{"id":84994,"date":"2025-08-13T18:08:16","date_gmt":"2025-08-13T12:38:16","guid":{"rendered":"https:\/\/www.guvi.in\/blog\/?p=84994"},"modified":"2025-08-29T08:28:46","modified_gmt":"2025-08-29T02:58:46","slug":"key-limitations-of-artificial-intelligence","status":"publish","type":"post","link":"https:\/\/www.guvi.in\/blog\/key-limitations-of-artificial-intelligence\/","title":{"rendered":"Understanding the 9 Key Limitations of Artificial Intelligence"},"content":{"rendered":"\n<p>We often hear how artificial intelligence is changing the world, automating tasks, driving innovation, and even outperforming humans in certain areas. But here\u2019s the real question: <strong>Is AI truly limitless, or are there boundaries it just can\u2019t cross?<\/strong>&nbsp;<\/p>\n\n\n\n<p>If you\u2019ve ever wondered why AI stumbles with basic logic or why it needs enormous data to function, you\u2019re not alone. Understanding where AI falls short is just as important as knowing what it can do, especially if you&#8217;re planning to build, use, or rely on it.<\/p>\n\n\n\n<p>That\u2019s why in this article, to ease your AI learning process, we compiled a list of well-known and some unknown limitations of artificial intelligence. These help you in understanding where one might go wrong when using AI. So, without further ado, let us get started!<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>What is Artificial Intelligence?<\/strong><\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1200\" height=\"636\" src=\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/What-is-Artificial-Intelligence_-1200x636.png\" alt=\"Artificial Intelligence\" class=\"wp-image-85823\" srcset=\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/What-is-Artificial-Intelligence_-1200x636.png 1200w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/What-is-Artificial-Intelligence_-300x159.png 300w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/What-is-Artificial-Intelligence_-768x407.png 768w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/What-is-Artificial-Intelligence_-1536x814.png 1536w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/What-is-Artificial-Intelligence_-2048x1085.png 2048w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/What-is-Artificial-Intelligence_-150x80.png 150w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" title=\"\"><\/figure>\n\n\n\n<p>Before diving into its flaws, let\u2019s quickly recap what AI is. At its core, <a href=\"https:\/\/www.guvi.in\/blog\/what-is-artificial-intelligence\/\" target=\"_blank\" rel=\"noreferrer noopener\">artificial intelligence<\/a> refers to machines or systems that mimic human intelligence, learning from data, recognizing patterns, making decisions, and improving over time.<\/p>\n\n\n\n<p>From voice assistants like Alexa and Siri to recommendation engines on Netflix, AI is embedded into many parts of our lives. But here\u2019s the thing, it\u2019s still not <em>truly<\/em> intelligent in the human sense.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Why Knowing AI\u2019s Limits Matters<\/strong><\/h2>\n\n\n\n<p>You can\u2019t use a tool effectively unless you know where it breaks. This is especially true with AI. If you&#8217;re building, using, or even just interacting with<a href=\"https:\/\/www.guvi.in\/blog\/ai-tools-for-developers\/\" target=\"_blank\" rel=\"noreferrer noopener\"> AI-powered tools<\/a>, knowing their limitations will help you:<\/p>\n\n\n\n<ul>\n<li>Avoid over-reliance<br><\/li>\n\n\n\n<li>Set realistic expectations<br><\/li>\n\n\n\n<li>Prevent ethical and operational risks<br><\/li>\n\n\n\n<li>Design better systems<\/li>\n<\/ul>\n\n\n\n<p>Let\u2019s break down these limitations one by one.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>9 Key Limitations of Artificial Intelligence<\/strong><\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1200\" height=\"630\" src=\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/9-Key-Limitations-of-Artificial-Intelligence@2x-1200x630.png\" alt=\"9 Key Limitations of Artificial Intelligence\" class=\"wp-image-85825\" srcset=\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/9-Key-Limitations-of-Artificial-Intelligence@2x-1200x630.png 1200w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/9-Key-Limitations-of-Artificial-Intelligence@2x-300x158.png 300w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/9-Key-Limitations-of-Artificial-Intelligence@2x-768x403.png 768w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/9-Key-Limitations-of-Artificial-Intelligence@2x-1536x806.png 1536w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/9-Key-Limitations-of-Artificial-Intelligence@2x-2048x1075.png 2048w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/9-Key-Limitations-of-Artificial-Intelligence@2x-150x79.png 150w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" title=\"\"><\/figure>\n\n\n\n<p>Let\u2019s break this down in detail. While AI can solve complex problems and automate routine tasks, it still struggles with a range of fundamental issues. These limitations stem from how AI is trained, what it\u2019s trained on, and how it&#8217;s deployed in the real world.