{"id":23448,"date":"2025-03-19T19:22:34","date_gmt":"2025-03-19T18:22:34","guid":{"rendered":"https:\/\/tiledesk.com\/senza-categoria\/il-costo-del-ritardo-le-sfide-delladozione-dellintelligenza-artificiale-e-la-soluzione-tiledesk\/"},"modified":"2025-05-07T13:19:49","modified_gmt":"2025-05-07T11:19:49","slug":"il-costo-del-ritardo-le-sfide-delladozione-dellintelligenza-artificiale-e-la-soluzione-tiledesk","status":"publish","type":"post","link":"https:\/\/tiledesk.com\/it\/blog-it\/il-costo-del-ritardo-le-sfide-delladozione-dellintelligenza-artificiale-e-la-soluzione-tiledesk\/","title":{"rendered":"Il costo del ritardo: le sfide dell’adozione dell’intelligenza artificiale e la soluzione Tiledesk"},"content":{"rendered":"

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Per le aziende di medie dimensioni, l’intelligenza artificiale promette di rivoluzionare la produttivit\u00e0 e la competitivit\u00e0. Eppure, per molti, questa promessa appare irraggiungibile. Flussi di lavoro obsoleti, complessit\u00e0 IT e soluzioni rigide spesso rendono l’adozione dell’intelligenza artificiale pi\u00f9 un onere che un vantaggio. <\/p> \n

\nThis isn\u2019t just a technical issue \u2014 it\u2019s a strategic one. Falling behind on AI adoption means not only losing out on productivity gains but also missing opportunities to innovate and thrive in a rapidly changing market. \n

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Il vero problema: perch\u00e9 l\u2019adozione dell\u2019intelligenza artificiale \u00e8 in stallo<\/strong><\/h2> \n

\nThe potential of AI is undeniable. Early studies suggest that AI adoption can significantly boost productivity. Firm-level research indicates that AI can yield productivity increases ranging from 10% to 56%<\/strong>, depending on the use case (Source: OECD, \u201cThe impact of Artificial Intelligence on productivity, distribution and growth\u201d<\/a><\/em>). For customer support teams, the impact is equally compelling: a study involving 5,000 agents found that access to generative AI assistants increased productivity by 14% on average<\/strong>, with the greatest benefits seen among less experienced workers (Source: \u201cGenerative AI at Work\u201d<\/a><\/em>). \n

\nYet, despite these clear benefits, adoption remains a challenge:<\/span> \n

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    1. L’integrazione \u00e8 travolgente<\/strong><\/span>I sistemi legacy e la complessit\u00e0 dell’IT creano barriere significative. In Europa, l’81% delle organizzazioni di medie dimensioni<\/strong> fatica a scalare, aggiornare e preparare al futuro i propri stack tecnologici nell’era dell’intelligenza artificiale ( <\/span>Source:<\/span> Censuswide, \u201cMid-market tech challenges report\u201d<\/a><\/em>).<\/span><\/li> \n\r\n\r\n \n
    2. Gli strumenti generici sono carenti<\/strong><\/span>Chi adotta l’IA ad alte prestazioni spesso si affida a soluzioni personalizzate o proprietarie. Tuttavia, molte aziende faticano ad allineare gli strumenti di IA generici ai propri flussi di lavoro specifici, con conseguenti inefficienze e scalabilit\u00e0 limitata. <\/span>Source:<\/span> McKinsey, \u201cThe State of AI in Early 2024\u201d<\/a><\/em>).<\/span><\/li> \n\r\n\r\n \n
    3. Esclusione dei team non tecnici<\/strong><\/span>AI tools often cater to technical users, leaving non-technical teams sidelined. Only 15% of non-technical users<\/strong> successfully adopt low-code AI tools without guided workflows or feedback loops. This gap slows organization-wide adoption and hinders productivity ( <\/span>Source: <\/span>\u201c<\/span>IDA: Breaking Barriers in No-Code UI Automation Through Large Language Models and Human-Centric Design\u201d<\/a><\/em>).<\/span><\/li> \n \n \n \n

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      Il costo del non fare nulla<\/strong><\/h2>\r\n

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      The stakes for mid-sized businesses in Europe are higher than many realize. Each year, the productivity losses from failing to modernize workflows and adopt AI solutions are staggering:<\/p> \n