Understanding the Deployment Crisis
The decline in successful deployments can be attributed to several factors:
Increasing Model Complexity: As organizations move beyond basic AI applications like image recognition and speech automation, they're attempting to implement more sophisticated solutions that require significantly more resources and expertise.
Data Quality Challenges: The complexity of newer AI models demands higher-quality data, which is becoming increasingly difficult to source and maintain.
Resource Constraints: Many organizations lack the technical resources and tools necessary to properly implement and maintain advanced AI systems.