AI Agents: the next big phase of artificial intelligence
The challenges and opportunities of scaling AI agents for large-scale automation

Artificial intelligence (AI) has entered a new phase of its evolution – one where models do not just reason but also act. Welcome to the age of AI agents: where systems can independently execute complex tasks, collaborate with other agents, and operate autonomously at scale.
This shift is poised to unlock transformative gains in productivity and efficiency across every industry.
SVP, AI Developer Platforms and Services, Arm.
From models to agents
Traditionally, AI interactions have centered around a single, often large, model designed to perform a variety of tasks. However, with AI agents, this is changing. Instead of relying on one massive model to handle everything from start to finish, AI agents break down tasks into smaller, specialized components, each handled by different agents. Compare this to moving from a single craftsman to an intelligent network of specialist workers, making AI more specialized and efficient.
For example, today, if someone asked an AI to design a new computer chip, the task would be processed end-to-end by one model. In the world of AI agents, that same request would be divided among a network of agents – each responsible for specific aspects like layout, simulation, and optimization – working together to deliver the result faster and more intelligently.
Business transformation
Beyond responding to specific requests and tasks, the impact of AI agents will be transformative. They are set to drive large-scale automation, bringing greater adaptability, intelligence and autonomy to processes that were previously manual or considered to be inefficient.
At the same time, AI agents are set to reshape workplace operations and practices, by enhancing how repetitive tasks like document management, customer support, and workflow orchestration are handled.
The pivot towards AI agents is also set to influence AI investment strategies. The Arm AI Readiness Index report reveals that 80 percent of organizations surveyed have an AI budget, with 87 percent expecting it to grow. Businesses are increasingly prioritizing AI tools and platforms that support modular, scalable agent ecosystems.
Impact across industries and markets
The impact of AI agents will be widespread and cross-industry. Sectors like finance, insurance, healthcare, retail, logistics, and creative services are already exploring a variety of use cases where AI agents can be adopted, ranging from fraud detection to automated underwriting, and even content creation. The potential is staggering.
Moreover, AI agents will not be confined to one environment, with workloads covering a wide range of systems. In mobile, imagine saying “book me a flight" or "sort my photos," and having a local network of AI agents coordinate these requests seamlessly. AI-first wearables may soon allow us to blend the physical and virtual worlds by using agentic AI to reason, predict, assist, and adapt.
For example, you may glance at a flower, asking “what flower am I looking at?” — and your smart glasses will instantly identify it, offering care tips or fun facts. Even virtual assistants in the home could use AI agents to control devices and complete everyday household tasks more efficiently.
On a larger scale, future autonomous vehicles could deploy multiple AI agents to handle various workloads, like navigation, object detection, real-time decision-making, and passenger interactions. Meanwhile, in cloud or enterprise settings, AI agents will power next-generation customer service and decision-making systems for improved responses.
Smaller models will make a big difference
A key enabler of AI agents is the rise of smaller AI models. These are easier to customize for specific tasks, more power-efficient to run, and faster to deploy across distributed systems. By using a collection of smaller models rather than one giant model, businesses can optimize both the performance and power-efficiency that are critical for everything from mobile devices to datacenters.
In fact, as explained in the Arm Silicon Reimagined report, many of these smaller models are already providing great results in terms of AI capabilities and performance, while running entirely on the device.
Wide scale transformation
AI agents represent more than just the next evolution of AI – they signal a fundamental shift in how work gets done, decisions are made, and value is created. Autonomous, task-driven systems powered by AI agents have the potential to enhance productivity, streamline operations, and enable entirely new customer experiences.
By moving beyond standalone AI models to networks of multiple specialized AI agents, organizations in any industry can unlock faster, smarter, and more cost-effective ways of operating across every function.
As AI agents become more capable, collaborative, and context-aware, they will redefine our expectations of technology – not simply as tools, but as proactive, intelligent collaborators. The organizations that embrace this shift early will not only boost efficiency, but also uncover new opportunities for innovation, differentiation, and growth in this new AI world.
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SVP, AI Developer Platforms and Services, Arm.
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