What Is an AI Integration Project in Business?

Understand the steps and challenges of an AI integration project in business, from initial idea to production deployment.

The term 'AI integration project' is increasingly used by businesses, but it covers very different realities depending on the context. Here is what it concretely involves.

A simple definition

An AI integration project involves incorporating an artificial intelligence building block, existing or custom-built, into a business process or product. This can range from adding a conversational assistant to a website all the way to developing a personalized recommendation system for an e-commerce platform.

The key steps of such a project

Scoping: identifying the precise business need and expected results
The technical choice: using an existing solution via an API or building a custom model
Development and testing: integrating the solution and verifying its reliability on real cases
Production deployment and ongoing performance monitoring

The skills involved

Depending on the project's scale, several profiles may be involved: a developer for technical integration, a data scientist if a custom model is needed, a project manager to coordinate stakeholders, and often a consultant to scope the need upstream.

A project that doesn't end at deployment

Unlike traditional software development, an AI project generally requires ongoing monitoring after it goes into production: a model's performance can shift over time, especially if the underlying data changes, which calls for regular adjustment. To better understand the different types of possible projects, read our complete guide to artificial intelligence in business and the projects related to artificial intelligence posted on the platform.