{"id":21767,"date":"2026-04-22T17:21:02","date_gmt":"2026-04-22T17:21:02","guid":{"rendered":"https:\/\/scannn.com\/real-world-gen-ai-use-cases-from-industry-leaders\/"},"modified":"2026-04-22T17:21:02","modified_gmt":"2026-04-22T17:21:02","slug":"real-world-gen-ai-use-cases-from-industry-leaders","status":"publish","type":"post","link":"https:\/\/scannn.com\/lv\/real-world-gen-ai-use-cases-from-industry-leaders\/","title":{"rendered":"Real-world gen AI use cases from industry leaders"},"content":{"rendered":"


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We first published this list two years ago at Next \u201824, as the agentic era was just dawning. Watching this list grow \u2014 propelled by our customer\u2019s enthusiastic commitment to AI \u2014 proves we are now firmly in the era of the agentic enterprise.\u00a0<\/p>\n

This almost certainly is the fastest technological transformation we\u2019ve seen, and customers are driving it. Production AI and agentic systems are now deployed in meaningful ways across virtually every one of the thousands of organizations joining us this week in Las Vegas for Next \u201826.\u00a0<\/p>\n

To celebrate our customers\u2019 work, we\u2019re expanding this list once again, adding hundreds more, and now well beyond the 101 we started with. The vast majority showcase impactful applications of agentic AI, built with tools like Gemini Enterprise, Gemini CLI, Security Command Center, and our AI Hypercomputer infrastructure stack.<\/p>\n

Like the thousands of organizations mentioned here, we thought it would be fitting to enlist the help of AI to get some interesting perspectives. Especially with the list having grown so long, it would be hard to read in one go without the benefit of an LLM.\u00a0<\/p>\n

We uploaded the complete dataset to Gemini Enterprise, running the latest Gemini Pro models for its deep research capabilities, and asked to surface the ten most notable trends and insights. Our team then reviewed the output and selected our five favorites, refining them with our own input. Here are those, which actually nicely reflect many of the thousands of conversations we\u2019ve had about gen AI over the past two years:<\/p>\n

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  1. The shift from assistants to agentic teams:<\/b> The most significant trend is the transition from AI as a passive assistant to AI as an active part of the team, where specialized agents can orchestrate entire workflows. For example, supply chain agents are talking to compliance agents, which then trigger financial forecasting agents \u2014 all autonomously. The business opportunity lies in building the management and governance frameworks for these agentic task forces.<\/li>\n
  2. Natural language is the translator for legacy IT:<\/b> A massive, challenging, but highly lucrative trend is using AI to unlock legacy systems. Organizations are using Gemini to build natural language interfaces on top of 40-year-old SAP instances, mainframes, and COBOL codebases. This allows non-technical staff to query complex, siloed data simply by asking a question, bypassing IT bottlenecks and modernizing old infrastructure without migrating it.<\/li>\n
  3. Gen media as a low-marginal-cost factory:<\/b> With models like Veo 3 and Imagen 4, media creation is shifting from strictly a manual production process to a computational one. Brands like WPP and Authentic Brands Group are turning a single hypothesis into hundreds or even thousands of personalized, cinematic creative variations in hours. It\u2019s bringing a whole new process to marketing, creating hyper-personalized, real-time creative computation.<\/li>\n
  4. Multimodality digitizes the physical world:<\/b> AI is bounding beyond the browser. You can transmit live video feeds, architectural blueprints, environmental sensors and so much more into multimodal models to gain a better understanding of a project. We see AI actively monitoring factory floors for safety hazards, evaluating physical shelf inventory via robotics, and even analyzing athlete biomechanics from smartphone footage. There\u2019s a lot of space to explore spatial AI.<\/li>\n
  5. Cybersecurity Moves to Agentic Auto-Remediation:<\/b> The threat landscape has evolved, and so has the defense. Security teams are no longer just using AI to detect anomalies. Platforms are deploying AI agents that can automatically write detection rules, isolate compromised workloads, and deploy “honeytokens” to trick malicious actors. AI is actively hunting and neutralizing tier-1 threats without human intervention.<\/li>\n<\/ol>\n

    We hope these insights spark inspiration for your own business \u2014 or that you\u2019ll come up with your own. Try it for yourself in Gemini Enterprise or NotebookLM to see what ideas you can uncover for your teams. It might even make it onto the list next time!\u00a0<\/p>\n\n

    The list is organized by 11 major industry groups, and within those, six agent types:<\/i> Customer<\/i><\/b>,<\/i> Employee<\/i><\/b>,<\/i> Creative<\/i><\/b>,<\/i> Code<\/i><\/b>,<\/i> Data<\/i><\/b> and<\/i> Security<\/i><\/b>. There are 301 new entries in this edition, denoted with an asterisk (*) before the organization\u2019s name.<\/i><\/p>\n<\/div>\n


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    We first published this list two years ago at Next \u201824, as the agentic era was just dawning. Watching this list grow \u2014 propelled by our customer\u2019s enthusiastic commitment to AI \u2014 proves we are now firmly in the era of the agentic enterprise.\u00a0 This almost certainly is the fastest technological transformation we\u2019ve seen, and […]<\/p>\n","protected":false},"author":1,"featured_media":21768,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[100],"tags":[],"class_list":["post-21767","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-google"],"_links":{"self":[{"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/posts\/21767","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/comments?post=21767"}],"version-history":[{"count":0,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/posts\/21767\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/media\/21768"}],"wp:attachment":[{"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/media?parent=21767"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/categories?post=21767"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/scannn.com\/lv\/wp-json\/wp\/v2\/tags?post=21767"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}