{"id":29960,"date":"2026-05-25T12:00:00","date_gmt":"2026-05-25T10:00:00","guid":{"rendered":"https:\/\/res-group.eu\/?p=29960"},"modified":"2026-07-21T15:48:31","modified_gmt":"2026-07-21T13:48:31","slug":"ai-adoption-enterprises-europe-italy","status":"publish","type":"post","link":"https:\/\/res-group.eu\/en\/article\/ai-adoption-enterprises-europe-italy\/","title":{"rendered":"AI Adoption in Enterprises: Europe and Italy Compared"},"content":{"rendered":"<div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1248px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_1 1_1 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:100%;--awb-margin-top-large:0px;--awb-spacing-right-large:1.92%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:1.92%;--awb-width-medium:100%;--awb-order-medium:0;--awb-spacing-right-medium:1.92%;--awb-spacing-left-medium:1.92%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-1\"><p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"3:1-3:282;57-338\">In recent years, <strong>Artificial Intelligence<\/strong> has become a fixture in the language of business. First as a topic for experimentation, then as a lever for efficiency, and today increasingly as <strong>a potential driver of transformation for processes, skills, and organizational models<\/strong>.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"5:1-5:282;340-621\">The real question, though, is understanding what &#8220;<strong>adopting AI<\/strong>&#8221; actually means. Using a single generative tool, introducing automation in a few departments, or rethinking business processes around data, governance, and skills \u2014 these represent very different levels of maturity.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"7:1-7:254;623-876\">This is where the debate on enterprise innovation gets more interesting. It&#8217;s no longer enough to ask how many companies are using AI. The more useful question is: <strong>how many are managing to turn it into operational, measurable, and sustainable value?<\/strong><\/p>\n<blockquote class=\"ml-2 border-l-4 border-&#091;hsl(var(--border-300)\/0.1)&#093; pl-4 text-text-300\" dir=\"auto\" data-sourcepos=\"9:1-9:462;878-1339\">\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"9:3-9:462;880-1339\">The research reviewed points to a consistent picture: AI is spreading fast across enterprises, but adoption is outpacing organizations&#8217; ability to govern it. The data show clear growth in Europe and in Italy, alongside a still-significant gap between tool usage, digital maturity, internal skills, and process integration. The real challenge, then, isn&#8217;t just introducing AI \u2014 it&#8217;s making it part of a more mature, measurable, and sustainable operating model.<\/p>\n<\/blockquote>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_82_2 counter-hierarchy ez-toc-counter ez-toc-custom ez-toc-container-direction\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Contents<\/p>\n<label for=\"ez-toc-cssicon-toggle-item-6a64393345f69\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #231d1c;color:#231d1c\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewBox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #231d1c;color:#231d1c\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewBox=\"0 0 24 24\" version=\"1.2\" baseProfile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-6a64393345f69\"  aria-label=\"Toggle\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1 ' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/res-group.eu\/en\/article\/ai-adoption-enterprises-europe-italy\/#AI_adoption_in_enterprises_what_the_European_and_Italian_data_show\" >AI adoption in enterprises: what the European and Italian data show<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/res-group.eu\/en\/article\/ai-adoption-enterprises-europe-italy\/#Why_adopting_AI_doesnt_yet_mean_transforming_the_company\" >Why adopting AI doesn&#8217;t yet mean transforming the company<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/res-group.eu\/en\/article\/ai-adoption-enterprises-europe-italy\/#AI_and_innovation_processes_where_usage_is_most_mature\" >AI and innovation processes: where usage is most mature<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/res-group.eu\/en\/article\/ai-adoption-enterprises-europe-italy\/#Skills_governance_and_data_the_conditions_for_using_AI_well\" >Skills, governance, and data: the conditions for using AI well<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/res-group.eu\/en\/article\/ai-adoption-enterprises-europe-italy\/#AI_investment_growth_expectations_and_process_integration\" >AI investment: growth, expectations, and process