On June 24, the Datanomix team held a hands-on workshop in Almaty on the topic "Data as an asset: practical monetization with AI." The event was held at the DoubleTree by Hilton Hotel and brought together more than 40 participants – CDO, CIO, Head of Data, as well as product and business executives interested in extracting real value from data.

The workshop was built around specific steps to generate and select monetization ideas, analyze their potential (using the Impact × Effort model), and design an implementation architecture based on Qlik and Talend. Participants received a tool that allows them to immediately put their knowledge into practice, forming pilot hypotheses for their teams.

• Alexander Polorotov opened a workshop with an analysis of the reasons why the introduction of AI in companies often does not have the expected effect, and presented approaches to avoid this.
• Nikita Susoev shared cases of implementing AI among Datanomix customers, demonstrated the impact of solutions on business metrics, and presented a framework that is used in brainstorm sessions with customers. All participants got access to a web application that implements this framework - it was created exclusively using AI tools.
• Alexander Kosobokov spoke about modern approaches to building data architecture in the era of active AI adoption.
• Aynash Gaisina focused on change management and how to ensure seamless integration of new technologies into large organizations.

Following the results of the event, the participants shared their feedback:

• “The approach of implementing AI was interesting, from hypothesis generation to Impact-Effort evaluation. I especially remember the framework and the open case exchange.”
• “I liked the framework for searching and scoring hypotheses for the use of AI, which gave a clear structure. I plan to repeat it with the team.”
• “It is important that not only the advantages were voiced, but also the real limitations — this created a sense of an honest, mature conversation about technology.”

Datanomix believes that it is possible to profit from data only when AI initiatives are based on real business objectives and are architecturally and organizationally ready for implementation.