Artificial intelligence is already present in banking. In June 2026, the European Central Bank indicated that more than 85 % of the banks under its supervision were already using AI. In Africa, GITEX Africa estimates that the continent accounts for nearly 50 % of the world’s mobile money users, while African fintech revenues could increase from USD 30 billion in 2025 to USD 65 billion by 2030.
These figures show that the foundations are already in place: widespread mobile usage, growing volumes of transactional data, and the digitalisation of banking journeys.
The next stage, however, will not simply be another chatbot. It will be agentic AI: systems capable of carrying out several coordinated actions within a banking process, with clearly defined permissions and human oversight.
By 2027, the challenge for African banks will be less about multiplying experiments and more about transforming selected use cases into reliable, measurable, and secure services.
A chatbot answers a question. An AI agent pursues an objective.
In the context of a credit application, a chatbot can explain the eligibility conditions. Depending on the permissions granted to it, an AI agent can:
The final decision can remain in the hands of the banker. The agent automates the research, verification, and preparation of the file, while sensitive decisions remain subject to human approval.
The Bank for International Settlements also notes that AI and digital finance can improve efficiency, reduce costs, and support the integration of financial markets, while creating new types of risks for institutions and supervisors.
Announcements made in 2026 show that AI agents are beginning to be integrated into business processes, rather than being limited to conversational interfaces.
On May 4, 2026, FIS announced that it was working with Anthropic to develop an AI agent dedicated to fighting financial crime.
The system is designed to gather the information required to analyse an alert, compare it with risk scenarios, and present priority cases to investigators.
FIS states that the objective is to reduce certain investigations, which currently take several hours or several days, to just a few minutes. This is a performance target announced by the provider, rather than a result already achieved across the entire banking sector.
The lesson is nevertheless important: the initial value of an AI agent does not necessarily lie in autonomous decision-making. It may lie in its ability to search for, collect, and document the information required for human decision-making much more quickly.
On May 14, 2026, Fiserv launched agentOS, a platform designed to deploy, manage, and govern AI agents within banking operations.
This development reflects a new level of maturity. Institutions are no longer simply looking to develop one agent for each need. They must now manage agent identities, access rights, interactions, authorised actions, and human approvals.
Oracle launched an agentic platform for retail banking in February 2026 and extended it to corporate banking in April.
The announced use cases include credit, corporate lending, treasury management, and trade finance. Oracle positions human oversight as a central component of its agentic architecture.
These examples remain vendor announcements. However, they show that the market is moving towards AI that is directly integrated into banking operations.
The more an agent is able to act, the more precisely a bank must control its scope.
Each agent should have:
The European Central Bank points out that AI can improve risk management and IT security, but that it also increases the capabilities available to malicious actors.
The Bank for International Settlements also emphasises data quality and data governance. When an AI system is used in core financial activities, institutions must be able to demonstrate which data was used, how it was controlled, and which rules governed its use.
In a bank, an AI agent should therefore not be regarded as a simple software application. It should be treated as a governed, audited, and monitored digital identity.
Africa has a particularly favourable context for the development of agentic banking.
According to the GSMA, USD 1.432 trillion moved through mobile money services in Africa in 2025. According to market projections presented by GITEX Africa, African fintech revenues could more than double to reach USD 65 billion by 2030.
These estimates come from the organiser of GITEX Africa and should be regarded as market projections. They nevertheless confirm several trends:
African banks do not therefore have to reproduce all the complex legacy architectures of more mature markets. They can progressively integrate specialised agents on top of their existing platforms, provided that security, interoperability, and data sovereignty are preserved.
Five areas offer tangible potential.
An agent can verify the presence of supporting documents, extract the relevant information, and transfer unusual cases to a compliance officer.
It can gather authorised data, check eligibility rules, and prepare an explainable recommendation.
It can enrich alerts, connect related transactions, and prepare a documented case file for the investigator.
It can consult the customer’s history, verify the status of a transaction, and prepare a response or an authorised action.
It can identify potential cash-flow pressure, simulate several scenarios, and provide an alert tailored to the customer.
Success should not be measured by the number of agents launched, but by their impact on operations.
Banks can monitor:
An agent that performs impressively during a demonstration, but does not reduce processing times, costs, or errors, is not yet an industrialisable use case.
The first use case should involve sufficient volume, accessible data, measurable costs, and a manageable level of risk.
The agent prepares the file or recommends an action. A human employee retains approval authority until the system’s reliability has been demonstrated.
Identities, access rights, audit trails, and escalation rules must be defined before several agents are connected.
Agentic banking does not replace digital transformation. It represents its next stage.
A mobile application allows customers to access the bank. An agentic system helps accelerate and coordinate the operations taking place behind that interface.
For MEDIANET, this evolution is a natural extension of its expertise in digital banking, e-KYC, mobile banking, BPM, integration, data, and sector-specific platforms. The next objective is to enhance these environments with specialised, governed agents that are progressively integrated into business processes.
By 2027, the question will no longer be: “Should we adopt AI?”
It will be: “Which first process can we improve in a measurable way, without compromising trust?”
