Talents and New Skills – Focus on Labotec. The Intelligent Laboratory: Artificial Intelligence, Data Science, and the New Skills Required

Event organized by Cisita Parma

Today, the search for highly specialized young talent is a defining feature of the most dynamic, innovative, and technologically advanced professional environments. But how can we effectively connect talents, new skill sets, and the professional world within an increasingly fast-paced and ever-evolving business landscape?

“Talent Academy” is a special area within the new Labotec trade fair, created specifically for this purpose in partnership with Cisita Parma, the training body of UPI (Unione Parmense degli Industriali) and GIA (Gruppo Imprese Artigiane), both expressions of Confindustria in the Parma region.

The goal of Talent Academy is to foster a productive and virtuous meeting point between specialized training institutions and key representatives from the world of analysis laboratories, across a variety of sectors — from agri-food to the many branches of chemistry.

Session overview

Artificial Intelligence and Machine Learning for Advanced Data Analysis in Analytical Laboratories.

AI and machine learning are increasingly used to analyze data from imaging instruments — such as microscopes — and to predict analysis outcomes and support diagnostics through automated learning. These algorithms can identify patterns and anomalies that are difficult to detect manually, thereby improving the accuracy and efficiency of laboratory analyses. The analysis of large datasets (Big Data), when combined with AI, enables the identification of trends, prediction of future outcomes, and personalization of analytical processes.

Against this backdrop, the event aims to showcase the innovative potential of advanced data analysis in food testing laboratories, examining real-world applications and the new skill sets required for professionals in the sector. In food testing labs, image processing and analysis can help identify and classify food products more accurately, as well as detect contamination or quality issues more effectively. Microbiological quality control, which traditionally involves a high degree of repetitive manual tasks, is poised for major advancements in productivity, data integrity, and reliability through full automation of test execution and data management. Machine learning-based diagnostics can reduce human error and significantly improve the efficiency of laboratory operations.

These perspectives form the foundation of a talk designed to stimulate reflection and exchange, bringing together technical experts, industry representatives, and young talents from regional ITS Academies.

 The event will be held in Italian