{"id":34745,"date":"2026-06-30T13:02:26","date_gmt":"2026-06-30T17:02:26","guid":{"rendered":"https:\/\/kapdec.com\/blog\/?p=34745"},"modified":"2026-07-11T08:22:34","modified_gmt":"2026-07-11T12:22:34","slug":"understanding-agentic-ai-differences-applications-and-future-implications-for-businesses","status":"publish","type":"post","link":"https:\/\/kapdec.com\/blog\/understanding-agentic-ai-differences-applications-and-future-implications-for-businesses\/","title":{"rendered":"Understanding Agentic AI: Differences, Applications, and Future Implications for Businesses"},"content":{"rendered":"<span class=\"span-reading-time rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\"> 2<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span><p>The use of AI agents, automated software systems capable of taking actions such as booking flights or handling digital tasks, is rapidly increasing in businesses. According to a report by MIT Sloan School of Management and Boston Consulting Group in November 2025, 35% of surveyed companies had already implemented AI agents, with 44% planning to adopt them soon. Phillip Isola, an associate professor at MIT studying agentic AI, explains the distinction between agentic AI and generative AI like ChatGPT. While generative AI creates content such as text and images, agentic AI performs actions either physically, like in robotics, or digitally.<\/p>\n<p>Agentic AI systems typically start with a foundational generative AI model and are tailored for specific applications, equipped with tools necessary for their tasks. For instance, a digital agent might have access to a calculator or database to handle its assigned functions. However, developing such systems poses challenges due to insufficient training data, especially for tasks like online flight booking, which require the agent to learn through trial and error.<\/p>\n<p>Promising applications of agentic AI include coding agents that have evolved from generative AI. These systems are trained on code and can solve coding problems by iterating different solutions, provided they can verify outcomes. However, full automation is not always advisable, particularly in high-stakes or safety-critical areas like medicine or security, where human oversight remains crucial.<\/p>\n<p>The widespread use of AI agents presents risks. For example, coding agents may lead to errors if users rely too heavily on them without proper verification, potentially introducing bugs or leaking private data. Furthermore, over-reliance on AI agents could result in a loss of skills, as people might become dependent on agents for tasks they previously handled themselves.<\/p>\n<p>Looking forward, the development of agentic AI may require new models that go beyond current language-based architectures, incorporating various data types like videos or radar scans. There&#8217;s ongoing debate about whether future AI will simply enhance existing models like Claude with added capabilities, or whether fundamentally new architectures will emerge to handle more complex interactions with the world. The direction of this evolution is a key focus for AI researchers today.<\/p>\n<hr>\n<p>\n<strong>Source:<\/strong> MIT News<br \/>\n<strong>Read Original:<\/strong><br \/>\n<a href=\"https:\/\/news.mit.edu\/2026\/agentic-ai-and-what-do-we-want-it-be-0630\" target=\"_blank\" rel=\"noopener\">https:\/\/news.mit.edu\/2026\/agentic-ai-and-what-do-we-want-it-be-0630 <\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p><span class=\"span-reading-time rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\"> 2<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span>Computer scientist Phillip Isola cuts through the hype to explain how AI agents work and what the future might hold for this rapidly advancing technology.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"footnotes":""},"categories":[226],"tags":[484,826,572],"class_list":["post-34745","post","type-post","status-publish","format-standard","hentry","category-ai-digest","tag-ai-in-education","tag-smart-and-modern-learning","tag-stem-education"],"acf":[],"_links":{"self":[{"href":"https:\/\/kapdec.com\/blog\/wp-json\/wp\/v2\/posts\/34745","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/kapdec.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/kapdec.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/kapdec.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/kapdec.com\/blog\/wp-json\/wp\/v2\/comments?post=34745"}],"version-history":[{"count":1,"href":"https:\/\/kapdec.com\/blog\/wp-json\/wp\/v2\/posts\/34745\/revisions"}],"predecessor-version":[{"id":34997,"href":"https:\/\/kapdec.com\/blog\/wp-json\/wp\/v2\/posts\/34745\/revisions\/34997"}],"wp:attachment":[{"href":"https:\/\/kapdec.com\/blog\/wp-json\/wp\/v2\/media?parent=34745"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/kapdec.com\/blog\/wp-json\/wp\/v2\/categories?post=34745"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/kapdec.com\/blog\/wp-json\/wp\/v2\/tags?post=34745"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}