Research objectives and hypothesis/research questions:
The objective of this study is to analyze selected attributes of the artificial intelligence (AI) environment in the context of its potential for effective business process management. Hypothesis: Information efficiency in cyberspace is a strong determinant of business success, and AI tools and models enhance the flexibility and efficiency of business processes.

Research methods:
Critical literature review, analysis of documents and reports, diagnostic survey, case study, quantitative and qualitative analysis methods.

Main results:
AI implementation significantly reduces operational costs and minimizes resource waste, particularly in the SME sector. AI models support offer personalization and customer service automation, increasing business competitiveness. Machine learning models improve market trend forecasting, enabling businesses to adapt more quickly to changing environments. AI adoption requires well-developed information strategies and integration of various knowledge areas within enterprises. Research confirms that information efficiency in cyberspace is a key determinant of business success.

Implications for theory and practice:
Research confirms that AI is a key factor supporting data-driven business decision-making. Further development of theoretical models is needed to assess AI’s impact on decision-making, innovation, and operational efficiency. AI and organizational management AI transforms traditional management approaches, enabling real-time data-driven integration of organizations. This shift should be reflected in strategic management theories and business models considering digital transformation. Changing managerial roles process automation shifts managers’ roles from operational management to strategic oversight of algorithms and data. Traditional management theories must incorporate digital leadership and AI-driven change management.