{"id":5191,"date":"2026-08-17T10:08:19","date_gmt":"2026-08-17T15:08:19","guid":{"rendered":"https:\/\/www.mspmovil.com\/en\/?p=5191"},"modified":"2026-08-17T10:08:19","modified_gmt":"2026-08-17T15:08:19","slug":"real-roi-of-ai-automation-in-2026-what-the-numbers-say","status":"publish","type":"post","link":"https:\/\/www.mspmovil.com\/en\/real-roi-of-ai-automation-in-2026-what-the-numbers-say\/","title":{"rendered":"Real ROI of AI automation in 2026: what the numbers say"},"content":{"rendered":"<p id=\"p-rc_8ca784834ab5e9b9-37\" data-path-to-node=\"2\"><span data-path-to-node=\"2,0\">MThere are two headlines about AI in business that seem to contradict each other<\/span><span data-path-to-node=\"2,2\">. The first states that 95% of generative artificial intelligence projects do not generate any economic return<\/span><span data-path-to-node=\"2,4\">. The second claims that SMEs that effectively automate their processes see an ROI of between 150% and 400% in the first year<\/span><span data-path-to-node=\"2,6\">. Both are true, and understanding why they coexist is the key to not confusing the SME automation processes ROI of a press headline with that of your actual business<\/span><span data-path-to-node=\"2,8\">.<\/span><\/p>\n<h2 data-path-to-node=\"3\">The scary figure: the 95% that sees no return<\/h2>\n<p id=\"p-rc_8ca784834ab5e9b9-38\" data-path-to-node=\"4\"><span data-path-to-node=\"4,0\">The report \u00abThe GenAI Divide: State of AI in Business 2025,\u00bb by the MIT NANDA initiative, analyzed 300 public AI deployments and interviewed 150 executives<\/span><span data-path-to-node=\"4,2\">. Its conclusion, highly cited in 2026, is that 95% of generative AI pilots stall without translating into a measurable impact on revenue or costs<\/span><span data-path-to-node=\"4,4\">. The cause is not the technology: it is that most of these projects are generic pilots. Disconnected from a specific process and lacking baseline data that would allow comparing the before and after<\/span><span data-path-to-node=\"4,6\">.<\/span><\/p>\n<h2 data-path-to-node=\"5\">The other side: where there is real ROI<\/h2>\n<p id=\"p-rc_8ca784834ab5e9b9-39\" data-path-to-node=\"6\"><span data-path-to-node=\"6,0\">That 95% mostly refers to large corporate open generative AI projects, not the automation of specific processes in SMEs<\/span><span data-path-to-node=\"6,2\">. There, the landscape changes: according to the ONTSI, only 36% of Spanish SMEs with more than 10 employees have implemented some type of automation, and among those that do so with a clearly defined process (billing, customer service, marketing), the first-year return typically ranges between 150% and 400%, with investment payback periods of between 2 and 6 months<\/span><span data-path-to-node=\"6,4\">. The difference does not lie in the technology used, but in the size and clarity of the problem being tackled<\/span><span data-path-to-node=\"6,6\">.<\/span><\/p>\n<h2 data-path-to-node=\"7\">How to calculate the real ROI of your automation<\/h2>\n<p id=\"p-rc_8ca784834ab5e9b9-40\" data-path-to-node=\"8\"><span data-path-to-node=\"8,0\">The most useful formula for an SME is simple: ROI = (H \u00d7 C) (I\/M) (T\/M)<\/span><span data-path-to-node=\"8,2\">. H is the monthly hours saved by the automated process, C is the hourly cost of the profile that did it manually (the INE places the average labor cost in Spain at \u20ac22.8\/h), I\/M is the monthly cost of the tool, and T\/M is the initial configuration investment amortized over the months of use<\/span><span data-path-to-node=\"8,4\">. Without a baseline figure of how much time and money the process cost before, it is impossible to prove later that the automation worked; that is precisely the error that explains much of the MIT&#8217;s 95%<\/span><span data-path-to-node=\"8,6\">.