{"id":150308,"date":"2026-02-20T16:22:58","date_gmt":"2026-02-20T15:22:58","guid":{"rendered":"https:\/\/www.bbs.unibo.it\/?p=150308"},"modified":"2026-02-20T18:27:57","modified_gmt":"2026-02-20T17:27:57","slug":"150308","status":"publish","type":"post","link":"https:\/\/www.bbs.unibo.it\/en\/150308\/","title":{"rendered":"From classroom to enterprise: how AdoptAI was born"},"content":{"rendered":"

Transforming the potential of Artificial Intelligence<\/strong> into concrete business value<\/strong> requires strategic vision<\/strong>, method<\/strong>, and the ability to integrate diverse competences. It is from this awareness that the entrepreneurial journey of Stefano Urbani<\/strong> and Francesco Simonetti<\/strong> began \u2014 alumni of the Executive Master in Artificial Intelligence for Business at Bologna Business School<\/strong><\/a> and co-founders of AdoptAI<\/strong>.<\/p>\n

<\/p>\n

Stefano Urbani<\/strong> is an advisor with over twenty years of experience in strategy<\/strong>, M&A<\/strong>, growth<\/strong>, and turnaround<\/strong>, gained alongside entrepreneurs, boards, and senior executives across complex, multi-sector environments. His professional trajectory has always been oriented toward value creation<\/strong>, the redesign of operating models<\/strong>, and the management of transformation<\/strong>. Francesco Simonetti<\/strong> works in quantitative risk management<\/strong> and advanced analytics<\/strong>, with a background focused on quantitative models<\/strong>, data analysis<\/strong>, and the integration of AI into corporate decision-making processes<\/strong>. His perspective starts from numbers, modeling, and risk analysis<\/strong>, and evolves toward the development of more advanced and conscious decision systems<\/strong>.<\/p>\n

It was during the Executive Master in AI for Business that these competences began to converge into a shared project.<\/p>\n

\u201cThe idea emerged naturally during the Master,\u201d Stefano explains. \u201cRather than stemming from an individual intuition, it grew out of continuous discussion among classmates from different professional backgrounds but united by the same perception: Artificial Intelligence was entering the managerial debate with force, yet often remained distant from concrete applications within organizations.\u201d<\/p>\n

The issue was not technology itself, but the gap between enthusiasm and implementation<\/strong> \u2014 between narrative and execution.<\/p>\n

For Stefano, the shift was also personal:<\/p>\n

\u201cMy consulting background had already led me to observe companies through the lens of processes and value creation. During the Master, this perspective was enriched with new tools and languages, allowing me to interpret AI not as an isolated technology, but as a lever for the evolution of companies\u2019 operating models.\u201d<\/p>\n

Alongside the strategic dimension, Francesco emphasizes the importance of method<\/strong> and systemic thinking<\/strong>.<\/p>\n

\u201cThe Executive Master in AI for Business helped us make this transition in a very concrete way, starting from processes<\/strong>, data<\/strong>, and organizational impacts<\/strong> rather than tools. Frameworks such as \u2018from data to value\u2019 played an important role, but what truly made the difference was the systemic approach<\/strong>: connecting technology, operating model, and value creation.\u201d<\/p>\n

The real turning point came with the Project Work<\/strong> developed within a real corporate context. That was when theory was tested in practice.<\/p>\n

\u201cWorking on a concrete case forced us to translate theoretical models into operational choices,\u201d they explain. \u201cDefining priorities<\/strong>, identifying the necessary data<\/strong>, estimating the expected impact<\/strong>: that was the moment when AI stopped being a concept and began to become a project.\u201d<\/p>\n

From that experience, a clear approach matured: start from business processes<\/strong>, identify priority use cases<\/strong>, develop targeted Proofs of Concept<\/strong>, and build progressive adoption roadmaps<\/strong> to design sustainable implementation paths<\/strong>.<\/p>\n

This is how AdoptAI<\/strong> project came into being: not as a software house, but as a reality focused on the strategic adoption of AI<\/strong>. The objective is to guide organizations from initial interest to concrete implementation<\/strong>, reducing risk<\/strong> and validating value<\/strong> before scaling.<\/p>\n

Within this evolution, the organizational dimension<\/strong> also emerged strongly.<\/p>\n

\u201cAt the beginning, our focus was on application opportunities and market potential,\u201d they acknowledge. \u201cAs projects evolved, the need to introduce human-in-the-loop<\/strong> logic, supervision<\/strong>, and output validation<\/strong> became clear, especially when working with proprietary data and decision-making processes.\u201d<\/p>\n

The theme of governance<\/strong> and responsibility<\/strong> was not the starting point, but a stage of maturity in the project\u2019s development. Implementing AI means intervening in decision processes<\/strong>, corporate knowledge<\/strong>, and organizational dynamics<\/strong>: without control and awareness, innovation risks becoming fragile.<\/p>\n

At the same time, change management<\/strong> became a structural element of the AdoptAI model. Technological implementation<\/strong> alone is not enough. It requires competences, culture, and the ability to guide people through transformation<\/strong>.<\/p>\n

Reflecting on their journey, the advice for those aiming to launch an AI-driven project<\/strong> is clear.<\/p>\n

\u201cThe first mistake is starting from the technology,\u201d Francesco observes. \u201cIt is far more effective to begin with a concrete need, map the processes, and build Proofs of Concept to validate value before making structural investments.\u201d<\/p>\n

Stefano adds:<\/p>\n

\u201cAI is now technologically accessible, but creating value requires method<\/strong>, vision<\/strong>, and the ability to lead organizational change<\/strong>. It is this combination that transforms an AI-driven project into a solid and lasting entrepreneurial initiative<\/strong>.\u201d<\/p>\n

From classroom to enterprise, the transition was not a sudden leap, but a structured journey. The Executive Master provided frameworks<\/strong>, language<\/strong>, and method<\/strong>, while professional experience gave direction and substance.<\/p>\n

Today, AdoptAI<\/strong> represents the synthesis of this convergence: AI not as an end in itself, but as a lever for conscious<\/strong>, progressive<\/strong>, and value-oriented transformation<\/strong>.<\/p>\n","protected":false},"excerpt":{"rendered":"

Transforming the potential of Artificial Intelligence into concrete business value requires strategic vision, method, and the ability to integrate diverse competences. It is from this awareness that the entrepreneurial journey of Stefano Urbani and Francesco Simonetti began \u2014 alumni of the Executive Master in Artificial Intelligence for Business at Bologna Business School and co-founders of […]<\/p>\n","protected":false},"author":132,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[2],"tags":[],"rubrica":[708],"class_list":["post-150308","post","type-post","status-publish","format-standard","hentry","category-uncategorized","rubrica-alumni-pov-en"],"acf":[],"yoast_head":"\nFrom classroom to enterprise: how AdoptAI was born | BBS<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.bbs.unibo.it\/en\/150308\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"From classroom to enterprise: how AdoptAI was born | BBS\" \/>\n<meta property=\"og:description\" content=\"Transforming the potential of Artificial Intelligence into concrete business value requires strategic vision, method, and the ability to integrate diverse competences. 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