Artificial intelligence (AI) has become one of the most discussed technologies of recent years. Investment in AI is growing rapidly, while companies compete to implement new solutions. Yet the core question remains: does it actually improve efficiency?
Experts note that AI enhances productivity, but not for everyone and not equally across fields. The biggest benefits are seen in analytical and technical roles, where automation reduces routine tasks. In these sectors, productivity growth can reach double digits, saving employees hours each week in document creation, information search, and text structuring.
Service professions that rely on physical presence and communication are harder to automate. AI may assist with training or advice but cannot completely replace the human factor.
Large firms already report measurable results: for example, a leading Latin American bank claimed a 30% reduction in code generation time. Other companies, such as Procter & Gamble and Goldman Sachs, are implementing internal AI platforms to optimize document flow and prepare reports.
Key limitations exist: not every AI project yields results. Success often depends on the quality of the data and how well processes are adapted. Weak quality control or bureaucracy can undermine AI's benefits.
Economists expect that countries and organizations that scale up AI faster will see quicker productivity growth. Meanwhile, the need for adaptation, retraining, and effective usage scenarios is becoming more important. AI technology has significant potential, but it is realized only through careful integration into real business processes.