integration<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/res-group.eu\/en\/article\/ai-adoption-enterprises-europe-italy\/#From_adoption_to_governance_the_organizational_challenge_of_AI\" >From adoption to governance: the organizational challenge of AI<\/a><ul class='ez-toc-list-level-3' ><li class='ez-toc-heading-level-3'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/res-group.eu\/en\/article\/ai-adoption-enterprises-europe-italy\/#Bibliography\" >Bibliography<\/a><\/li><\/ul><\/li><\/ul><\/nav><\/div>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-&#091;1.125rem&#093; font-bold\" dir=\"auto\" data-sourcepos=\"11:1-11:71;1341-1411\"><span class=\"ez-toc-section\" id=\"AI_adoption_in_enterprises_what_the_European_and_Italian_data_show\"><\/span>AI adoption in enterprises: what the European and Italian data show<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"13:1-13:480;1413-1892\">At the European level, AI adoption among enterprises is growing. According to <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"#bibliography\"><strong>Eurostat<\/strong><\/a>, in 2025 <strong>19.95% of EU enterprises with 10 or more employees<\/strong> use AI technologies. Size plays a big role here too: AI is used by <strong>17% of small enterprises<\/strong>, <strong>30.36% of medium-sized enterprises<\/strong>, and <strong>55.03% of large enterprises<\/strong>. Eurostat notes that this gap can be explained by factors such as implementation complexity, economies of scale, and investment costs.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"15:1-15:402;1894-2295\">The Italian picture fits this same trajectory. The <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"#bibliography\"><strong>ISTAT<\/strong><\/a> report shows that in 2025, <strong>16.4% of Italian enterprises with 10 or more employees<\/strong> use at least one AI technology, up from <strong>8.2% in 2024<\/strong> and <strong>5.0% in 2023<\/strong>. Growth is even more pronounced among large enterprises, which went from <strong>32.5% in 2024 to 53.1% in 2025<\/strong>; among SMEs, usage doubled, from <strong>7.7% to 15.7%<\/strong>.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"17:1-17:394;2297-2690\">These figures confirm a clear trend: AI is no longer confined to a handful of experimental cases or large tech groups. At the same time, they reveal a <strong>still-significant gap between large and smaller enterprises<\/strong>. It&#8217;s not just a matter of access to tools, but of the ability to integrate them into organizational contexts that often differ widely in resources, skills, and digital maturity.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"19:1-19:502;2692-3193\">Overall digitalization levels also help make sense of this. Still according to the same <strong>ISTAT survey<\/strong>, in 2025 nearly <strong>80% of Italian enterprises with 10 or more employees<\/strong> reach a basic level of digitalization, defined as adopting at least four out of twelve digital activities under the <em>Digital Intensity Index<\/em>. <strong>38.1%<\/strong> reach at least a high level, meaning at least seven out of twelve digital activities. Among large enterprises, these figures rise to <strong>96.4%<\/strong> and <strong>81.4%<\/strong> respectively.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"21:1-21:428;3195-3622\">The <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"#bibliography\"><strong>ITIR \u2013 University of Pavia<\/strong><\/a> research adds another layer, focusing on medium-to-large Italian enterprises. In the sample analyzed, <strong>59.8% of the workers<\/strong> surveyed report making at least some use of AI in their work. This varies sharply by role: adoption is highest among <strong>Top Managers<\/strong> (<strong>91.2%<\/strong>), among those who describe themselves as AI experts (<strong>89.7%<\/strong>), and among younger workers (<strong>71.9%<\/strong>).<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"23:1-23:24;3624-3647\">Three things stand out:<\/p>\n<ol class=\"&#091;li_&amp;&#093;:mb-0 &#091;li_&amp;&#093;:mt-1 &#091;li_&amp;&#093;:gap-1 &#091;&amp;:not(:last-child)_ul&#093;:pb-1 &#091;&amp;:not(:last-child)_ol&#093;:pb-1 list-decimal flex flex-col gap-1 pl-8 mb-3\" dir=\"auto\" data-sourcepos=\"25:1-27:87;3649-3824\">\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"25:1-25:46;3649-3694\">AI is growing rapidly, including in Italy;<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"26:1-26:43;3695-3737\">large enterprises remain ahead of SMEs;<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"27:1-27:87;3738-3824\">basic digitalization is widespread, but more advanced maturity remains less common.