The AI Paradox in Companies: Why Isn't Intelligence Alone Enough?

Economic Expectations vs. Practical Reality

The AI Paradox: Despite significant media attention on artificial intelligence and its projected value reaching trillions of dollars, and McKinsey's estimates that it could add the equivalent of 2.6 trillion to 4.4 trillion dollars annually to the global economy, most projects are still stuck in testing phases.

The Core Problem: Application and Operational Challenges

The core problem: lies not in the capabilities of the models, but in the difficulty of effectively applying and operating them in real-world scenarios.

The more advanced the model, the greater the challenges of deployment, reliability, and governance within real business systems. This is the AI paradox in organizations.

The Gap Between Technology Adoption and Value Generation

The fundamental discrepancy: The essence of this paradox, according to McKinsey, lies in the discrepancy between how AI technologies are adopted and how they generate actual value.

Horizontal use cases are widespread, such as tools like Google Workspace AI or Microsoft, but true value requires deeper integration.