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>1. Lack of Common Sense<\/strong><\/h3>\n\n\n\n<p>AI doesn\u2019t truly understand the world; it identifies patterns but lacks real-world reasoning. Unlike humans, who use intuition and lived experience, AI can\u2019t make sense of simple absurdities or obvious contradictions.<\/p>\n\n\n\n<p><strong>Example:<\/strong><strong><br><\/strong>If you ask an AI, \u201cCan I put my phone in the microwave to charge it?\u201d, a human will immediately say no, but an AI might give a dangerously neutral answer if it hasn&#8217;t seen enough similar examples during training.<\/p>\n\n\n\n<p><strong>Why This Matters:<\/strong><strong><br><\/strong>In mission-critical systems like legal advisors, healthcare assistants, or emergency bots, this lack of grounding in reality can lead to embarrassing or even dangerous results.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2. Data Dependency<\/strong><\/h3>\n\n\n\n<p>AI doesn\u2019t learn like humans do. It needs large, structured, and labeled datasets. If those datasets are incomplete, biased, or outdated, the AI will reflect those same flaws.<\/p>\n\n\n\n<p><strong>Example:<\/strong><strong><br><\/strong>An AI model trained to analyze hiring decisions might learn that certain demographics are less likely to be hired if that was the historical pattern, even if it\u2019s illegal or unethical.<\/p>\n\n\n\n<p><strong>Why This Matters:<\/strong><strong><br><\/strong>Bad data leads to bad predictions. AI trained on flawed data can reinforce existing biases in hiring, loan approvals, medical diagnostics, and even policing.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>3. Limited Generalization<\/strong><\/h3>\n\n\n\n<p>AI systems usually perform well in the specific task they were trained for, but they can&#8217;t generalize across different domains.<\/p>\n\n\n\n<p><strong>Example:<\/strong><strong><br><\/strong>A model trained to identify cats in images won\u2019t understand a photo of a lion unless it\u2019s explicitly taught that lions are also part of the feline family.<\/p>\n\n\n\n<p><strong>Why This Matters:<\/strong><strong><br><\/strong>AI can\u2019t \u201cthink outside the box.\u201d That\u2019s a major roadblock for building flexible, multi-purpose systems, something humans do naturally.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>4. High Resource Requirements<\/strong><\/h3>\n\n\n\n<p>AI models, especially deep learning ones, demand serious computing power, electricity, memory, and time.<\/p>\n\n\n\n<p><strong>Example:<\/strong><strong><br><\/strong>Training GPT-3 took thousands of petaflop\/s-days of computation and a multimillion-dollar budget, not something your college lab can replicate overnight.<\/p>\n\n\n\n<p><strong>Why This Matters:<\/strong><strong><br><\/strong>AI development is often limited to tech giants or well-funded institutions. This creates an uneven playing field and slows down innovation in smaller ecosystems.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>5. Explainability Issues (Black Box Problem)<\/strong><\/h3>\n\n\n\n<p>Many AI models, especially neural networks, are so complex that even their developers can\u2019t fully explain how they arrived at a decision.<\/p>\n\n\n\n<p><strong>Example:<\/strong><strong><br><\/strong>An AI might reject a home loan application, but when asked why, the system can\u2019t provide a clear or logical reason, just a probability score.<\/p>\n\n\n\n<p><strong>Why This Matters:<br><\/strong>In regulated industries, a lack of transparency can lead to non-compliance, lawsuits, and a total breakdown of user trust.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>6. Vulnerability to Attacks<\/strong><\/h3>\n\n\n\n<p>AI systems are fragile. Slight changes in input, called adversarial attacks, can confuse them completely.<\/p>\n\n\n\n<p><strong>Example:<\/strong><strong><br><\/strong>By changing just a few pixels in an image, researchers have tricked AI models into thinking a turtle is a rifle.