For years, APIs have quietly connected the software that businesses depend on. They allow a banking application to retrieve an account balance, a mobile app to process a payment, or one internal system to send information to another without requiring developers to rebuild the underlying technology each time.
The rise of AI agents is giving those interfaces a much bigger job.
As businesses move from AI systems that generate answers to agents that can perform tasks, APIs are increasingly becoming the bridge between an AI model and the enterprise systems it needs to interact with. An agent might need to retrieve a customer record, check an account, create a support ticket or initiate a workflow, and APIs provide a structured way of accessing those capabilities.
That makes APIs an increasingly important part of the infrastructure behind enterprise AI, a theme that will feature prominently at WSO2Con Africa 2026, taking place September 22–24 at the JW Marriott Nairobi.
APIs were built for software. Now AI agents are using them
An API, or application programming interface, provides a defined way for software systems to communicate with each other. Instead of one application needing to understand how another application works internally, it can make a request through an API and receive a structured response.
For conventional software, the process is relatively predictable. A developer decides which API to call, when to call it, what information to send and how to handle the response. The application follows those instructions.
AI agents introduce a different kind of caller.
An agent can be given an objective rather than a fixed sequence of instructions. It may decide which tool or API it needs, determine the order in which to use them and adapt its next action based on what it receives.
That changes what organisations need from their APIs.
An API that works perfectly well for a developer may not necessarily be easy or safe for an AI agent to use. The agent needs to understand what a capability does, what information it requires, what it will return, what actions it might trigger and what can happen if something goes wrong.
The API becomes a tool for the agent
Consider a bank that has APIs for checking account balances, transferring money, verifying customers and reviewing transactions.
A traditional application has those APIs wired into predetermined workflows. A developer decides that a particular sequence of calls should happen when a customer performs a specific action.
An AI agent could potentially use the same underlying capabilities differently. If a customer asks an AI assistant to investigate a transaction, the agent could retrieve the relevant information, compare it with other records and determine which enterprise systems it needs to consult before responding.
If the agent is also authorised to take action, the stakes become higher.
The API is no longer simply providing data to an application. It becomes the controlled doorway through which an autonomous system can interact with the business.
That is why API design, access control, governance and monitoring become part of the AI conversation.
An API being available does not make it AI-ready
One of the more important distinctions emerging around agentic systems is the difference between an API being accessible and an API being useful to an AI agent.
A human developer can read documentation, understand business terminology, interpret an error message and figure out what to try next. An AI agent needs those capabilities to be exposed much more clearly through the interfaces it consumes.
The API needs to communicate intent and context. Its operations should be clearly defined, inputs and outputs should be predictable, and errors should provide information that allows the agent to understand what went wrong. Where an operation can create a side effect, such as sending money or deleting a record, that behaviour needs to be explicit and appropriately controlled.
This is where API design begins to intersect directly with agent design.
At WSO2Con Africa 2026, one of the technical sessions is specifically titled “Preparing APIs for Agentic Consumption.” The session will examine how API contracts, descriptions, schemas, error responses and workflow definitions influence an agent’s ability to select and use APIs correctly, as well as how capabilities can be made discoverable through developer portals, catalogues and MCP registries.
Where MCP fits in
The growing interest in Model Context Protocol (MCP) adds another layer to this discussion.
MCP provides a standardised way for AI applications to connect with external tools and data sources. In an enterprise environment, that can make it easier for agents to discover and interact with business capabilities.
But simply turning every existing API endpoint into an AI tool can create another problem.
An enterprise may have hundreds or thousands of APIs, many of which were designed around individual technical operations rather than business outcomes. Giving an agent access to every endpoint could leave it with too many choices and force it to reconstruct complicated business workflows on its own.
The more useful approach is often to expose capabilities in ways that make sense to the agent and the business process it is trying to complete.
For example, rather than giving an agent separate tools for checking a customer’s identity, retrieving an account and calculating eligibility, an organisation might expose a carefully designed capability around a particular business task, with the appropriate controls underneath.
The goal is not simply to give AI access to more APIs. It is to give agents useful, governed capabilities.
Security becomes part of the API layer
Giving an AI agent access to an API also raises a fundamental question: who is making the request?
With traditional applications, organisations have well-established approaches to authentication and authorisation. Users log in, applications authenticate themselves and permissions determine what they can access.
Autonomous agents complicate that model because an agent may act on behalf of a user or organisation while making decisions and invoking tools independently.
An enterprise therefore needs to establish what the agent is allowed to access, which actions it can perform and under whose authority it is operating. Sensitive information may need to be filtered, requests may need to be inspected, and potentially risky actions may require additional approval.
These issues are increasingly becoming part of API management itself. WSO2Con Africa’s agenda reflects that shift with sessions covering API security, PII masking, prompt guardrails and data sovereignty alongside discussions about AI-ready APIs.
APIs also give enterprises a way to work with what they already have
There is another reason APIs matter as companies experiment with agentic AI: most businesses already have them.
Enterprises have spent years exposing capabilities from banking platforms, ERP systems, customer databases, payment systems, HR applications and other infrastructure through APIs. Those interfaces can provide a starting point for connecting AI agents to existing technology without rebuilding the entire enterprise stack.
That does not mean existing APIs can simply be handed to an AI agent and left alone. They may need better documentation, clearer contracts, stronger access controls, additional monitoring or redesigned operations for agent consumption.
But the underlying capability may already exist.
This is particularly relevant for organisations that cannot afford to replace large portions of their technology infrastructure simply to accommodate AI. Instead, APIs can provide a controlled layer between emerging AI systems and the systems that already run the business.
The infrastructure behind the agentic enterprise
The discussion around agentic AI can easily become dominated by models, prompts and increasingly capable assistants. But an enterprise agent needs much more than an AI model to do useful work.
It needs access to data and business capabilities. It needs identity and permissions. It needs integration with existing systems, observability, governance and controls that limit what it can do.
APIs sit in the middle of many of those interactions.
That is why WSO2Con Africa 2026 is putting APIs alongside AI, integration, identity and security in its programme. The event’s Day 3 agenda includes “Designing APIs & MCP for AI Readiness,” while another session examines how enterprises can prepare existing APIs for agents. There is also a dedicated “Panel: APIs for Agents” featuring technology leaders from Stima SACCO, Mansa Bank and WSO2.
The broader shift is therefore less about APIs suddenly becoming new technology and more about who is consuming them and what that consumer is capable of doing.
For decades, APIs helped software talk to software. As enterprises give AI agents the ability to make decisions and take action, those same interfaces are becoming part of the control layer through which AI interacts with the business.
That makes the quality, security and governance of an organisation’s API estate increasingly important to its AI strategy. At WSO2Con Africa, that connection between APIs and agentic AI will be one of the more technical, but consequential, conversations taking place in Nairobi.
Real ESG impact doesn’t happen in panels alone, it happens in the rooms where financiers, operators, and policymakers actually align. Our GreenShift Forum 2026 cuts the noise, bringing together the people rewiring Africa’s sustainability and energy frameworks for one focused day in Nairobi. Secure your seat.
Go to TECHTRENDSKE.co.ke for more tech and business news from the African continent and across the world.
Follow us on WhatsApp, Telegram, Twitter, and Facebook, or subscribe to our weekly newsletter to ensure you don’t miss out on any future updates. Send tips to editorial@techtrendsmedia.co.ke
