AI Agents in Practice: Real-World Use Cases & Products Explored
“This is the most impactful change we’ve seen since the dawn of the internet,” an Amazon executive declared, describing the advent of AI agents during the launch of the company’s new Bedrock agentic framework. While the hype surrounding AI agents continues to accelerate, the more pressing question for many remains: what is truly happening in the real world?
Four months after the last significant update on AI agents in practice, the landscape has evolved rapidly. We’ve witnessed the emergence of dedicated agent products from major players like OpenAI, the development of sophisticated frameworks for product teams looking to build their own AI agents, and the launch of AI browsers capable of performing complex, agentic actions on behalf of users. Navigating this fast-paced evolution can be challenging, but a closer look reveals how these intelligent systems are being deployed internally at leading corporations, alongside new AI agent capabilities and products entering the market.
Companies are increasingly integrating AI agents into their core operations. Over twenty real-world examples highlight this trend, with internal use cases at giants such as Uber, McKinsey, Figma, and Walmart leading the charge. These internal deployments, often the most challenging to track, offer invaluable insights into how AI agents are transforming daily workflows. For instance, one notable company successfully deployed over 8,000 distinct AI agents for internal use, a testament to the potential for widespread adoption. However, such rapid expansion isn’t without its hurdles; another organization, after creating so many agents that employees struggled to keep track, had to temporarily pause its rollout—a challenge they subsequently addressed and resolved.
Beyond internal applications, the market is seeing a proliferation of new AI agent products and features. These innovations promise to streamline workflows and enhance productivity across various sectors. Simultaneously, the development of new agentic frameworks, such as Amazon Web Services’ offerings, empowers product teams to custom-build their own AI agents tailored to specific organizational needs. These frameworks provide the foundational tools necessary for companies to design, deploy, and manage their intelligent agents, marking a significant step towards democratizing AI agent development. The current landscape underscores a critical shift: AI agents are no longer just a futuristic concept but a tangible, evolving technology actively reshaping how businesses operate and innovate.