Mapping Workflows Is the Key to Success in Artificial Intelligence Efficiency
The underlying reason why companies fail to get the expected performance from their artificial intelligence investments is the inability to integrate processes correctly. Research reveals that businesses redesigning their workflows can double their revenues.
A study conducted by researchers from INSEAD and Harvard Business School draws attention to the "mapping problem" experienced in the integration of artificial intelligence technologies into business processes. Experiments conducted on 515 companies prove that businesses reorganizing their workflows with a focus on artificial intelligence achieve much more successful results than their competitors regarding operational efficiency and customer acquisition.
The Mapping Problem and Loss of Efficiency
Although four years have passed since the widespread adoption of large language models, many companies still struggle to translate this technology into tangible performance increases. Researchers explain the primary reason for this situation as the failure to determine how artificial intelligence will be included in production processes and how surrounding activities will change.
Experimental Results and Tangible Gains
A randomized field experiment conducted on 515 early-stage companies showed that businesses exposed to examples of artificial intelligence-supported workflow design identified 44% more use cases. These companies increased their task completion rates by 12%, raised their customer acquisition probability by 18%, and nearly doubled their revenues.
Artificial Intelligence as a Continuous Transformation Process
Experts emphasize that the implementation of artificial intelligence should not be treated as a one-time setup, but rather as a continuous process. A thorough mapping of existing workflows, including a detailed examination of handoff points, decision bottlenecks, and delivery processes, is critically important to unlock the potential of the technology.