University of Kwazulu-Natal

Agentic Ai Examples And Use Cases In Real World 2025

Bonisiwe Shabane
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agentic ai examples and use cases in real world 2025

From cybersecurity to supply chain management, agentic AI can help businesses automate complex, multistep tasks in real time. The term agentic AI, or AI agents, refers to AI systems capable of independent decision-making and autonomous behavior. These systems can reason, plan and perform actions, adapting in real time to achieve specific goals. Unlike traditional automation tools that follow predetermined pathways, agentic AI doesn't rely on a fixed set of instructions. Instead, it uses learned patterns and relationships to determine the best approach to achieving an objective. To do this, agentic AI breaks down a larger main objective into smaller subtasks, said Thadeous Goodwyn, director of generative AI at Booz Allen Hamilton.

These subtasks are then delegated to more specialized AI models, often using more traditional, narrow AI models for specific actions. The decisions and actions of these component AI systems ultimately enable the AI agent to achieve its primary objective. And this capability is quickly maturing, according to Goodwyn. As we advance through 2025, the artificial intelligence landscape has evolved far beyond the generative AI boom of 2023-2024. The current focus has shifted to agentic AI, the kindof autonomous systems that don’tjust generate content or provide responses, but actively pursue goals, make decisions, and execute complex workflows without human intervention. According to recent industry reports, the agentic AImarket is projected to reach $78.2 billionby 2030, with enterprise adoption accelerating at an unprecedented 127% year-over-year growth rate in 2025.

Several converging factors have accelerated agentic AI adoption in 2025: Agentic AI systems in 2025 possess four critical capabilities that distinguish them from previous generations of AI: These characteristics enable agentic AI to function as autonomous business units rather than mere tools, capable of handling sophisticated business processes that previously required human expertise and judgment. In 2025, successful implementations demonstrate that these systems can achieve 90%+ accuracy in decision-making tasks while operating continuously without fatigue or bias. Financial markets generate over $6 trillion in daily trading volume, creating opportunities that exist for microseconds. Agentic AI trading systems now execute complex multi-asset strategies, automatically adjusting positions based on real-time market sentiment, geopolitical events, and technical indicators.

Agentic AI isn’t some far-off future. In fact, it’s already powering real results. From Nike solving bad sizing with smart fit tools to Mastercard stopping fraud mid-swipe, brands are using AI agents that do the work, not just suggest it. These systems are now tracking, adapting, following up, and fixing things on their own. Bottom line? If there's a repetitive task or bottleneck slowing your team down, there's probably an AI agent that can take it off your plate.

For good. Agentic AI completely changes how humans work with machines. These aren’t just regular chatbots; they are more like digital employees with powerful software minds. Agentic AI understands texts, images, and even sounds, and can plan and execute an entire project on its own. They understand text, images, and even audio, and they adapt in real time. Take this: You’re prepping for a work trip.

Normally, you’d have to book flights, schedule meetings, block your calendar, manage emails, and update your team. Now imagine all of that handled without you lifting a finger. Register today and get 10% off on all courses Master the power of Artificial Intelligence with industry-recognized certifications. Advance your career with cutting-edge skills and real-world applications. SAFe Courses provide structured learning paths for individuals and teams adopting the Scaled Agile Framework (SAFe).

These certifications enable professionals to implement Agile practices at scale, fostering collaboration, delivering value efficiently, and driving organizational agility. Technology courses cover a wide range of subjects aimed at developing technical skills, from programming and software development to data science, cybersecurity, and cloud computing. These courses provide foundational knowledge and hands-on experience to help individuals excel in tech-driven careers. Microsoft offers a variety of online courses focusing on Microsoft 365, Azure, AI, data analysis, development, and productivity tools. These courses include self-paced modules, instructor-led sessions, and certification programs designed to build skills in areas such as Microsoft 365 apps, Power BI, Excel, AI & ML engineering, and full-stack development. Agentic AI marks a shift from simpler prompt-response systems to active autonomous collaborators.

These systems can reason over multiple steps, plan actions, call external tools or APIs, and adapt based on feedback. They can handle complex, multi-step tasks with minimal human input. Top companies across various industries are already deploying agentic AI for real impact. Financial institutions use AI agents to automate transaction analysis and compliance checks, e-commerce companies employ them for dynamic recommendations, and engineering teams rely on multi-agent systems for code review and test generation. In this blog, we will explore seven agentic AI examples and use cases in the real world. Delivery Hero built QueryAnswerBird (QAB), an AI-powered data analyst assistant, to enable employees to query, visualize, and discover business data without code.