<\/span><\/p>\n<h2 data-path-to-node=\"9\">Processes with proven returns in SMEs<\/h2>\n<ul data-path-to-node=\"10\">\n<li>\n<p id=\"p-rc_8ca784834ab5e9b9-41\" data-path-to-node=\"10,0,0\"><span data-path-to-node=\"10,0,0,0\"><b data-path-to-node=\"10,0,0,0\" data-index-in-node=\"0\">Automated billing:<\/b> reduces processing time from 45 to 10 minutes per invoice and errors by up to 94%<\/span><span data-path-to-node=\"10,0,0,2\">.<\/span><\/p>\n<\/li>\n<li>\n<p id=\"p-rc_8ca784834ab5e9b9-42\" data-path-to-node=\"10,1,0\"><span data-path-to-node=\"10,1,0,0\"><b data-path-to-node=\"10,1,0,0\" data-index-in-node=\"0\">Customer service with AI:<\/b> documented cases of support cost reductions of up to 60% by freeing up hours of repetitive service<\/span><span data-path-to-node=\"10,1,0,2\">.<\/span><\/p>\n<\/li>\n<li>\n<p id=\"p-rc_8ca784834ab5e9b9-43\" data-path-to-node=\"10,2,0\"><span data-path-to-node=\"10,2,0,0\"><b data-path-to-node=\"10,2,0,0\" data-index-in-node=\"0\">Marketing automation:<\/b> 76% of the companies that incorporate it achieve a positive return before twelve months<\/span><span data-path-to-node=\"10,2,0,2\">.<\/span><\/p>\n<\/li>\n<li>\n<p id=\"p-rc_8ca784834ab5e9b9-44\" data-path-to-node=\"10,3,0\"><span data-path-to-node=\"10,3,0,0\"><b data-path-to-node=\"10,3,0,0\" data-index-in-node=\"0\">Predictive inventory management:<\/b> reductions in excess stock of up to 35% and in stockouts of up to 52%<\/span><span data-path-to-node=\"10,3,0,2\">.<\/span><\/p>\n<\/li>\n<\/ul>\n<h2 data-path-to-node=\"11\">Why projects that don&#8217;t succeed fail<\/h2>\n<p id=\"p-rc_8ca784834ab5e9b9-45\" data-path-to-node=\"12\"><span data-path-to-node=\"12,0\">The patterns of failure repeat themselves: automating twenty processes at once instead of completing one before moving to the next. Choosing the tool before measuring the process; and treating automation as an isolated technological expense rather than a workflow change with a clear person in charge<\/span><span data-path-to-node=\"12,2\">. The SMEs that do see ROI do the opposite: they diagnose a process. Fully automate it, measure the result for two or three months, and only then decide whether to scale to another process<\/span><span data-path-to-node=\"12,4\">.<\/span><\/p>\n<p id=\"p-rc_8ca784834ab5e9b9-46\" data-path-to-node=\"14\"><span data-path-to-node=\"14,0\">IT&#8217;s 95% and the 150-400% of well-executed SMEs are not incompatible figures: they represent the difference between launching generative AI without focus and applying process automation with a prior diagnosis<\/span><span data-path-to-node=\"14,2\">. For any company that in 2026 wants to talk about SME automation processes ROI with its own figures, the first step is not to choose the tool, but to measure how much the process it wants to automate currently costs<\/span><span data-path-to-node=\"14,4\">.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>MThere are two headlines about AI in business that seem to contradict each other. The first states that 95% of generative artificial intelligence projects do not generate any economic return. The second claims that SMEs that effectively automate their processes see an ROI of between 150% and 400% in the first year. Both are true, [&hellip;]<\/p>\n","protected":false},"author":8,"featured_media":5192,"comment_status":"open","ping_status":"open","sticky":true,"template":"","format":"standard","meta":{"footnotes":""},"categories":[121],"tags":[],"class_list":["post-5191","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-digital-business-es"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.1.1 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Real ROI of AI automation in 2026: what the numbers say - MSP Mobility<\/title>\n<meta name=\"description\" content=\"95% of generative AI projects yield no return, according to MIT. 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