According to the McKinsey Global Survey on AI (2022), the proportion of organizations using AI has plateaued between 50 and 60 percent for the past few years, impacting the increasing number of AI specialists that companies need to train or recruit. The international Erasmus+ Planet 4 consortium teamed up with universities from Spain, Poland, Italy, and Greece with the industrial sector and corporations to analyze how universities can contribute to meeting the demand for AI specialists.


New tasks for educational institutions and future talents

As the experts explain, the AI-everything trend brings out a new demand for universities and educational institutions which prepare tech specialists and engineers. “It is quite a complex task and multidisciplinary point of view as this coexistence must be framed within the current boundaries of ethics and responsibility, which usually advocates for transparency, explainability, and bias-free in AI systems that work together with humans in industrial environments”, says Dr Joan Navarro, a member of the Internet Technologies & Storage Research Group of the Salle – URL in Spain explains the current boom of artificial intelligence.

During the Erasmus+ program’s Planet 4 project, collaborating organisations and universities followed the insights from industrial digitalization needs and pains, and resurfaced meaningful insights. “For example, there is a latent need for real-time, not only for processing and storing and collecting them but also for generating them. That is, what can be done to adapt and retrofit existing machinery to generate more data that could be used to optimize processes and improve efficiency” points out Dr Navarro.

He and colleagues from Italian, Polish, and Greek universities, emphasised the most concerning signals from the industry and summarizes the focus on the security of industrial processes. It is becoming more critical with increased connectivity, as cyber threats pose potential risks that can cause business disruptions and significant financial losses. Consequently, securing systems and enhancing their resilience is now more vital than ever.

Improves the study curriculum

“From a technical point of view, we saw that one of the major issues in the application of Industry 4.0 to real industrial scenarios is the integration between hardware and software technology. The gap between Operation Technology solutions used for the control and management of industrial machines and Information Technology applications like ERP, MES and similar is still big and despite being tentative is still very far from being filled” explains an entrepreneur, an innovator and a researcher in Human-Computer Interaction design Daniele Mazzei from the University of Pisa (Italy).

Regarding these contexts, collaborations between industry and academia are necessary to develop training curriculums that are aligned with industry needs and, thus, provide students with access to real-world projects and mentorship.

Experts agree that when these circumstances are met, the coexistence of AI and humans in the industry sector has the potential to lead to significant improvements in productivity, efficiency, and innovation.

Depends on our ability to combine their strengths

“Actually, even the earlier forms of AI and humans have coexisted in the industry sector for a long time in different fields such as tasks automation in manufacturing, assistance in diagnosis and treatment for healthcare, customer services by means of chatbots, or trend analysis and predictions in finance”, says Dr Joan Navarro.

The fact that both AI and humans bring unique and complementary strengths to the table enables their successful coexistence: while AI can rapidly process large amounts of data in an automatic fashion, humans bring creativity and critical thinking.

“As we have seen so far, the successful coexistence between AI and humans depends on our ability to find ways to combine their strengths. Typically, this involves conceiving AI systems that work alongside humans to augment their capabilities, rather than replacing them entirely”, notes Dr Navarro.

For example, AI can be used to automate routine tasks, freeing up human workers to focus on more complex and strategic tasks that may require human intuition and expertise.

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About the Author: Daniele Mazzei

Daniele is the CPO and co-founder of Zerynth. His strong interest in the interaction between people and intelligent objects led him to co-found Zerynth and to design connected devices and Industrial IoT applications. After earning a PhD in Bioengineering and Biomedical Engineering, he is now an Associate Professor at the Department of Computer Science at the University of Pisa.

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