Derga Consulting Outlines Transition from Business Intelligence to Business AI
October 30, 2026 · 2 min read
Derga Consulting has detailed how the transition from traditional Business Intelligence to Business AI enables companies to interact with corporate data using natural language. This shift allows for the use of conversational models to provide analyses, benchmarks, and predictions within seconds, which is intended to increase the informative potential of a company and strengthen decision making processes.
This transformation is driven by the convergence of Generative AI and new generation Data Cloud architectures. To turn language models into actual value and ensure fast, precise data access, companies must address challenges beyond technology. These include establishing solid data governance to ensure information quality and security, as well as creating architectures that securely connect Enterprise Resource Planning systems with AI engines.
Analysis of the Italian market by Giulio Nicelli of the Politecnico di Milano indicates that while interest is high, widespread experimentation has not yet led to real organizational transformation. More than 80 percent of large companies use AI tools for productivity, and there is a high volume of pilot projects. However, 75 percent of companies report that they have not redesigned their processes, and only 7 percent have defined organized models where AI operates autonomously with human validation.
The Italian Data Management and Analytics market, which supports AI projects, has seen significant growth. Business volume increased from 1.393 billion euro in 2018 to over 4 billion euro in 2025. This growth is supported by large companies at 75 percent, small and medium enterprises at 19 percent, and public administration at 6 percent. Such investments are considered strategic enablers because generative models require integrated, accessible, and reliable data.
Issues regarding Shadow AI, where employees use AI tools without company authorization, affect approximately 67 percent of companies. This phenomenon creates risks for privacy, security, and regulatory compliance. In 29 percent of cases, this occurs because corporate tools are missing, or existing tools are considered inadequate. Only 38 percent of large companies have defined a formalized Data Strategy, although 87 percent of those that have such a strategy measure concrete business benefits.
To enable the move to Business AI, three pillars are identified: usability as a condition for adoption, the interpretation of AI as a knowledge accelerator, and data governance as a reference point.