<\/li>\n<\/ol>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"29:1-29:97;3826-3922\">It&#8217;s in this gap between adoption and maturity that the more interesting discussion takes shape.<\/p>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-&#091;1.125rem&#093; font-bold\" dir=\"auto\" data-sourcepos=\"31:1-31:61;3924-3984\"><span class=\"ez-toc-section\" id=\"Why_adopting_AI_doesnt_yet_mean_transforming_the_company\"><\/span>Why adopting AI doesn&#8217;t yet mean transforming the company<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"33:1-33:423;3986-4408\">Internationally, several studies converge on one point: using AI doesn&#8217;t necessarily mean transforming the organization. The <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"#bibliography\"><strong>McKinsey<\/strong><\/a> report finds that companies are starting to build structures and processes to generate value from GenAI, but the journey is still in its early stages. Practices cited include redesigning workflows, strengthening governance, and bringing in senior roles to oversee AI.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"35:1-35:348;4410-4757\"><a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"#bibliography\"><strong>BCG<\/strong><\/a> also stresses the gap between potential and impact. According to their research, only 5% of the companies analyzed are classified as <em>future-built<\/em> \u2014 capable of generating AI value at scale; 35% are scaling AI and starting to generate value; the remaining 60% see only limited material benefits, despite their investments.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"37:1-37:493;4759-5251\">Italian evidence helps make this gap more concrete. Research from the <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"#bibliography\"><strong>Politecnico di Milano&#8217;s AI4Innovation Observatory<\/strong><\/a> distinguishes between occasional and structured use of AI in innovation processes. Occasional use is experimental, individual, and not integrated into processes; structured use involves defined workflows, dedicated tools, governance, and metrics. It&#8217;s precisely between these two modes that the real transformation of the innovation process plays out.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"39:1-39:455;5253-5707\">The <strong>ITIR \u2013 University of Pavia<\/strong> study confirms the same gap from a different angle. In the medium-to-large enterprises analyzed, AI is already widespread, but only 14.4% of workers feel they have meaningful competence in using these technologies. Moreover, just 1.8% of companies sit at a very advanced, deeply embedded stage of AI maturity. The data show that, despite growing diffusion, the process of organizational adoption often remains immature.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"41:1-41:519;5709-6227\">This distinction is central. One company may use generative tools to write text, analyze documents, or support day-to-day tasks without having genuinely changed how it works. Another may embed AI into core processes, defining responsibilities, metrics, controls, and adoption pathways. In both cases, you could say AI is &#8220;in use&#8221; \u2014 but the level of transformation is very different. The difference, then, isn&#8217;t the presence of the technology, but the organization&#8217;s ability to make it a stable part of how it operates.<\/p>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-&#091;1.125rem&#093; font-bold\" dir=\"auto\" data-sourcepos=\"43:1-43:59;6229-6287\"><span class=\"ez-toc-section\" id=\"AI_and_innovation_processes_where_usage_is_most_mature\"><\/span>AI and innovation processes: where usage is most mature<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"45:1-45:356;6289-6644\">International research shows that the value of AI depends less and less on simple access to tools, and more and more on the ability to embed them into processes. <strong>McKinsey<\/strong>, for instance, links value generation to the capacity for <em>rewiring<\/em> \u2014 rethinking how the organization works: workflows, governance, adoption, training, KPIs, and trust in outputs.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"47:1-47:241;6646-6886\">In the Italian context, the <strong>AI4Innovation Observatory<\/strong> report is particularly useful because it looks at how GenAI and Agentic AI enter the different stages of the innovation process, distinguishing between occasional and structured use.