László (ELTE Közgazdaság és Regionális Tudományi Kutatóközpont, Regionális Kutatások Intézete), Farkas Jenő Zsolt (ELTE KRTK RKI), Hoyk Edit (ELTE KRTK RKI), Lennert József (ELTE KRTK RKI), Kovács András Donát (ELTE KRTK RKI) and Szalai Ádám (ELTE KRTK RKI). The article reflects the authors' views and does not necessarily represent the editorial position of Portfolio.
Overall, the results indicate that Bács‑Kiskun County's long‑term competitiveness will depend on timely, coordinated action by firms, educational institutions and development policy actors to close the competence gap and steer the technological transition.
