The recent launch of GPT-5 by OpenAI has attracted significant attention in the tech world and among companies worldwide. With each new model, OpenAI sets another milestone in AI development, and GPT-5 is regarded as the most powerful language model to date: it can recognize complex relationships even better, grasp context more precisely, and act far more versatilely than its predecessors.

Many digitization projects are on companies’ agendas—from optimizing internal workflows to the intelligent automation of entire business processes. Yet organizations often run up against the limits of existing systems: many workflows are shaped by manual steps, isolated data silos, and cumbersome legacy systems. At the same time, pressure is mounting to continuously improve customer service, innovation speed, and productivity.

This is precisely where GPT-5 comes into play as a potential game-changer. Following the first generations of language models and AI assistants, GPT-5 offers an even broader range of capabilities: whether as a digital assistant in customer interactions, a tool for text analysis and data extraction, or a dynamic component in business applications—companies can use GPT-5 to address a wide spectrum of challenges and unlock new value-creation potential.

However, despite the enthusiasm, the question remains how companies can use GPT-5 in concrete terms, where the day-to-day limits lie, and which risks arise—particularly with regard to data protection and integration into existing system landscapes. Anyone exploring GPT-5 should critically assess their starting point and develop a future-proof AI strategy step by step.

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