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"49:1-49:449;6888-7336\">In the <strong>front-end<\/strong> \u2014 the activities that precede a project&#8217;s formalization \u2014 AI is most widespread in the stages where experimentation is easiest. <em>Idea generation<\/em> is the area with the highest overall diffusion: 45% of companies report occasional use and 13% structured use. <em>PoC building<\/em> also shows a relatively more advanced level, with 18% structured use. By contrast, <em>idea evaluation<\/em> remains the least structurally supported stage, at 9%.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"51:1-51:275;7338-7612\">The pattern is clear: AI takes hold more easily where operational barriers are low, such as idea generation or prototype building. It struggles to become structural in stages that require greater trust in outputs, stronger governance, and review of decision-making criteria.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"53:1-53:545;7614-8158\">In the <strong>back-end<\/strong> of innovation \u2014 the stage where selected ideas are turned into concrete solutions \u2014 the picture is similar. <em>Knowledge management<\/em> is the most advanced area: about 60% of the sample reports at least some form of AI use, with 27% structured and 33% occasional. In <em>decision making<\/em>, on the other hand, fewer than one company in three has started integrating AI, and structured use sits at just 13%. In <em>project management<\/em>, 70% of the sample uses no AI tools to support project management, and only 12% report structured use.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"55:1-55:508;8160-8667\">The <strong>ITIR \u2013 University of Pavia<\/strong> report helps explain this gap from another angle: AI often enters organizations from the bottom up. 6.5% of respondents say they use paid AI applications at work funded out of their own pocket. This figure is higher among Experts, at 11.5%, and among profiles defined as Rebels, at 9.6%. It&#8217;s a sign of spontaneous, not always governed, adoption \u2014 one that can anticipate real needs, but also raises questions around security, data governance, and process standardization.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"57:1-57:298;8669-8966\">In short, AI is most easily used to search for information, generate ideas, summarize documents, or build prototypes. It becomes harder to integrate at the moments when an organization needs to make decisions, monitor projects, assign responsibilities, and change established operational routines.<\/p>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-&#091;1.125rem&#093; font-bold\" dir=\"auto\" data-sourcepos=\"59:1-59:66;8968-9033\"><span class=\"ez-toc-section\" id=\"Skills_governance_and_data_the_conditions_for_using_AI_well\"><\/span>Skills, governance, and data: the conditions for using AI well<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"61:1-61:345;9035-9379\">Internationally, the skills issue is especially visible among SMEs. The <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"#bibliography\"><strong>OECD<\/strong><\/a> report describes AI adoption among SMEs as still relatively low compared to other digital technologies and to large enterprises. The paper identifies connectivity, data, algorithms, computing capacity, skills, and finance as key enabling factors.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"63:1-63:363;9381-9743\">In Italy, the problem shows up very concretely. According to <strong>ISTAT<\/strong>, enterprises that don&#8217;t use AI but have considered adopting it point to five main obstacles: a lack of skills (<strong>58.6%<\/strong>), insufficient regulatory clarity (<strong>47.3%<\/strong>), unavailable or poor-quality data (<strong>45.2%<\/strong>), privacy and data protection concerns (<strong>43.2%<\/strong>), and high costs (<strong>43.0%<\/strong>).<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"65:1-65:476;9745-10220\">The <strong>AI4Innovation Observatory<\/strong> report also confirms how central skills are. <strong>96%<\/strong> of respondents believe new skills need to be developed within innovation teams to work effectively with GenAI and agents \u2014 <strong>52%<\/strong> significantly so, <strong>44%<\/strong> at least in part. To close these gaps, companies rely mainly on internal training (<strong>75%<\/strong> of respondents), followed by on-the-job upskilling through pilot projects (<strong>62%<\/strong>) and partnerships with vendors and consultants (<strong>48%<\/strong>).<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"67:1-67:298;10222-10519\">The data on sought-after profiles is equally interesting: <strong>51%<\/strong> of respondents prioritize hybrid profiles \u2014 people who combine innovation management skills with a baseline understanding of AI. Purely technical profiles, such as data scientists, ML engineers, or AI engineers, come in at <strong>32%<\/strong>.