<\/p>\n\n\n\n<p><strong>Why This Matters:<\/strong><strong><br><\/strong>This is dangerous in autonomous vehicles, military systems, or medical diagnostics, where mistakes can cost lives.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>7. No Emotional Intelligence<\/strong><\/h3>\n\n\n\n<p>AI might understand words like \u201chappy\u201d or \u201canxious,\u201d but it doesn\u2019t <em>feel<\/em> anything. It can\u2019t empathize, offer moral guidance, or understand subtle social dynamics.<\/p>\n\n\n\n<p><strong>Example:<\/strong><strong><br><\/strong>A mental health chatbot might fail to detect suicidal ideation in a user\u2019s tone and offer a generic \u201cHave a nice day\u201d response.<\/p>\n\n\n\n<p><strong>Why This Matters:<br><\/strong>For roles requiring emotional nuance, counseling, teaching, and negotiation, AI just doesn\u2019t cut it.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>8. Legal and Ethical Challenges<\/strong><\/h3>\n\n\n\n<p>The law is still catching up with AI. Questions like &#8220;Who\u2019s liable when AI fails?&#8221; remain largely unanswered.<\/p>\n\n\n\n<p><strong>Example:<\/strong><strong><br><\/strong>If an autonomous delivery drone crashes and injures someone, it&#8217;s unclear whether the blame lies with the software developer, hardware manufacturer, or operator.<\/p>\n\n\n\n<p><strong>Why This Matters:<\/strong><strong><br><\/strong>This legal ambiguity creates risk for businesses and makes regulators hesitant to approve AI deployments in critical sectors.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>9. Job Displacement (Not Full Replacement)<\/strong><\/h3>\n\n\n\n<p>AI doesn&#8217;t take jobs; it takes <em>tasks.<\/em> But that still impacts livelihoods, especially for people in roles that rely on routine or predictable workflows.<\/p>\n\n\n\n<p><strong>Example:<\/strong><strong><br><\/strong>AI tools now handle basic customer support, invoice processing, and even some coding tasks.<\/p>\n\n\n\n<p><strong>Why This Matters:<br><\/strong>Without proper reskilling programs, workers can find themselves pushed out of the economy faster than they can adapt.<\/p>\n\n\n\n<div style=\"background-color: #099f4e; border: 3px solid #110053; border-radius: 12px; padding: 18px 22px; color: #FFFFFF; font-size: 18px; font-family: Montserrat, Helvetica, sans-serif; line-height: 1.6; box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15); max-width: 750px;\"><strong style=\"font-size: 22px; color: #FFFFFF;\">\ud83d\udca1 Did You Know?<\/strong> <br \/><br \/> In a 2023 study, over 70% of surveyed AI professionals admitted they couldn\u2019t fully explain how their deep learning models worked, highlighting the growing gap between performance and transparency.<\/div>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Real-World Use Cases Where AI Fails<\/strong><\/h2>\n\n\n\n<figure class=\"wp-block-image size-large\"><img decoding=\"async\" width=\"1200\" height=\"630\" src=\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/Real-World-Use-Cases-Where-AI-Fails@2x-1200x630.png\" alt=\"Real-World Use Cases Where AI Fails\" class=\"wp-image-85826\" srcset=\"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/Real-World-Use-Cases-Where-AI-Fails@2x-1200x630.png 1200w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/Real-World-Use-Cases-Where-AI-Fails@2x-300x158.png 300w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/Real-World-Use-Cases-Where-AI-Fails@2x-768x403.png 768w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/Real-World-Use-Cases-Where-AI-Fails@2x-1536x806.png 1536w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/Real-World-Use-Cases-Where-AI-Fails@2x-2048x1075.png 2048w, https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/Real-World-Use-Cases-Where-AI-Fails@2x-150x79.png 150w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" title=\"\"><\/figure>\n\n\n\n<p>Now that you\u2019ve seen the theoretical side, let\u2019s get into some real-world failures that highlight these limitations in action.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>1. IBM Watson in Healthcare<\/strong><\/h3>\n\n\n\n<p><strong>What happened:<\/strong><strong><br><\/strong>IBM\u2019s Watson was supposed to revolutionize cancer diagnosis and treatment recommendations. Instead, it gave \u201cunsafe and incorrect\u201d suggestions in several cases due to poor training data and flawed logic.<\/p>\n\n\n\n<p><strong>Limitation exposed:<\/strong><strong><br><\/strong>Lack of common sense, data dependency, and poor generalization.