The GenAI Implementation Challenge: Why Traditional Approaches Fall Short
Enterprises are racing to adopt GenAI, with 54% integrating it into service operations and 45% into supply chains.
Yet, only 1% have reached full maturity, hampered by talent shortages (60-80% harder to hire AI experts), ethical risks like bias and data privacy, scalability issues, and soaring integration costs. McKinsey reports that these barriers could slow adoption by 20-30%, potentially missing out on trillions in global GDP gains.
Traditional consultants focus on strategy, while in-house teams struggle with commoditized models like Llama or GPT-4. The result? 50-70% of GenAI projects fail without embedded expertise.