Realities and promises of AI to accelerate, simplify and enrich quality control and product data production.
While AI is the subject of many discussions, many people are testing its value on use cases from their day-to-day business, or enriching their solution with mechanisms derived from artificial intelligence.
Behind the exaggerations and fears that this technology can bring, several important ideas must be kept in mind:
- AI is a tool for accelerating the synthesis or production of high-value data after an essential learning phase.
- Like any process, if fed with poor-quality data, it will produce disappointing results.
- As a revolutionary tool, the aim of AI is not to replace human work, but to improve productivity and focus on higher value-added actions.
On February 27, Micropole and Stibo Systems invite you to join us for a lunchtime discussion on the strategic and business challenges of AI. We'll be delighted to welcome Galeries Lafayette, who will talk about their vision of AI's contribution to their PIM 3.0 project.
To register, click here 
Sign up now!
📅 February 27
⏰ From 11:30 a.m.
📍 La Fabrique Générale (Paris 17e)
Presentation program
- Challenges and specificities of product data in relation to business challenges
- AI as a productivity tool for Data Managers
- AI at the service of Product Experience for consumers
- AI and Product Data, testimonial: feedback and vision on Galeries Lafayette's strategy
AI & Data management
For companies in the distribution and manufacturing sectors, the task of data management and data quality control has become a cumbersome, time-consuming process, and a major cost center. Connecting, enriching, controlling and enhancing data are now tasks largely affected by digital, regulatory constraints and new consumer demands.
This raises many questions about the possible role of AI in data management:
- How can AI help meet the challenges of product data quality and richness, while reducing human workload, costs and time-to-market?
- Should AI be seen as a data quality tool (classification, consistency, validity...) or as a solution for generating information, images and content?
- What are the dangers of generative AI to enrich product data?
- How can AI enable ultra-personalization of product data for new end-consumer experiences?
- How can we be sure that these AI algorithms are effective?
At this key event, Micropole and Stibo Systems will have the opportunity to answer all these questions.
Our Speakers
- Pascal Anthoine, Data Governance & Management Director
Micropole - Fabrice KOUAMOLuxury & Retail Data Governance Advisor
Micropole - Vincent Sprit, Solution Consultant
StiboSystems - Béatrice Mouchet, Customer IS Manager, Store Sales Front & ecom
Galeries Lafayette - Julien Perronnet, Digital SEO Manager
Galeries Lafayette
Practical information
- 11:30 a.m.: Welcome
- 12:00: State of the art in AI, acculturation and feedback
- 1:00 pm: Cocktail lunch