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"69:1-69:558;10521-11078\">The <strong>ITIR \u2013 University of Pavia<\/strong> research adds a complementary data point on governance. <strong>50.5% of enterprises<\/strong> run training activities, workshops, or events dedicated to AI. More structured solutions are far less common, though. Only <strong>17.0%<\/strong> of the sample has developed rules, regulations, or processes specifically designed for working with AI. Just <strong>16.3%<\/strong> has created dedicated AI roles, and a mere <strong>8.6%<\/strong> has an organizational unit fully dedicated to it. Formal governance and usage policies for AI are in place at <strong>21.1%<\/strong> of organizations.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"71:1-71:99;11080-11178\">In short, companies don&#8217;t just need new tools. They need to build the conditions to use them well:<\/p>\n<ul class=\"&#091;li_&amp;&#093;:mb-0 &#091;li_&amp;&#093;:mt-1 &#091;li_&amp;&#093;:gap-1 &#091;&amp;:not(:last-child)_ul&#093;:pb-1 &#091;&amp;:not(:last-child)_ol&#093;:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3\" dir=\"auto\" data-sourcepos=\"73:1-76:95;11180-11435\">\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"73:1-73:47;11180-11226\">widespread skills, not just specialist ones;<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"74:1-74:56;11227-11282\">clear governance over data, risk, and responsibility;<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"75:1-75:58;11283-11340\">processes redesigned around genuinely useful use cases;<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"76:1-76:95;11341-11435\">metrics that distinguish experimentation, expected productivity, and actual value generated.<\/li>\n<\/ul>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"78:1-78:323;11437-11759\">This is a meaningful distinction. AI can simplify repetitive tasks, speed up information analysis, and support operational decisions. Introduced without governance, though, it can have the opposite effect: disconnected tools, parallel workflows, duplicated data, untracked usage, and decisions that are hard to trace back.<\/p>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-&#091;1.125rem&#093; font-bold\" dir=\"auto\" data-sourcepos=\"80:1-80:64;11761-11824\"><span class=\"ez-toc-section\" id=\"AI_investment_growth_expectations_and_process_integration\"><\/span>AI investment: growth, expectations, and process integration<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"82:1-82:432;11826-12257\">Internationally, AI is now firmly established among investment priorities. The <a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"#bibliography\"><strong>Deloitte<\/strong><\/a> report notes that AI is moving from a phase of experimentation to one of deeper enterprise integration. Globally, <strong>25%<\/strong> of respondents say AI is having a transformative effect on their company, <strong>30%<\/strong> of organizations are redesigning key processes around AI, while <strong>37%<\/strong> say they&#8217;re still using it at a surface level.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"84:1-84:435;12259-12693\">In the Italian market, Deloitte finds that <strong>82% of the companies surveyed<\/strong> plan to increase their AI investments over the next year, and <strong>92%<\/strong> expect a productivity increase from adopting these tools. These are useful figures, but should be treated with caution: they measure the expectations, perceptions, and investment intentions of surveyed companies, not definitive proof of economic impact already realized across the board.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"86:1-86:504;12695-13198\">The <strong>AI4Innovation Observatory<\/strong> research adds a useful detail on the nature of investment among the Italian companies analyzed. The most frequently cited item is employee access to LLMs and generative tools, cited by <strong>73%<\/strong> of respondents. Next is the in-house development of custom solutions or solutions based on proprietary data, cited by <strong>67%<\/strong>. Vertical tools with built-in AI are cited by <strong>38%<\/strong>, low-code and no-code platforms by <strong>29%<\/strong>, while only <strong>9%<\/strong> report not investing in AI at all.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"88:1-88:552;13200-13751\">The <strong>ITIR \u2013 University of Pavia<\/strong> report offers a more cautious figure on actual, consolidated investment. Among the medium-to-large Italian enterprises in the sample, <strong>17.8%<\/strong> report making some form of AI investment, equal to at least 1% of their total budget. The report also notes that nearly <strong>55%<\/strong> of the sample either doesn&#8217;t know, or prefers not to disclose, the share of budget allocated to AI. This may reflect confidentiality concerns, but also limited spend traceability \u2014 consistent with AI adoption that is often hybrid and bottom-up.