<\/p>\n\n\n\n<p><strong>Lesson:<\/strong><strong><br><\/strong>Even in a well-funded, data-rich environment like medicine, AI can&#8217;t replace expert human judgment.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>2. Amazon\u2019s Hiring AI<\/strong><\/h3>\n\n\n\n<p><strong>What happened:<\/strong><strong><br><\/strong>Amazon built an AI tool to screen resumes but had to scrap it after discovering it penalized female applicants.<\/p>\n\n\n\n<p><strong>Limitation exposed:<\/strong><strong><br><\/strong>Bias in training data and lack of explainability.<\/p>\n\n\n\n<p><strong>Lesson:<\/strong><strong><br><\/strong>AI learns from past patterns. If those patterns are biased, the AI will carry them forward, sometimes invisibly.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>3. Tesla Autopilot Failures<\/strong><\/h3>\n\n\n\n<p><strong>What happened:<\/strong><strong><br><\/strong>Tesla\u2019s self-driving system has been involved in several fatal crashes. In one instance, it failed to recognize a white truck against a bright sky.<\/p>\n\n\n\n<p><strong>Limitation exposed:<\/strong><strong><br><\/strong>Inability to handle edge cases and vulnerability to unexpected input.<\/p>\n\n\n\n<p><strong>Lesson:<\/strong><strong><br><\/strong>Even advanced computer vision systems can fail in real-world environments with poor lighting or uncommon scenarios.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>4. Google Photos Tagging Error<\/strong><\/h3>\n\n\n\n<p><strong>What happened:<\/strong><strong><br><\/strong>Google\u2019s AI once labeled images of Black individuals as \u201cgorillas.\u201d The company had to disable the feature after public backlash.<\/p>\n\n\n\n<p><strong>Limitation exposed:<br><\/strong>Severe bias and a lack of context understanding.<\/p>\n\n\n\n<p><strong>Lesson:<\/strong><strong><br><\/strong>AI doesn&#8217;t understand race, culture, or human dignity. It&#8217;s up to developers to test thoroughly and design responsibly.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\"><strong>5. Chatbot Meltdowns (e.g., Microsoft Tay)<\/strong><\/h3>\n\n\n\n<p><strong>What happened:<br><\/strong><a href=\"https:\/\/www.bbc.com\/news\/technology-35902104\" target=\"_blank\" rel=\"noreferrer noopener nofollow\">Microsoft\u2019s chatbot Tay<\/a> learned from Twitter users and turned into a racist, offensive bot within hours.<\/p>\n\n\n\n<p><strong>Limitation exposed:<\/strong><strong><br><\/strong>Blind pattern imitation and lack of ethical safeguards.<\/p>\n\n\n\n<p><strong>Lesson:<\/strong><strong><br><\/strong>Without guardrails, AI will mirror the worst of the internet, and fast.<\/p>\n\n\n\n<p>These failures aren\u2019t outliers. They are signs that AI, while powerful, still needs human oversight, context, and conscience.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Quick Challenge \u2013 Can You Spot the Limitation?<\/strong><\/h2>\n\n\n\n<p>Here\u2019s a quick scenario for you:<\/p>\n\n\n\n<p>An AI is trained to detect spam emails. It has 99% accuracy in tests. But when deployed in the real world, it starts marking client emails as spam.<\/p>\n\n\n\n<p>What limitation is being exposed here?<\/p>\n\n\n\n<p>A) Emotional Intelligence<br>B) Data Bias or Overfitting<br>C) Lack of Legal Framework<br>D) Energy Consumption<\/p>\n\n\n\n<p><strong>Answer: B \u2013 Data Bias or Overfitting.<br><\/strong>The AI was likely trained on a dataset that didn&#8217;t reflect real-world variation, leading it to misclassify legitimate emails.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Where We Go From Here?<\/strong><\/h2>\n\n\n\n<p>Understanding AI\u2019s limitations doesn\u2019t mean we stop using it. Instead, it means we use it wisely. Here\u2019s what you can do as a student or early professional:<\/p>\n\n\n\n<ul>\n<li><strong>Stay curious<\/strong>: Learn not just how to build AI, but how to evaluate and question it.<br><\/li>\n\n\n\n<li><strong>Think ethically<\/strong>: Ask who might be affected when AI fails.<br><\/li>\n\n\n\n<li><strong>Upskill constantly<\/strong>: The best way to future-proof yourself is to blend technical know-how with problem-solving and people skills.<br><\/li>\n<\/ul>\n\n\n\n<p>If you\u2019re serious about mastering artificial intelligence and want to apply it in real-world scenarios, don\u2019t miss the chance to enroll in HCL GUVI\u2019s Intel &amp; IITM Pravartak Certified<a href=\"https:\/\/www.guvi.in\/mlp\/artificial-intelligence-and-machine-learning\/?utm_source=blog&amp;utm_medium=hyperlink&amp;utm_campaign=limitations-of-artificial-intelligence\" target=\"_blank\" rel=\"noreferrer noopener\"> Artificial Intelligence &amp; Machine Learning course<\/a>. Endorsed with Intel certification, this course adds a globally recognized credential to your resume, a powerful edge that sets you apart in the competitive AI job market.