Politecnico di Milano's AI Model & Manufacturing Leadership

Before the manufacturing sector can fully-embrace AI, executives must understand how the technology that they adopt will shape the way their business pursues a balance between conflicting objectives. 

The Politecnico di Milano (PoliMi) is developing frameworks to guide manufacturers and public entities in their AI adoption journey. This includes strategies for data and technologies, as well as skill redesign and regulations compliance. 

Giovanni Miragliotta is a Professor at the School of Management at Politecnico di Milano. He is also Co-Director at the Observatory on Artificial Intelligence and the AI Research and Innovation Centre at PoliMi. Miragliotta has a PhD in Management Engineering and started his academic career in 1999. Since then, he’s been researching and teaching in the field of Operations Management. 

“I joined the Digital Innovation research team in 2004,” says Miragliotta. “Through the years I’ve opened several research lines, such as IoT, digital payments, Industry 4.0, 5G, and AI.”

Charting the AI Landscape with data and framework

As the Director of the university’s Artificial Intelligence Observatory, Miragliotta is working across four areas of research with his team:

Mapping AI and its application landscape

Both public and private organisations are leveraging AI-powered solutions to enhance their capabilities. By mapping AI and its application landscape, Miragliotta believes that this can provide a basic yet essential piece of research, key to understanding the investments, skill requirements, benefits and barriers of AI.

Developing frameworks for the AI adoption journey

The second area consists of developing models to guide companies and public entities in their “AI adoption journey”. This includes strategies for data and technologies, as well as skill redesign and regulations compliance. 

Assessing data

The team is collecting quantitative data to assess the overall status of the Italian AI Strategy programme, which comprises research, talent development and retainment, and entrepreneurship, in order to give feedback to public authorities and review or confirm their governance actions. 

Developing models to estimate the impact of AI

The fourth area concerns the development of models to estimate the macro-economic impact of AI on, for instance, job creation and displacement in Italy. 

“The Observatory is a public source of first-hand information, accessible to any stakeholder looking for a comprehensive understanding of how AI is evolving in the country in relation to the rest of the European Union (EU) and other developed economies,” explains Miragliotta. 

Rethinking processes and priorities to thrive with Industry 5.0

Before companies rethink their processes and priorities in regards to Industry 5.0, there are several outstanding goals that need to be met first. 

“I’d start with data foundation, building a trusted and well-documented data layer connected with critical business decisions and the most relevant innovation projects,” says Miragliotta. “Second, managers must hone the skill to develop innovation portfolios capable of balancing short and long-term returns. Achieving such ambidexterity ability, which is still not common in most companies, must become a priority.”

Miragliotta feels that there is still a gap in the level of technological knowledge managers need to have to guide digital transformation. 

“Manufacturing executives need to reinforce open innovation practices, as no one alone can master all the skills that are necessary to succeed in our digital-first era. Collaboration with universities should thus be a priority, as higher education institutions are able to foster a culture of research and exploration, but of course, I’m biassed in my perception!”

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