By Izak van Heerden, Senior Manager: Development at Altron FinTech
South Africa's payments industry is at a crossroads. While the Big Four banks deploy AI-powered fraud detection, fintech startups and payment innovators are forcing competitive urgency through faster, cheaper alternatives. Add an economy where household finances remain constrained by inflation and interest rates, and the imperative becomes clear: payment providers must reduce transaction costs, speed up processing times, and eliminate friction from everyday payments.
The most transformative shift isn't generative AI. It's agentic AI, autonomous systems that execute multi-step financial tasks without human intervention. And most South African payment infrastructure wasn't built for this.
Unlike chatbots that suggest actions, AI agents take them. They initiate payments, reconcile invoices, and make purchasing decisions autonomously, according to Juniper Research’s Future of Payments report, which identifies agentic AI as the trend reshaping payments in 2026, while McKinsey characterises it as a revolution comparable to e-commerce.
The hard truth is that while our banks love talking about LLM co-pilots, their core engines are still stuck in the 'human-clicks-ok' era. That's a massive liability. The bank's LLM co-pilots and fraud prevention capabilities demonstrate clear use-case value, but moving from detection to action requires fundamentally different infrastructure. Our systems were designed assuming a human approves every transaction. That assumption is about to break.
Research from Juniper indicates AI agents will handle approximately one-third of B2B payment workflows globally by 2026. That's not a distant prediction, it's this year.
For South African payment processors, this matters because manual reconciliation, invoice matching, and exception handling consume resources that could be redirected to customer service or product innovation. We're not talking about replacing humans. We're talking about freeing them from work that shouldn't require human judgment in the first place.
In a market where every basis point of efficiency compounds into competitive advantage, the companies that automate this layer will pull ahead, fast.
AI-driven efficiency isn't optional anymore - payment providers must help banks, retailers, and financial institutions reduce costs, improve collections, and serve consumers whose budgets are stretched thin.
Automated reconciliation: AI matches invoices with payments instantly, eliminating the manual cost of matching each transaction. For South African enterprises processing thousands of payments monthly, think retailers managing gift card transactions or municipalities handling utility payments; every efficiency gain translates to real cost savings.
Predictive payment timing: Instead of blindly hitting a customer's account on the 1st of every month, systems analyse cash flow patterns to determine the optimal collection window. This reduces failed debit orders (and their associated fees) while respecting customer liquidity constraints. When a debit order fails, it costs everyone - the merchant loses revenue, the bank processes a reversal, and the customer gets hit with fees.
Intelligent routing: AI evaluates multiple payment rails in real-time, selecting the fastest, cheapest, or most reliable option based on current conditions, transaction amount, and urgency. Think of it as GPS for money, constantly recalculating the best route.
Autonomous vendor payments: Businesses set the parameters; AI executes. When inventory hits reorder levels, agents initiate supplier payments using pre-approved logic and negotiated terms. No purchase orders sitting in someone's inbox for three days.
Dynamic credit decisioning: Real-time affordability assessments powered by transaction data, not static credit scores three months out of date. This enables faster, more accurate lending decisions, particularly important for underbanked consumers who may have strong cash flow but limited credit history.
Here's the problem: Agentic AI demands payment infrastructure that doesn't exist yet in South Africa. Our traditional systems were built on a simple assumption, a human initiates every transaction. Agent-driven commerce breaks that model entirely.
Mandate frameworks: How does a payment processor verify an AI agent's authority to spend on behalf of a user? Internationally, protocols like Google's Agentic Protocol for Payments (AP2) and OpenAI's commerce frameworks tackle this through cryptographically signed mandates that link intent, cart, and payment authorisation. South African banks will need to build local implementations that integrate with our existing mandate systems, particularly DebiCheck, which already handles authenticated debit orders.
Agent-to-agent communication: When your purchasing agent negotiates with a supplier's pricing agent, they need shared protocols for discovering options, comparing terms, and executing transactions. Right now? No South African bank supports machine-to-machine payment negotiation. We're still in the "human picks up phone" era of B2B payments.
Audit trails: Every autonomous action requires traceability. Who authorised what, when, and why? South Africa's POPI Act compliance becomes exponentially more complex when AI makes decisions on behalf of humans. "The algorithm did it" isn't a legal defence.
Fraud prevention 2.0: Distinguishing malicious bots from legitimate agents demands entirely new approaches. Behavioural biometrics work brilliantly for humans - tracking typing speed, mouse movements, and login patterns. But agents don't behave like humans. They transact faster, more consistently, and at scale. We need new models.
As enterprise payment infrastructure providers, we sit at the layer where AI agents will actually transact. This isn't theoretical for us.
Our platforms already process millions of transactions monthly for banks, retailers, and financial services companies across South Africa. The shift to agentic commerce means our customers will need infrastructure that simply doesn't exist in most legacy systems:
We're building for a world where payments happen at machine speed, but humans still need control and visibility.
By late 2026, expect to see corporate treasury automation where the CFO approves parameters, and AI manages day-to-day cash positioning, payments, and short-term investments within those guardrails. For companies processing 500+ vendor payments monthly, this eliminates bottlenecks while maintaining control.
Subscription intelligence where agents identify unused subscriptions, negotiate better rates, or switch providers automatically. In an economy where every rand matters, eliminating R50,000 in unused SaaS subscriptions (the "vampire subscriptions" bleeding companies dry) compounds quickly.
Dynamic instalment plans that adjust in real-time based on customer cash flow. When liquidity is constrained, the system extends terms automatically, reducing defaults while maintaining collection rates. This is particularly powerful in South Africa's consumer credit environment.
Supply chain finance where agents monitor inventory, initiate just-in-time supplier payments, and optimise working capital without human intervention. For retailers managing thousands of SKUs, this turns payments from an administrative overhead into a competitive advantage.
The question for South African payment providers isn't whether to adopt AI in payments. It's how fast you can build the infrastructure. Because the providers who view AI as back-office automation will fall behind the ones building rails for autonomous commerce.
At Altron FinTech, we're choosing the latter. Building payment infrastructure that agents can trust, because when AI starts paying your bills, it needs to know the system works at machine scale, thousands of times per second, without breaking.
Have questions or ready to talk? Contact our team https://fintech.altron.com/