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Conclusion<\/strong><\/h2>\n\n\n\n<p>In conclusion, artificial Intelligence is a game-changing tool, but it\u2019s not a magic wand. Its limitations aren\u2019t just technical quirks; they\u2019re deeply tied to how we train, deploy, and interact with these systems.&nbsp;<\/p>\n\n\n\n<p>As a student stepping into the tech world, your edge lies not in blindly adopting AI, but in knowing when to trust it, when to question it, and when to step in with good old human judgment. The future of AI isn\u2019t just about smarter machines; it\u2019s about smarter humans designing them.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>FAQs&nbsp;<\/strong><\/h2>\n\n\n<div id=\"rank-math-faq\" class=\"rank-math-block\">\n<div class=\"rank-math-list \">\n<div id=\"faq-question-1755087386155\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>1. Why can\u2019t AI understand emotions like humans?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>AI can detect emotion based on text or facial expressions, but it doesn\u2019t feel or understand them. It lacks consciousness and emotional context.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1755087389369\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>2. Is AI dangerous if it becomes too powerful?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>AI itself isn&#8217;t inherently dangerous, but misuse or over-reliance without safeguards can lead to risks, especially in defense, finance, or healthcare.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1755087393765\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>3. Can AI ever have common sense?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Researchers are working on it, but current models are still far from achieving human-level common sense reasoning.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1755087397977\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>4. Why is AI often biased?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>Because AI learns from historical data, any existing bias in the data gets replicated or amplified in the model unless corrected.<\/p>\n\n<\/div>\n<\/div>\n<div id=\"faq-question-1755087406890\" class=\"rank-math-list-item\">\n<h3 class=\"rank-math-question \"><strong>5. What\u2019s the biggest barrier to using AI in real life?<\/strong><\/h3>\n<div class=\"rank-math-answer \">\n\n<p>It\u2019s a mix of data quality, lack of explainability, ethical concerns, and high resource requirements that make large-scale adoption difficult.<\/p>\n\n<\/div>\n<\/div>\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>We often hear how artificial intelligence is changing the world, automating tasks, driving innovation, and even outperforming humans in certain areas. But here\u2019s the real question: Is AI truly limitless, or are there boundaries it just can\u2019t cross?&nbsp; If you\u2019ve ever wondered why AI stumbles with basic logic or why it needs enormous data to [&hellip;]<\/p>\n","protected":false},"author":22,"featured_media":85822,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[933],"tags":[],"views":"3247","authorinfo":{"name":"Lukesh S","url":"https:\/\/www.guvi.in\/blog\/author\/lukesh\/"},"thumbnailURL":"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/Understanding-the-9-Key-Limitations-of-Artificial-Intelligence-300x116.png","jetpack_featured_media_url":"https:\/\/www.guvi.in\/blog\/wp-content\/uploads\/2025\/08\/Understanding-the-9-Key-Limitations-of-Artificial-Intelligence.png","_links":{"self":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts\/84994"}],"collection":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/users\/22"}],"replies":[{"embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/comments?post=84994"}],"version-history":[{"count":7,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts\/84994\/revisions"}],"predecessor-version":[{"id":85827,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/posts\/84994\/revisions\/85827"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/media\/85822"}],"wp:attachment":[{"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/media?parent=84994"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/categories?post=84994"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.guvi.in\/blog\/wp-json\/wp\/v2\/tags?post=84994"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}