AI Commerce Needs Better Payments—Here’s the Proof

A payment failure is the most expensive “bug” in e-commerce. It doesn’t matter how good your AI product recommendations are, how sharp your lifecycle emails look, or how perfectly your chatbot handles delivery questions—if checkout declines, revenue disappears.

That’s why a recent move in African digital commerce matters more than it sounds at first glance: Xsolla (a global video game commerce company) has added SPENN as a payment method in Rwanda and Zambia. On paper, it’s a payments integration announcement. In practice, it’s a case study in how modern digital services grow in mobile-first economies—and what South African retailers and digital service providers should take from it as they scale AI-powered commerce.

Two stats from the announcement frame the opportunity clearly: about 86% of Rwandan adults own or have used mobile money (FinScope 2024), and Zambia’s mobile money transaction volumes rose 44% to 1.4 billion transactions by mid-2024. In markets like these, the “default” card-based checkout flow isn’t the default at all.

Payment integrations are the foundation for AI-powered commerce

AI-powered e-commerce only works when payments match local behavior. If the preferred consumer habit is wallet-led payments, then the most advanced personalization engine in the world won’t fix a checkout built for someone else.

The Xsolla–SPENN integration highlights a simple but often ignored reality: conversion rate optimisation starts with payment rails, not just landing pages and ad creative.

When you add a wallet method that people already trust and use daily, you typically see three downstream effects that AI can then amplify:

• More successful checkouts (fewer declines): You can’t optimise what doesn’t complete.
• More repeat buyers: Familiar payment flows reduce friction the second and third time.
• Better data for AI: More completed orders means cleaner signals for recommendations, churn prediction, and LTV modelling.

For South African businesses building AI-driven digital services—subscriptions, gaming, streaming, online education, on-demand delivery—the message is blunt: payments aren’t a “finance problem”. They’re a growth model input.

Why “fewer declines” is an AI KPI (even if you don’t track it)

Declines are rarely random. They cluster by:

• payment type (card vs wallet)
• device and network conditions
• fraud rules and 3DS friction
• cross-border routing
• customer segment (new vs returning)

If your checkout fails disproportionately for first-time buyers, your AI will “learn” the wrong lesson: that acquisition channels are low quality, that certain regions don’t convert, or that price points are wrong. You end up optimising the model around broken plumbing.

Mobile-first economies are where digital services scale fastest

Rwanda and Zambia being “wallet-led” is the headline—but the deeper point is adoption speed. In mobile-first markets, consumer habits form around what works on a phone with real-world constraints: intermittent connectivity, low tolerance for multi-step verification, and a heavy reliance on trusted local brands.

That matters to South Africa because our market is increasingly split:

• Urban, card-friendly customers who expect fast one-tap checkout
• Mobile-first customers who prefer wallets, bank transfers, or other local methods

If you’re selling nationally (or across borders in SADC), you can’t treat checkout like a single design. You need a payment mix that mirrors your audience mix.

A practical rule: match payment methods to your growth map

If your growth plan includes “expand into region X,” your payment plan needs to answer:

1. What do customers in that region already use daily?
2. What’s the failure rate if we force card payments?
3. How quickly can we add wallet-based methods through a provider?

The Xsolla example is a reminder that adding a trusted wallet option can be the difference between “we launched” and “we grew.”

What Xsolla + SPENN teaches South African e-commerce teams

The integration’s stated benefits—streamlined checkout, fewer declines, access to a growing wallet network—map directly to South African e-commerce pain points. Here’s how to translate them into actions you can take.

1) Streamlined checkout isn’t design—it’s decision reduction

Most companies get “streamlined checkout” wrong. They focus on UI polish and ignore the biggest friction: asking customers to use a payment method they don’t prefer.

A better approach is to use AI (and plain common sense) to reduce decisions:

• Show the most likely payment method first based on device, region, and historical conversion.
• Remember the last successful method for returning customers.
• Offer wallet options early (not hidden behind “More payment methods”).

This is where AI helps: once you have enough data, you can build a simple ranking model that predicts payment-method success per session. Even a rules-based version (geo + device + returning customer) improves conversion quickly.

