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<\/a><\/p>\nAI Agent Examples in Real Life<\/h2>\n1. Recommendation Engines<\/h3>\n
Every time you sift through recommendations on your Netflix, you\u2019re seeing AI agents at work.<\/p>\n
AI agents take action without constant human intervention by recognizing patterns and predicting behavior.<\/p>\n
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When Netflix is recommending you shows to watch, that rec list has been compiled by an AI agent tasked with analyzing your watch history and ratings for trends and genre preferences.<\/p>\n
Brands like Amazon, YouTube, and Spotify all use similar agents to personalize user experience.<\/p>\n
2. Dynamic Pricing Models<\/h3>\n
Hotels, ride-hailing apps, and airlines all have one thing in common: Surge pricing \u2013 powered by AI agents.<\/p>\n
These companies operate on a flexible pricing structure that fluctuates based on factors like supply, demand, and user trends.<\/p>\n
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Source<\/em><\/a><\/p>\n Take Lyft for instance. If I order a ride at 2 a.m. on a Saturday during Art Basel, it will surely cost me more than on a Tuesday night at 8 a.m. When the user even places the request for a ride, the AI agent evaluates these factors, sets the price, and responds to the user\u2019s request.<\/p>\n OpenAI and Google have both introduced AI agents, \u2013 Operator<\/a> and Mariner<\/a> respectively \u2013 that can search the web independently and serve as a true assistant, filling up shopping carts and getting answers to your most pressing questions.<\/p>\n \u201cIt can understand that it needs to press a button to make something happen,\u201d Demis Hassabis, who oversees Google\u2019s core A.I. lab, said in an interview with The NYT<\/a>. \u201cIt can take action in the world.\u201d<\/p>\n Source<\/a><\/p>\n While AI assistants escalate support requests and direct users toward self-service options, AI agents are working behind the scenes to:<\/p>\n Sites built on user-generated content \u2013 think Reddit, YouTube, Meta \u2013 require advanced content moderation practices to keep users safe.<\/p>\n Human moderators rely on AI agents to do some of the legwork of flagging, reviewing, and sorting content that goes against the site\u2019s policies.<\/p>\n Think about how good YouTube has gotten at flagging when a video includes copyrighted music. There\u2019s no human reviewing each upload \u2013 instead, Google relies on AI systems to analyze content as they\u2019re uploaded to the site and take actions if they\u2019re not compliant.<\/p>\n For instance, on YouTube, an uploaded video will be muted automatically if it includes copyrighted music. On TikTok, a content creator\u2019s video will be first muted, then removed for review. These steps allow moderation teams to focus on higher priority work and automate routine tasks.<\/p>\n When you\u2019re spending money on an ad, you\u2019re looking for return on investment (ROI). Doing so entails optimizing your ad after it\u2019s placed \u2013 that can mean anything from doubling down on the version that performs the best to customizing the ad based on user history.<\/p>\n While this can be done manually, it\u2019s not scalable \u2013 and that\u2019s where an AI agent comes in. Based on historical trends and performance data, advertisers can optimize their campaigns in real time, which saves them money and increases ROI.<\/p>\n Recruiters on LinkedIn can now automate routine tasks like finding and following up with candidates, and scheduling interviews.<\/p>\n Source<\/em><\/a><\/p>\n According to LinkedIn, recruiters report spending around 20 hours a week on these tasks, and these AI agents can cut that time by half \u2013 at least.<\/p>\n While I haven\u2019t had the chance to (read: the guts to) ride in a Waymo, Google\u2019s robotaxi, I can tell you a bit about how it works.<\/p>\n To operate safely, Waymo vehicles must rely on AI systems to perceive their surroundings, understand other drivers\u2019 behaviors, control the vehicle, and make safe driving decisions. It relies on real-time and historical data to guide and adapt its actions.<\/p>\n Tesla\u2019s AutoPilot feature is another example of an AI agent at work.<\/p>\n The stock market is unpredictable. Imagine if you had an AI agent tracking it during pre- and open market hours to recommend strategies?<\/p>\n Beyond recommendations, consumers and businesses alike are beginning to leverage AI agents to make trades based on their own risk profiles and investment strategies.<\/p>\n U.S. hospitals and healthcare orgs, like Mayo Clinic, are piloting the use of AI agents for a series of administrative tasks, including:<\/p>\n \u201cFor some years now, we\u2018ve collected mountains of data in EHRs and data lakes but struggled to translate those insights into meaningful impact. Too often, it\u2019s added more burden to clinicians instead of relieving it,” said the executive director for Atlantic Health System, an org overseeing over 550 medical care sites, to Becker\u2019s Health It<\/a>.<\/p>\n The next time you get a fraud alert notification from your bank, you\u2019ve likely got an AI agent to thank. (Or rather the team who configured it.)<\/p>\n In the banking space, AI agents monitor users\u2019 transaction activity and track spending habits. When they flag behaviors that fall outside of routine, they\u2019ll respond by freezing cards, alerting users, and requesting transaction approvals.<\/p>\n BMW is one of many companies using AI-powered robots to streamline production lines. They operate through a series of complex AI systems that assign them tasks and program them to adjust their behavior based on historical data.<\/p>\n Alongside humans, production lines function much more smoothly, allowing workers to focus on higher-impact tasks that require human oversight.<\/p>\n As you can now see, AI agents are working all around us. <\/p>\n AI agents are like the backstage crew at the concerts we attend: Operating independently on the backend to deliver a smooth experience on the user end. They power many of the tech we use \u2013 and have for a while \u2013 but haven\u2019t gotten that […]<\/p>\n","protected":false},"author":1,"featured_media":2286,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[10],"tags":[],"class_list":["post-2284","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-marketing"],"_links":{"self":[{"href":"http:\/\/nurseagence.com\/index.php\/wp-json\/wp\/v2\/posts\/2284","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/nurseagence.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/nurseagence.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/nurseagence.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/nurseagence.com\/index.php\/wp-json\/wp\/v2\/comments?post=2284"}],"version-history":[{"count":2,"href":"http:\/\/nurseagence.com\/index.php\/wp-json\/wp\/v2\/posts\/2284\/revisions"}],"predecessor-version":[{"id":2292,"href":"http:\/\/nurseagence.com\/index.php\/wp-json\/wp\/v2\/posts\/2284\/revisions\/2292"}],"wp:featuredmedia":[{"embeddable":true,"href":"http:\/\/nurseagence.com\/index.php\/wp-json\/wp\/v2\/media\/2286"}],"wp:attachment":[{"href":"http:\/\/nurseagence.com\/index.php\/wp-json\/wp\/v2\/media?parent=2284"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/nurseagence.com\/index.php\/wp-json\/wp\/v2\/categories?post=2284"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/nurseagence.com\/index.php\/wp-json\/wp\/v2\/tags?post=2284"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}3. Web Search<\/h3>\n
4. Customer Support<\/h3>\n
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5. Content Moderation<\/h3>\n
6. Ad Optimization<\/h3>\n
7. Recruiting Assistants<\/h3>\n
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<\/p>\n8. Autonomous Vehicles<\/h3>\n
9. Stock Trading Bots<\/h3>\n
10. Healthcare Admin<\/h3>\n
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11. Fraud Detection<\/h3>\n
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<\/p>\n12. Manufacturing Robots<\/h3>\n
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