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For a financial services firm, managing this can be very challenging. A Forrester study found that 57% of financial organizations are still developing the necessary internal capabilities to fully leverage agentic AI. \u201c<\/strong>The data exists in many different formats, created over the course of a bank\u2019s history,\u201d says Mayzak. \u201cTake any bank that’s been around for 50 years: They might have 60 different types of PDFs for the exact same thing. And at the same time, we want the output of these systems to be 100% accurate. In many cases, there is no \u2018good enough\u2019.\u201d That is, companies need to do it right, and the first time.<\/p>\n An effective search platform is key to solving the problem of fragmented, poorly indexed, inaccessible data. Financial services companies that can readily sift through both their structured and unstructured data, keep it secure, and apply it in the right context will get the most value from agentic AI. This often requires designing AI systems with data access and utility in mind so they can work faster and yield more accurate results, as well as reduce risk. \u201cSearch is the foundational technology that makes AI accurate and grounded in real data,\u201d Mayzak says. \u201cSearch platforms have become the authoritative context and memory stores that will power this AI revolution.\u201d<\/p>\n Once in place, these AI-enhanced searches and autonomous systems can serve financial services companies for a range of purposes. When monitoring client exposure, agentic AI can continuously scan transactions, market signals, and external data to detect emerging risks; platforms can then automatically flag or escalate issues in real time. In trade monitoring, AI agents can review trade workflows, identify discrepancies across different formats, and resolve exceptions step by step with minimal human intervention. In regulatory reporting, AI can gather data from across systems, generate required reports, and track how each output was produced. These applications of AI save time while supporting audit and compliance needs by being traceable and explainable.<\/p>\n Although such capabilities already exist, they are often manual, fragmented, and difficult to scale. Agentic AI allows financial organizations to move toward more automated, efficient, and scalable processes while maintaining the accuracy and transparency required in their highly regulated environment. As Mayzak says, \u201cIt\u2019s not that different from how humans operate today, just done at a much faster pace and at scale.\u201d\u00a0<\/p>\n Launching agentic AI can be daunting, especially if other AI ventures have stalled internally. Mayzak\u2019s recommendation is to choose a manageable use case and allow it to grow over time. \u201cSuccess can build on success,\u201d he says. \u201cWhile companies may aim to automate a 70-step business process, they are discovering that you have to start somewhere. What is working in the market is tackling the problem one step at a time. Once you get the first step working, then you can take the next step, and the next.\u201d\u00a0<\/p>\n The financial services organizations that lead among their peers will be those that integrate agentic AI into a broader ecosystem that includes strong security controls, good data governance, and effective management of system performance. As Mayzak says, <\/strong>\u201cDoing this well will create an AI feedback loop, where executives gain new signals from these systems to assess the effectiveness of their investments and generate reliable, actionable insights.\u201d By iterating on pilots and continuously improving, companies will build agentic systems that can be measured, managed, and scaled. This will transform agentic AI into lasting competitive advantage.<\/p>\n Learn more about how Elastic supports financial services. This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review\u2019s editorial staff. It was researched, designed, and written by human writers, editors, analysts, and illustrators. This includes the writing of surveys and collection of data for surveys. AI tools that may have been used were limited to secondary production processes that passed thorough human review.<\/em><\/p>\n<\/p><\/div>\n #Data #readiness #agentic #financial #services<\/p>\n","protected":false},"excerpt":{"rendered":" For a financial services firm, managing this can be very challenging. A Forrester study found…<\/p>\n","protected":false},"author":1,"featured_media":10211,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[7],"tags":[3630,1265,80,8403,5133],"class_list":["post-10210","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-stories","tag-agentic","tag-data","tag-financial","tag-readiness","tag-services"],"featured_image_urls":{"full":["https:\/\/news678.top\/wp-content\/uploads\/2026\/05\/Elastic-iStock-2224485239.jpg",1200,600,false],"thumbnail":["https:\/\/news678.top\/wp-content\/uploads\/2026\/05\/Elastic-iStock-2224485239-150x150.jpg",150,150,true],"medium":["https:\/\/news678.top\/wp-content\/uploads\/2026\/05\/Elastic-iStock-2224485239-300x150.jpg",300,150,true],"medium_large":["https:\/\/news678.top\/wp-content\/uploads\/2026\/05\/Elastic-iStock-2224485239-768x384.jpg",640,320,true],"large":["https:\/\/news678.top\/wp-content\/uploads\/2026\/05\/Elastic-iStock-2224485239-1024x512.jpg",640,320,true],"1536x1536":["https:\/\/news678.top\/wp-content\/uploads\/2026\/05\/Elastic-iStock-2224485239.jpg",1200,600,false],"2048x2048":["https:\/\/news678.top\/wp-content\/uploads\/2026\/05\/Elastic-iStock-2224485239.jpg",1200,600,false],"covernews-featured":["https:\/\/news678.top\/wp-content\/uploads\/2026\/05\/Elastic-iStock-2224485239-1024x512.jpg",1024,512,true],"covernews-medium":["https:\/\/news678.top\/wp-content\/uploads\/2026\/05\/Elastic-iStock-2224485239-540x340.jpg",540,340,true]},"author_info":{"display_name":"admin","author_link":"https:\/\/news678.top\/?author=1"},"category_info":"Stories<\/a>","tag_info":"Stories","comment_count":"0","_links":{"self":[{"href":"https:\/\/news678.top\/index.php?rest_route=\/wp\/v2\/posts\/10210","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/news678.top\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/news678.top\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/news678.top\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/news678.top\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=10210"}],"version-history":[{"count":0,"href":"https:\/\/news678.top\/index.php?rest_route=\/wp\/v2\/posts\/10210\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/news678.top\/index.php?rest_route=\/wp\/v2\/media\/10211"}],"wp:attachment":[{"href":"https:\/\/news678.top\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=10210"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/news678.top\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=10210"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/news678.top\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=10210"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}Searching and securing results\u00a0<\/strong><\/h3>\n
Building an agentic AI ecosystem<\/strong><\/h3>\n
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