The API Avalanche: AI Agents Reshape Digital Consumption

Just over a year ago, we saw in Sensedia's API Trends 2024 report that artificial intelligence would drive a new wave in API consumption. “There is no AI without APIs,” said Paolo Malinverno, our head of innovation, at the time. Today, that statement is no longer a prediction, it is a proven fact. 

According to Postman's State of APIs 2024 report, AI-driven API traffic increased by 73% in just 12 months. This is not a growth curve, it is an avalanche. What we are seeing now is the emergence of a new type of digital consumer: AI agents, machines that interact with systems, make decisions, learn, and do so on a scale impossible for any human team. 

The Silent Transformation 

We don´t hear too much said about this outside technical circles, but we should pay attention: artificial intelligence is changing the very nature of APIs. Until a few years ago, APIs were mainly used by developers and human systems. Today, that role has largely been taken over by autonomous software. 

A recent report by Cloudera on the future of enterprise AI agents, cited by Nordic APIs, notes that 96% of IT leaders plan to expand the use of these agents in the next 12 months. This is not science fiction, it is corporate strategy. Companies across all sectors are beginning to delegate critical tasks to automated agents, from financial analysis to customer support to complex purchasing. 

What are these agents and why should we talk about them? 

According to AWS, an AI agent is an autonomous system that acts on behalf of a user to achieve a goal. They perceive, reason, plan, execute tasks, and do so by interacting, of course, through APIs. They can be financial assistants that move investments, support bots that manage tickets, or purchasing systems that negotiate with suppliers. 

And here's the key point: for an AI agent to work, it must be connected. And that connection happens, time and time again, through APIs. APIs are no longer just integration tools; they are the backbone of an increasingly automated economy. 

APIs

What used to be predictable is now a chaotic ecosystem. AI agents don't sleep, don't rest, and don't make mistakes in their schedules. They operate 24/7, generating thousands of API calls per second. This is no exaggeration: a single agent can make more requests in an hour than a human can in a whole week. 

This is breaking paradigms. The old logic of “rate limits” — those restrictions designed to prevent abuse — is becoming obsolete. Not because they are no longer necessary, but because they were designed with people in mind, not machines. 

Furthermore, the identity of these agents is difficult to trace. Who is making the request? For what purpose? What model is behind it? Without real visibility, without context, it is impossible to manage the risks involved. 

To Govern or Be Governed? 

This is where many organizations are failing. They still operate with governance models designed for a human world, where API calls are specific, predictable, and traceable. That world no longer exists. 

The new reality requires intelligent governance, capable of observing, understanding, and regulating the behavior of autonomous systems. Technologies such as MCP (Model Context Propagation) allow each API request to be tagged with critical information: which model generated it, in what context, and for what purpose. This not only provides transparency, but also allows for timely action, prevents abuse, and — above all — reduces risks. 

Because AI doesn't just consume data, it also generates costs. And if not managed well, those costs can spiral out of control. 

What about security and compliance? 

The answer is complex. Today's businesses operate as decentralized ecosystems, with multiple tools, partners, suppliers, clouds, and regions. It is naive to think that a single security policy can protect this entire network. 

What is needed is federated governance: local rules, adaptable to the context, but with centralized visibility, especially when we talk about AI agents that access external APIs, handle sensitive data, or interact with customers. It is not enough to close the door. You need to know who is coming in, why they are coming in, and what they are doing while they are inside. 

Govern to Innovate, Not to Slow Down 

One of the most common mistakes is to think that governing means putting the brakes on. On the contrary: good governance is the only way to move forward with confidence. A good API strategy not only protects, it also enables. 

The monetization of AI-generated API traffic, for example, opens up new business opportunities. But it requires governance tools that allow differentiation between types of use, service levels, and consumption patterns. Not all traffic is the same, and not all agents deserve the same treatment. 

That is why we propose adaptive limitation models, which adjust the flow of calls according to the agent's behavior, its AI model, and its level of trust. This allows the infrastructure to be protected without blocking innovation. 

Sensedia's New Role 

At Sensedia, we are convinced that API governance will be the decisive factor in the maturity of enterprise artificial intelligence. That is why we have developed a solution with native governance for AI, support for MCP, compatibility with multigateway environments, and centralized but agile policies.