Taking Generative AI from Proof of Concept to Production

The journey from generative AI proofs of concepts (POCs) to full-scale production is often filled with challenges. While an initial POC can seem promising and exciting, the transition to production can be daunting due to factors including unrealistic ideas, unprepared data, and unclear benefits. However, by creating and executing a strategic planning process that ensures alignment with long-term objectives, organizations can streamline this transition effectively.

Challenges in Transitioning Generative AI POCs to Production
Transitioning generative AI POCs to production poses numerous challenges to organizations. Whether it's internal misalignment or a lack of understanding the technology, it's important to be aware of potential concerns before encountering them so you can proactively plan ahead.

Lack of Alignment with Organizational Objectives
One of the most significant challenges an organization can face in transitioning a POC to production is the lack of alignment with organizational objectives. Oftentimes the boards of an organization are saying "do gen AI," but no one is creating a clear roadmap of what needs to be done.

Without a clear understanding of how the POC aligns with the broader goals of the organization, it becomes difficult to justify investing the necessary resources. This misalignment often stems from a disconnect between the technical teams developing the POC and the business leaders setting organizational goals. To overcome this, it's important to establish a clear link between the POC and the organization's strategic objectives from the beginning so everyone in the organization is on the same page.