The solution consists of two components: Here’s how it works: a user asks a question in Slack, QAB retrieves relevant internal data definitions and examples via vector search, crafts a compliant SQL query tailored to business logic, validates it, and... Mercury is eBay’s internal agentic AI platform. It powers LLM-driven recommendation experiences on the marketplace and lets teams efficiently build and scale autonomous, goal-oriented AI workflows: Autonomous generative AI agents execute complex tasks with little or no human supervision. Agentic AI differs from chatbots and co-pilots.

Unlike traditional AI, particularly generative AI, which often requires human intervention in complex workflows, agentic AI aims to autonomously navigate and optimize processes thanks to its decision-making capabilities and goal-directed behavior. AI agents serve as: AI code editors like Cursor AI Editor, Windsurf Editor, and Replit aims to build and deploy apps (e.g. To-Do list app) by: A developer used OpenAI’s Operator and Replit’s AI Agent to build an entire app in 90 minutes. Two agents autonomously exchanged credentials, and ran tests.

Cursor’s agent mode Composer aims to generate a complete Tic Tac Toe game from a single prompt:“Generate an HTML, CSS, and JavaScript Tic Tac Toe game for 2 players.” Artificial Intelligence has entered a new era with the rise of agentic AI—systems that don’t just respond but act autonomously to achieve specific goals. Unlike traditional AI models, which rely on direct prompts, agentic AI agents can reason, plan, and execute tasks across digital environments. This shift is creating significant opportunities across industries, from healthcare and finance to retail and manufacturing. Let’s explore the most impactful agentic AI use cases and how they’re changing industries in real-world applications. One of the most promising agentic AI use cases is in healthcare.

AI agents can analyze patient data, cross-reference symptoms with global medical research, and suggest preliminary diagnoses. Beyond diagnosis, agents act as continuous patient companions—tracking vital signs, reminding patients to take medication, and alerting doctors when anomalies appear. For hospitals, agentic AI reduces administrative burdens by automating scheduling, insurance claims, and follow-up communications. Real-world example: AI agents are being used in telemedicine platforms to provide round-the-clock virtual triage, ensuring patients receive timely attention without overwhelming human staff. In finance, milliseconds can mean millions. Agentic AI enables financial institutions to deploy autonomous agents that analyze markets, execute trades, and adjust portfolios based on live data.

These agents are not only faster but can adapt to new conditions without constant human intervention. Fraud detection is another transformative area. Agentic AI agents continuously monitor transactions, spot unusual activity, and trigger automatic responses—freezing accounts or flagging risks—far quicker than traditional systems. You’ve heard the AI buzz a thousand times. Productivity, efficiency, automation—it all sounds exciting. But look closer, and the numbers tell an interesting story.

“According to PwC, only 66% companies have adopted agentic AI, and reported higher productivity; that still means a third of them haven’t cracked the code. This is why real-world examples of Agentic AI matter. They show us what’s working, where the impact is visible, and how businesses are moving from hype to measurable results. Across industries, these examples aren’t just case studies—they’re blueprints. From supply chain and logistics optimization to hyper-personalized customer journeys, we have agentic AI examples in action, demonstrating how organizations are leveraging AI to act, decide, and deliver at scale. If you’re looking to see how the world is putting agentic AI to work, let’s explore the stories that are shaping the future.

Agentic AI is actively changing how organizations solve problems, make decisions, and deliver results. Curious how this looks in practice? Here are some compelling examples of Agentic AI across industries. Artificial Intelligence is no longer a futuristic concept – it’s embedded in the way we search, shop, communicate, and work. At the core of this transformation are AI agents: software-powered systems capable of perceiving their environment, making decisions, and taking action. These autonomous AI systems-sometimes called intelligent software agents-are transforming industries with real-world use cases in 2025.

Whether they are scheduling appointments, guiding a customer through troubleshooting, or predicting market trends, AI agents are designed to handle tasks traditionally requiring human judgment and effort. Their versatility makes them a valuable tool for both individuals and organizations, and their adoption is growing at a rapid pace. In this guide, we’ll explore more than 20 real-world AI agent examples across consumer, business, and industry-specific contexts. Along the way, we’ll look at how they work, why they matter, and where the technology is headed next. An AI agent is more than just an app or a chatbot. It’s a digital entity that can sense, think, and act – often without ongoing human supervision.

Unlike static programs, AI agents are adaptive and capable of learning from new information. Most AI agents operate using three key capabilities:

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