Author: Martin Kriener
Agent economy is an emerging economic paradigm in which autonomous AI agents capable of perception, reasoning, and action participate directly in markets as independent economic actors. Unlike traditional automation, which simply performs pre-programmed tasks, these agents make decisions based on goals, real-time data, and learned behaviors. You can engage in activities such as price negotiation, supply chain coordination, and creative production. These can represent individual consumers, businesses, or themselves and can interact with other agents and humans to buy, sell, collaborate, and innovate. The agent economy is driven by advances in large-scale language models, reinforcement learning, and distributed infrastructure, blurring the lines between human and machine agents.
In a practical sense, agents will be able to do “something” on behalf of consumers without direct user involvement. For example, an agent is given the task of finding the best travel deal or health insurance policy for a customer, and they do this with the full power of GenAI while monitoring what’s available in the market. But unlike the search engines of the past 20 years, these agents will be empowered to go further on behalf of their customers. They can make decisions, negotiate with other systems, offer customers the best possible deal, and close that deal. These agents are authorized by the customer to sign contracts and make payments on the customer’s behalf, effectively acting as if they were the customer. Give them a task and they will find a way to accomplish it. Not only that, they actively work on their tasks 24/7 and limit the fixed period of signed contracts to the absolute minimum so that they can continue to look for better deals. In the agentic economy, instead of committing to a one-year health insurance contract, it may be renegotiated by the agent on a weekly or daily basis.
For some, this is an exciting prospect of the true potential of life-changing AI; for others, it is a frightening prospect of a dystopian world. But like it or not, the first implementation of the agent is already here, and it’s not going away. Agents are already built using modern large-scale language models like OpenAI, Anthropic, and DeepSeek, technologies like MCP and A2A, and orchestration frameworks like LangChain and CrewAI. Hyperscalers around the world, including Google, Meta, Microsoft and Alibaba, are already investing heavily here because they see this as fundamentally disruptive, changing how the internet is used and who profits from it.
The transition to an agentic economy promises greater efficiency, personalization, and scalability, and will disrupt existing digital economy business models. Even a cursory look at the dynamics of agentic economies reveals that the disruption to innovation in every part of the value chain will be substantial. Of course, technological innovation is driving the emergence of agentics, but business model innovation and adaptation will need to be equally fundamental, as the models that have driven the current digital economy (digital advertising, platforms, etc.) are likely to be completely disrupted.
Business models that have defined the digital economy over the past 15 years include platform business models, search-based advertising, and the broader app economy. As I mentioned earlier, in an agentic economy, a consumer (or business) simply tells an agent, “Please book a trip to Kyoto next month.” We know your schedule, what your interests are, and your budget. We’ll ask you a simple series of questions for clarification, and then we’ll start considering your options. Search for flights and select what you want, including hotels, rental cars, and experiences. And make lots of reservations. There’s no need to download an app, and there’s no chance of seeing attractive digital ads. Additionally, we do not have any involvement with travel platforms, hotel booking platforms, or car rental platforms. Done! By bypassing reservation aggregation platforms and going directly to airline, rental car, and hotel websites, agents also avoid the additional “transaction taxes” imposed by those platforms, likely resulting in lower prices.
