Artificial intelligence adoption among Serbian enterprises increased from 10.1% in 2025 to 17.2% in 2026, according to the Statistical Office of Serbia, highlighting accelerating corporate digitalisation and persistent differences in technology investment across the country.
The increase of 7.1 percentage points, equivalent to approximately 70.3% growth, does not necessarily reflect a similar rise in AI spending or productivity. The survey covers enterprises employing at least 10 people, and more than 82% of respondents reported no AI use in 2026.
Regional Differences in Technology Adoption
Belgrade recorded the highest adoption rate at 20.4%, followed by southern and eastern Serbia at 16.7%, Vojvodina at 15.8% and Šumadija and western Serbia at 12.5%.
Differences in industrial structure, company size, workforce skills and access to specialist services may contribute to the uneven distribution, although the survey does not establish their causes. Expanding digital infrastructure and technical training outside the capital could help more businesses access AI technologies.
Manufacturing and Energy Efficiency
Serbian manufacturers in automotive components, electrical equipment, metals processing, food production, chemicals and machinery could use AI for predictive maintenance, quality control, production scheduling, inventory management and energy optimisation.
Industrial applications can reduce equipment downtime, material losses and operating costs, but implementation often requires investment in sensors, data systems, software integration and employee training. Companies with incomplete industrial data may need to modernise their infrastructure before introducing advanced AI solutions.
Energy management represents another potential application, particularly for electricity-intensive industries such as steel, cement, chemicals and metals processing. AI can support demand forecasting and equipment efficiency, although potential savings depend on electricity tariffs, contractual arrangements and production flexibility.
Banking and SMEs Face Implementation Challenges
Serbia’s banking sector could apply AI to fraud detection, credit-risk assessment, transaction monitoring, document processing and customer support. Automated analysis may improve efficiency, but financial institutions must address cybersecurity, data protection, model governance and the risks associated with inaccurate decisions.
Small and medium-sized enterprises face different obstacles, including limited technology budgets and shortages of specialised personnel. While administrative automation may offer an accessible starting point, industrial applications can require substantial investment in equipment, engineering and data integration.
Commercial banks and development finance institutions could support digital modernisation through investment loans, equipment financing and technical-assistance programmes. Financing decisions would need to be supported by credible business plans and measurable expected benefits.
Engineering and Cybersecurity Demand
Growing industrial AI adoption could create opportunities for Serbian engineering companies providing sensor installation, industrial automation, control-system integration, equipment diagnostics and cybersecurity services.
Integration with existing industrial control systems, programmable logic controllers and supervisory control and data acquisition platforms can be technically demanding, particularly in older facilities. Companies must also protect commercially sensitive information and ensure that connections between corporate IT networks and industrial systems do not compromise operational reliability.
Productivity Will Determine Investment Returns
For Serbian companies supplying European industrial networks, AI could improve production traceability, quality documentation, delivery reliability and cost management. Digitalisation cannot independently resolve constraints involving energy reliability, logistics, workforce availability and access to finance.
Investors can evaluate results through operating margins, revenue per employee, equipment utilisation, working-capital efficiency and return on invested capital, while accounting for software, computing infrastructure, specialist staff and maintenance costs.
The increase in adoption could support demand for enterprise software, industrial automation, data infrastructure and specialist consulting, creating opportunities for lenders and investors. The available figures do not establish how much companies have invested or what financial returns they have achieved. The next phase of Serbia’s corporate AI adoption will depend on whether businesses can convert technology deployment into measurable productivity gains, lower operating costs and stronger export competitiveness.
