POC’s are usually carried out on rather simple algorithms using immediately available training data or internally labeled data. The main goal is to show that an algorithm can be trained to address a particular use case with a small amount of training data. The production stage represents a higher level of complexity for your AI project. Indeed, you are no more trying to prove that the solution works but that it can integrate within the company infrastructure and perform well in real-life conditions. In my opinion, organizations should invest in many proofs of concept because they can relatively learn about their potential, improve their data culture, quickly end AI PoCs that aren’t going anywhere, and identify the most promising approaches to continue monitoring and investing resources in. Companies should also take into consideration that the skills needed to make a proof of concept are very different from the skills needed to scale an idea to production. It is obvious but without a structure to support AI integration, even the best projects will die. All forms of data modeling for a PoC have to simplify and yet represent reality, and in the process, some authenticity is always lost. This creates risks for machine learning, as real-world data may be more prone to modeling issues than the training data used for the Proof of Concept (POC).

AI integration in Information Systems

The AI solution might be ready but you are not done yet. Indeed, real-scale implementation also involves interfacing AI with production information systems and architectures. Through my experience, I came to the conclusion that of the biggest issues in AI deployments is the difficulty to integrate cognitive projects with existing processes and systems. The best option is to use machine learning models written as APIs or as program code modules within existing systems. When it comes to AI projects, PoCs are very helpful whether they are successful or not. I believe that through a special process (data analysis, company adaptation, etc.), we could potentially increase the chance to see a PoC reach the production stage.



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