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"90:1-90:451;13753-14203\">This distribution points to two different levels of adoption. On one hand, access to general-purpose tools is often the first step \u2014 useful for spreading familiarity and boosting individual efficiency. On the other, developing custom solutions or ones based on proprietary data marks a more strategic shift: value doesn&#8217;t come only from access to the model, but from the ability to connect it to the organization&#8217;s own data, processes, and knowledge.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"92:1-92:374;14205-14578\">The stated priorities confirm this framing. According to the <strong>AI4Innovation Observatory<\/strong> report, <strong>72%<\/strong> of respondents name increased operational efficiency as a priority, and <strong>59%<\/strong> name automating repetitive tasks. <strong>43%<\/strong> cite exploring new opportunities and new business models, while <strong>40%<\/strong> point to improved decision quality thanks to a broader information base.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"94:1-94:289;14580-14868\">The point, then, isn&#8217;t just how much is invested, but where it&#8217;s invested and how deeply. Access to tools is necessary, but not enough to build a lasting advantage. The real difference lies in the ability to connect AI to proprietary data, core processes, internal skills, and governance.<\/p>\n<h2 class=\"text-text-100 mt-3 -mb-1 text-&#091;1.125rem&#093; font-bold\" dir=\"auto\" data-sourcepos=\"96:1-96:67;14870-14936\"><span class=\"ez-toc-section\" id=\"From_adoption_to_governance_the_organizational_challenge_of_AI\"><\/span>From adoption to governance: the organizational challenge of AI<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"98:1-98:395;14938-15332\">The sources reviewed tell a fairly clear story. AI in enterprises is growing fast, including in Italy. Large companies are ahead, SMEs are accelerating but remain more exposed to constraints in skills, resources, and digital maturity. Investment is rising, expectations are high, but real transformation still depends on the ability to integrate AI into processes, data, governance, and skills.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"100:1-100:432;15334-15765\">The <strong>AI4Innovation Observatory<\/strong> research reinforces this reading, since it shows, at the level of individual innovation processes, the gap between occasional and structured use. AI is already present in many activities, but often as ad hoc support, mostly through general-purpose tools. Moving toward deeper integration requires a roadmap, skills, metrics, workflow redesign, and governance capable of guiding adoption over time.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"102:1-102:386;15767-16152\">The <strong>ITIR \u2013 University of Pavia<\/strong> report adds a decisive point: new forms of AI tend to enter companies even without explicit direction, through spontaneous initiatives, local experiments, and bottom-up practices. This is why the question isn&#8217;t just whether to adopt AI, but how to govern its spread before it becomes opaque, fragmented, or inconsistent with the organization&#8217;s goals.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"104:1-104:260;16154-16413\">In the coming years, the real divide probably won&#8217;t be between companies that &#8220;use&#8221; AI and those that don&#8217;t. It will be between organizations that introduce it as an add-on tool, and organizations that manage to embed it coherently into their operating model.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"106:1-106:229;16415-16643\">It&#8217;s a less visible distinction, but a far more concrete one. Because innovation, in business, isn&#8217;t measured only by the technology adopted. It&#8217;s measured by the ability to make it useful, governable, and sustainable over time.<\/p>\n<\/div><div class=\"fusion-text fusion-text-2\"><h3 class=\"text-text-100 mt-2 -mb-1 text-base font-bold\" dir=\"auto\" data-sourcepos=\"108:1-108:17;16645-16661\"><span class=\"ez-toc-section\" id=\"Bibliography\"><\/span>Bibliography<span class=\"ez-toc-section-end\"><\/span><\/h3>\n<ul class=\"&#091;li_&amp;&#093;:mb-0 &#091;li_&amp;&#093;:mt-1 &#091;li_&amp;&#093;:gap-1 &#091;&amp;:not(:last-child)_ul&#093;:pb-1 &#091;&amp;:not(:last-child)_ol&#093;:pb-1 list-disc flex flex-col gap-1 pl-8 mb-3\" dir=\"auto\" data-sourcepos=\"110:1-117:209;16663-18159\">\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"110:1-110:158;16663-16820\"><a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.bcg.com\/publications\/2025\/are-you-generating-value-from-ai-the-widening-gap\">BCG (2025) <em>Are You Generating Value from AI? The Widening Gap<\/em><\/a>.