Effective career management in procurement requires continuously monitoring current competency trends. To meet the expectations of candidates who consciously shape their professional development and strive for stable employment, we consistently analyze market needs and the evolving role of procurement departments.

Our analysis of competencies and procurement positions focuses on the role of artificial intelligence in this field.

We examined job descriptions published on leading job portals in Poland as well as in Western European countries (including France, Germany, and the United Kingdom). Based on over 1,000 job descriptions covering operational roles (e.g., procurement specialists, analysts), strategic positions (e.g., category lead/manager), as well as managerial and transformative roles, we identified which competencies related to artificial intelligence—from basic analytical skills to advanced technologies—are required and in which positions they predominantly appear.

New Competencies Related to Artificial Intelligence

1. Data Analytics and Big Data
   This competency encompasses the ability to collect, process, and interpret large sets of procurement data, as well as to utilize analytical tools (e.g., Power BI, Tableau) to create visualizations and dashboards. Such skills are essential for both operational and managerial roles, enabling data-driven decision-making and cost optimization.
2. Process Automation
   This involves experience with Robotic Process Automation (RPA) technologies and the implementation of solutions that automate repetitive tasks within procurement. Proficiency with automation tools (e.g., UiPath, Blue Prism) is increasingly required for managerial and specialized roles, where AI-based solutions are deployed to reduce operational costs and streamline processes.
3. Programming and AI Tools
   This competency includes proficiency in programming languages such as Python or R—commonly used for developing analytical models and machine learning algorithms—as well as familiarity with libraries (e.g., TensorFlow, scikit-learn) and fundamental machine learning techniques. These requirements primarily appear in job offers targeted at data analysts and digital transformation specialists.
4. Machine Learning and Predictive Models
   This area involves developing and deploying predictive models that enable the forecasting of procurement trends, risk management, and inventory optimization, as well as interpreting model outputs to formulate specific business recommendations. These competencies are particularly valued in roles associated with advanced data analysis and strategic procurement management.
5. Digital Transformation and Innovation
   This encompasses knowledge of strategies for the digitization of procurement processes, as well as experience in the implementation of innovative technological solutions, coupled with the ability to manage transformational projects and collaborate with IT departments. These skills are required in managerial and executive roles where it is essential to integrate traditional procurement expertise with modern technologies.

Regional Specifics

The analysis reveals regional differences in the approach to leveraging artificial intelligence in procurement:

• Poland: Job offers predominantly view artificial intelligence as a tool to support procurement decisions, with an emphasis on process optimization and the use of analytical tools to monitor expenditures and manage risk.
• Western Europe: The requirements for advanced analytical and predictive competencies are higher. In Germany and the United Kingdom, there is a strong focus on the technical aspects of AI implementations, particularly regarding integration with ERP systems. In France, additional emphasis is placed on innovation and change management skills, indicating a growing demand for digital transformation specialists.

New AI-Focused Positions

Our analysis did not reveal a widespread emergence of entirely new procurement roles exclusively related to artificial intelligence. Instead, companies are integrating AI competencies into traditional roles.
Many job offers combine traditional procurement skills (such as negotiation, supplier analysis, and supply chain management) with advanced data analytics and programming abilities. Examples include positions like "Procurement Data Scientist" or "Digital Procurement Specialist," where artificial intelligence supports decision-making processes and operational optimization. Primarily, AI is used to improve operational efficiency, forecast trends, and automate routine tasks, making these competencies an integral part of traditional procurement roles.

Conclusions

Traditional procurement positions are undergoing transformation—there is an increasing demand for professionals who can integrate artificial intelligence technologies into everyday processes. Regardless of the role, the ability to analyze data remains crucial. Artificial intelligence is seen as a tool that enables better forecasting, cost optimization, and effective risk management. In higher-level managerial roles, experience in leading digital transformation projects—entailing the implementation of AI solutions—is increasingly required. In Western European countries, expectations regarding advanced technologies and AI integration are higher, while the domestic market focuses more on supporting operational decision-making.

An analysis of over 1,000 job descriptions from recent months confirms that competencies related to artificial intelligence are becoming an indispensable part of the candidate profile in procurement. From basic data analytics and process automation to advanced machine learning models, companies expect professionals to leverage modern tools to enhance operational efficiency and strategically manage supply chains. Consequently, both candidates and enterprises should invest in the development of digital technologies and analytical skills to meet the dynamically changing market demands.