In recent years, the integration of Generative AI (GenAI) into creative and professional domains has reshaped the Design Thinking landscape. As GenAI tools are increasingly adopted, critical questions arise about how designers can harness their potential. However, a notable gap in the literature concerns the personal skills needed by design thinkers to cope with and leverage GenAI effectively. This thesis explores, therefore, the evolving role of design thinkers' individual dynamic capabilities in the era of Generative AI. To investigate this, a comprehensive literature review informed the research and the development of a Research Design Experiment, involving 110 participants from 26 companies and collecting a total of 265 written comments. Data were collected with a qualitative method and, through an abductive research approach, a coding tree framework methodology analysis was performed. The research results highlight the need for design thinkers to develop new dynamic capabilities in traditional sensing, seizing, and reconfiguring to effectively integrate GenAI into their design processes. Traditional design thinkers’ dynamic capabilities must evolve: sensing transforms into Sensing through GenAI, seizing into Seizing through GenAI and reconfiguring into Reconfiguring through GenAI. Furthermore, the study identifies the most suitable GenAI tools, whether image-based or text-based, and activity modalities, whether individual or group, to foster these capabilities evolution. Key findings revealed that Sensing through GenAI is best supported by individual work with image-based tools, Seizing through GenAI by individual work with text-based tools, and Reconfiguring through GenAI by group work with text-based tools. Finally, as a practical contribution, this thesis introduces a website platform prototype called Genexus, designed to support design thinkers and innovators in developing these new capabilities. Genexus was tested and validated through focus groups, confirming its relevance and effectiveness in real-world contexts. The platform bridges the gap between the research theoretical insights and practical applications, empowering users to leverage GenAI tools effectively and serving as a resource guide for the design thinking community. To conclude this thesis advances the current studies through newly developed frameworks that demonstrate how GenAI transforms traditional individual capabilities and underscores the importance of managers to strategically develop these capabilities, using targeted tools and working modalities to drive innovation.
Negli ultimi anni, l'integrazione dell'Intelligenza Artificiale Generativa (GenAI) nei contesti creativi e professionali ha ridefinito il panorama del Design Thinking. Con l'adozione sempre più diffusa degli strumenti GenAI, sorgono questioni critiche su come i designer possano sfruttare il loro potenziale. Tuttavia, un’ importante lacuna nella letteratura riguarda le competenze personali necessarie ai design thinker per affrontare e sfruttare efficacemente la GenAI. Questa tesi esplora, pertanto, il ruolo in evoluzione delle dynamic capabilities individuali dei design thinker nell'era dell'Intelligenza Artificiale Generativa. Per investigare questa tematica, una revisione completa della letteratura ha guidato la ricerca e lo sviluppo di un Research Design Experiment, che ha coinvolto 110 partecipanti provenienti da 26 aziende, raccogliendo un totale di 265 commenti scritti. I dati sono stati raccolti utilizzando un metodo qualitativo e, attraverso un approccio di ricerca abduttivo, è stata eseguita un'analisi metodologica basata su un framework di codifica ad albero. I risultati della ricerca evidenziano la necessità per i design thinker di sviluppare nuove dynamic capabilities nei tradizionali ambiti di sensing, seizing e reconfiguring per integrare efficacemente GenAI nei loro processi di design. Le dynamic capabilities tradizionali dei design thinker devono evolversi: sensing si trasforma in Sensing through GenAI, seizing in Seizing through GenAI e reconfiguring in Reconfiguring through GenAI. Inoltre, lo studio identifica gli strumenti GenAI, basati su immagini o su testi, e le modalità di attività, individuali o di gruppo, più adatti per favorire l'evoluzione di queste capacità. I principali risultati rivelano che Sensing through GenAI è meglio supportato dal lavoro individuale con strumenti basati su immagini, Seizing through GenAI dal lavoro individuale con strumenti basati su testi, e Reconfiguring through GenAI dal lavoro di gruppo con strumenti basati su testi. Infine, come contributo pratico, questa tesi introduce un prototipo di piattaforma website chiamata Genexus, progettata per supportare i design thinker e gli innovatori nello sviluppo di queste nuove capacità. Genexus è stata testata e validata attraverso focus group, confermando la sua rilevanza ed efficacia nei contesti reali. La piattaforma colma il divario tra gli approfondimenti teorici della ricerca e le applicazioni pratiche, consentendo agli utenti di sfruttare efficacemente gli strumenti GenAI e fungendo da guida per la comunità del Design Thinking. In conclusione, questa tesi avanza gli studi attuali attraverso lo sviluppo di nuovi framework che dimostrano come GenAI trasformi le tradizionali dynamic capabilities individuali e sottolinea l'importanza per i manager di sviluppare strategicamente queste capacità, utilizzando strumenti mirati e modalità di lavoro specifiche per promuovere l'innovazione.
Design thinking in the GenAI era : investigating the role of GenAI in design thinkers' capabilities evolution
Fedrigo, Annalisa
2023/2024
Abstract
In recent years, the integration of Generative AI (GenAI) into creative and professional domains has reshaped the Design Thinking landscape. As GenAI tools are increasingly adopted, critical questions arise about how designers can harness their potential. However, a notable gap in the literature concerns the personal skills needed by design thinkers to cope with and leverage GenAI effectively. This thesis explores, therefore, the evolving role of design thinkers' individual dynamic capabilities in the era of Generative AI. To investigate this, a comprehensive literature review informed the research and the development of a Research Design Experiment, involving 110 participants from 26 companies and collecting a total of 265 written comments. Data were collected with a qualitative method and, through an abductive research approach, a coding tree framework methodology analysis was performed. The research results highlight the need for design thinkers to develop new dynamic capabilities in traditional sensing, seizing, and reconfiguring to effectively integrate GenAI into their design processes. Traditional design thinkers’ dynamic capabilities must evolve: sensing transforms into Sensing through GenAI, seizing into Seizing through GenAI and reconfiguring into Reconfiguring through GenAI. Furthermore, the study identifies the most suitable GenAI tools, whether image-based or text-based, and activity modalities, whether individual or group, to foster these capabilities evolution. Key findings revealed that Sensing through GenAI is best supported by individual work with image-based tools, Seizing through GenAI by individual work with text-based tools, and Reconfiguring through GenAI by group work with text-based tools. Finally, as a practical contribution, this thesis introduces a website platform prototype called Genexus, designed to support design thinkers and innovators in developing these new capabilities. Genexus was tested and validated through focus groups, confirming its relevance and effectiveness in real-world contexts. The platform bridges the gap between the research theoretical insights and practical applications, empowering users to leverage GenAI tools effectively and serving as a resource guide for the design thinking community. To conclude this thesis advances the current studies through newly developed frameworks that demonstrate how GenAI transforms traditional individual capabilities and underscores the importance of managers to strategically develop these capabilities, using targeted tools and working modalities to drive innovation.File | Dimensione | Formato | |
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https://hdl.handle.net/10589/226736