What to do after an AI POC?
This question frequently arises in organisations that have validated an AI agent POC but are unsure about how to proceed in real-world conditions.
An AI POC validates technical feasibility, not operational capability.
After a POC, organisations must decide whether to abandon, frame or industrialise.
This decision is based on actual value, risks, reliability and the ability to operate the agent over time.
Without a clear operational framework, a POC remains isolated and often ends up being abandoned.
Why does this happen?
POCs are generally designed to test an idea quickly, without any real operational constraints.
They often lack:
- a clearly identified manager,
- measurable value indicators,
- rules of use and supervision,
- sustainable integration into the existing IT system.
The POC works… but no one knows what to do with it next.
To support you with these issues and provide you with all the answers, Coexya has developed a consulting service to give you a clear vision of your marketplace/e-commerce project and help you move forw
What happens if nothing is done?
When no clear decision is made after a POC:
- the agent is no longer maintained,
- quality gradually deteriorates,
- value is never demonstrated,
- teams lose confidence,
the project is shelved without any real feedback.
What needs to be put in place
After a POC, several options are possible depending on the context:
- stop the project if it is not delivering value,
- frame a limited transition to production,
- industrialise the agent with a clear operating framework.
In all cases, the following must be clarified:
- expected uses,
- acceptable risks,
- value indicators,
- operating and supervision rules.
Limitations and points to consider
Not all POCs should become products.
Attempting to industrialise too early or without measurable value is often counterproductive.
Conversely, allowing a POC to ‘live on its own’ creates technical and organisational debt.
Reading IAgents
In mature organisations, the ‘post-POC’ phase is treated as a separate phase, with clear decision-making criteria and a Run & Ops system adapted to AI agents.
IAgents is part of this approach to providing support after the trial phase.