<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"111:1-111:205;16821-17025\"><a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.deloitte.com\/us\/en\/what-we-do\/capabilities\/applied-artificial-intelligence\/content\/state-of-ai-in-the-enterprise.html\">Deloitte (2026) <em>The State of AI in the Enterprise \u2013 2026 AI Report<\/em><\/a>.<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"112:1-112:205;17026-17230\"><a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/ec.europa.eu\/eurostat\/statistics-explained\/index.php?title=Use_of_artificial_intelligence_in_enterprises\">Eurostat (2025) <em>Use of artificial intelligence in enterprises<\/em><\/a>. Statistics Explained.<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"113:1-113:191;17231-17421\"><a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.itir.io\/itir-summit-2026\/itir-summit-2026-oltre-la-linea-rossa\/\">ITIR \u2013 University of Pavia (2026) <em>Oltre la linea rossa? Governo e diffusione dell&#8217;intelligenza artificiale<\/em><\/a>.<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"114:1-114:111;17422-17532\"><a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.istat.it\/comunicato-stampa\/imprese-e-ict-anno-2025\/\">ISTAT (2025) <em>Imprese e ICT \u2013 Anno 2025<\/em><\/a>.<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"115:1-115:227;17533-17759\"><a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.mckinsey.com\/capabilities\/quantumblack\/our-insights\/the-state-of-ai-how-organizations-are-rewiring-to-capture-value\">McKinsey &amp; Company (2025) <em>The State of AI: How organizations are rewiring to capture value<\/em><\/a>.<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"116:1-116:191;17760-17950\"><a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.oecd.org\/en\/publications\/ai-adoption-by-small-and-medium-sized-enterprises_426399c1-en.html\">OECD (2025) <em>AI adoption by small and medium-sized enterprises<\/em>. OECD Publishing<\/a>.<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"117:1-117:209;17951-18159\"><a class=\"underline underline underline-offset-2 decoration-1 decoration-current\/40 hover:decoration-current focus:decoration-current\" href=\"https:\/\/www.youtube.com\/watch?v=r80fR-hjXn8\">AI4Innovation Observatory \u2013 Politecnico di Milano (2026) <em>Innovazione &amp; AI nelle imprese italiane: Gen-AI &amp; Agentic-AI tra consapevolezza, prudenza ed azione<\/em><\/a>.<\/li>\n<\/ul>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"119:1-119:22;18161-18182\"><strong>A note on sources<\/strong><\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"auto\" data-sourcepos=\"121:1-121:538;18184-18721\">The sources cited don&#8217;t all measure the same phenomenon. <strong>ISTAT<\/strong> and <strong>Eurostat<\/strong> offer a statistical snapshot of AI adoption among enterprises. <strong>Politecnico di Milano<\/strong> and the <strong>University of Pavia<\/strong> take a closer look at maturity, innovation processes, and governance. <strong>McKinsey<\/strong>, <strong>BCG<\/strong>, <strong>Deloitte<\/strong>, and the <strong>OECD<\/strong> provide a managerial and international reading of the phenomenon. For this reason, the figures shouldn&#8217;t be read as directly comparable percentages, but as different vantage points on the same transformation.<\/p>\n<\/div><\/div><\/div><\/div><\/div>\n","protected":false},"excerpt":{"rendered":"<p>AI adoption is accelerating across Europe and Italy, but organizations are struggling to keep pace with governance. Data from ISTAT, Eurostat, McKinsey, BCG, and other sources reveal a growing gap between large enterprises and SMEs, and between occasional and structured AI use \u2014 pointing to skills, governance, and data as the real conditions for turning adoption into value.<\/p>\n","protected":false},"author":5,"featured_media":29969,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","footnotes":""},"categories":[240],"tags":[279,283,238],"class_list":["post-29960","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-article","tag-artificial-intelligence","tag-generative-ai","tag-innovation"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AI Adoption in Enterprises: Europe and Italy Compared - RES Group<\/title>\n<meta name=\"description\" content=\"AI adoption is growing fast in Europe and Italy. 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