“One key reason is that organizations lack an Orchestrator for managing the AI lifecycle.”
— Mr. Jum Damrongsak Reetanon, Chief Infrastructure and Integration Officer
What is an Orchestrator, and why is it important?
Implementing AI in an organization is like running an orchestra with many different instruments. Even if you have talented musicians, without a conductor to guide the rhythm, volume, and harmony, the music will lack cohesion. Similarly, managing an AI project requires someone who sees the big picture—an Orchestrator—who can align technical and business elements to work together efficiently, ensuring the final output truly meets organizational goals.
Challenges and Complexity in Managing the AI Lifecycle
- Different perspectives : Technical teams focus on model creation and management, while business leaders expect AI to drive better business outcomes. The Orchestrator bridges these viewpoints.
- Misunderstanding AI : Many think AI is only Generative AI or ChatGPT, but it also includes Predictive Models for specialized analytics, such as AI for reading X-rays.
- ESG and energy considerations : Building AI models consumes significant energy. Poor planning can negatively impact an organization’s ESG KPIs.
- Model selection and integration : Different AI models have different strengths. Choosing and combining the right models to meet business needs requires expert guidance.
- Cybersecurity concerns : AI often processes sensitive data. Using external cloud services increases the risk of data leakage, making risk management critical.
Key Considerations in the AI Lifecycle
- Data security and protection : Careful planning is needed to safeguard sensitive data both on-premises and in the cloud.
- Post-Implementation Care : Beyond building AI applications, organizations must ensure continuous operation, including stability management, data backup and recovery, vulnerability management, and regular system updates.
- Cross-functional coordination : Large AI projects may involve multiple technologies. A person overseeing the whole picture ensures all components work smoothly toward business goals.
MFEC’s Experience and Readiness
MFEC recognizes the importance of managing the AI lifecycle and has established an AI Lab to drive AI technologies across various organizational functions. We have experience applying AI to solve real business problems with an Orchestrator perspective, effectively managing complexity.
We are ready to provide consulting and AI lifecycle management strategies for any organization, enabling AI to become an orchestra that plays the symphony of business success beautifully and sustainably.
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