2) Fewer payment declines is revenue retention, not just “more sales”

Declines don’t only lose the immediate order. They also:

• increase support tickets (“My payment didn’t work”)
• lower trust (“Is this site legit?”)
• reduce the chance of a second attempt

If you’re running AI-driven marketing automation—retargeting, abandoned cart flows, win-back emails—declines can inflate your marketing cost because you’re paying to recover transactions that shouldn’t have failed.

What I’ve found works: treat declines like a product metric. Create a weekly “payment health” review that includes:

• decline rate by method
• decline rate by bank/wallet provider (where available)
• time-to-complete checkout
• refund and chargeback rate

Then feed the outcomes back into your AI campaigns. For example: if wallet checkouts succeed 12% more often in a segment, your ad landing experience should default to wallet.

3) Access to wallet ecosystems expands addressable market

SPENN isn’t just a payment button—it represents a consumer-merchant ecosystem. Wallet networks often come with habitual use cases: P2P transfers, airtime, bill payments, merchant QR payments. When a wallet becomes part of daily life, it’s easier for digital services (games, subscriptions, digital goods) to ride that behaviour.

For South African brands expanding into African markets, wallet ecosystems solve two common problems:

• Trust transfer: customers trust the wallet brand even if they don’t know you yet.
• Distribution support: wallets can become a marketing surface through partnerships and merchant networks.

AI ties in when you personalise onboarding and lifecycle messaging to wallet users differently from card users. Wallet customers may respond better to smaller, more frequent purchases or bundled offers aligned to how they top up.

Where AI fits in: smarter payments operations (not just smarter marketing)

AI in South African e-commerce often gets boxed into content generation, ads, and chatbots. Useful, yes. But the strongest compounding gains usually come from AI applied to transaction infrastructure.

Here are high-value, realistic ways AI supports payments and digital services once you’ve added the right local methods.

AI use case: payment routing and retry logic

The goal is simple: turn “failed” into “completed” without annoying the customer.

Examples:

• Smart retries timed to when wallet balances are replenished (e.g., after payday cycles)
• Routing transactions through the path with the highest historical success rate
• Detecting “soft declines” vs “hard declines” and choosing the right next step

Even basic models can outperform generic retry schedules because success patterns differ by market.

AI use case: fraud prevention that doesn’t punish real buyers

More payment methods can increase complexity, and fraudsters love complexity. But heavy-handed fraud rules can also block real customers—especially first-time buyers.

AI-based fraud scoring works best when it’s paired with local payment methods that have built-in trust and verification. The win is lower fraud without raising decline rates.

AI use case: personalisation tied to payment preferences

If your recommendation engine treats all customers the same, you’ll miss patterns like:

• wallet users preferring lower ticket sizes and higher frequency
• subscription churn correlating with certain payment methods
• higher LTV when customers switch from cash-like methods to stored-value wallets

Payment preference is a behavioural signal. It should sit next to device, channel, and product affinity in your customer models.

A practical checklist for SA businesses selling digital goods or services

If you’re building AI-powered e-commerce in South Africa and planning regional growth, this is the checklist I’d start with.

1. Map payment preference by segment (not by “country” only): metro vs rural, Android vs iOS, new vs returning.
2. Add at least one wallet-led payment option in markets where wallets dominate.
3. Measure declines like you measure CAC: by channel, by device, by payment method.
4. Use AI (or rules) to rank payment methods on checkout and default to the most successful.
5. Build decline recovery flows that respect context: instant retry prompts for network issues; delayed retries for insufficient funds.
6. Connect payments data to your AI marketing automation: personalise offers and messaging by method.

If you do only one thing this quarter, do this: report conversion rate by payment method. You’ll find hidden losses fast.

What this means for the “AI in South African e-commerce” story

The bigger narrative in this series is that AI is only as effective as the systems it can act on. Xsolla adding SPENN in Rwanda and Zambia is a clean example: improve payment access and reliability first, then let AI optimise the rest—personalisation, retention, support, and pricing.

South African retailers and digital service providers are often ahead on AI experimentation—automated campaigns, product recommendations, generative content. The next advantage comes from being equally serious about transaction infrastructure, especially when you expand into mobile-first African markets.

If you’re planning 2026 growth, here’s the question worth sitting with: Are you building AI on top of the payment behaviours your customers actually have—or the ones you wish they had?