A custom ChatGPT based on company data is a great way to boost efficiency and productivity. However, the success of a virtual assistant doesn’t just depend on technology development. A large part of its success is determined by implementation, where special attention must be paid to organizational processes and people’s habits.

Data science companies often focus solely on the data science itself. But for technology to provide real value, the central focus must be on business processes and human habits. Think of it like a theater production: even if all actors know their roles, the key to success is the staging – how the parts play together and how the audience experiences it.

Developing technology, like customizing ChatGPT for company data, is important, but it’s only half the challenge. Data and algorithms can create a great “script,” but without successful implementation, the audience vthe employees – might not accept it.

People have established habits, and even if they are inefficient, they aren’t easy to change. For example, if someone is used to receiving documents via email, they might resist a new tool that provides them faster. This is human nature, and it must be understood during the implementation process.

Our team focuses specifically on successful implementation. Our goal is to create a positive experience starting from the pilot project, giving the company a continuous sense of achievement. We want the virtual assistant to be easily accessible while changing existing habits as little as possible.

Instead of changing people’s habits, we aim to demonstrate how new technology helps them solve their problems. We train people, show them how the virtual assistant helps them work faster and more efficiently, and support them throughout the entire process. We train people, show them how the virtual assistant helps them work faster and more efficiently, and support them throughout the entire process.

Ultimately, the success of a virtual assistant is closely tied to its implementation. Technology development is only half of the equation – ensuring successful rollout and understanding human habits is the other half that determines the final result. Data science companies that focus on both technology and implementation are the ones that create the most value and achieve the best results.