Businesses across industries are embracing embedded payments to boost revenue and drive customer engagement, and independent software vendors (ISVs) are no exception. In 2025, 91% of ISVs say they expect embedded payments to play a larger role in their growth strategy over the next 12 months, according to a recent survey by Stax Payments.
Yet as ISVs scale their embedded payment strategies, they can’t ignore the growing role of AI in financial operations. Opportunities for AI use in embedded finance continue to expand, from enabling real-time payment processing to supporting hyper-personalized financial services. While this shift has clear advantages, it also introduces new responsibilities related to managing AI systems.
As AI becomes more central to embedded payments infrastructure, ISVs need a game plan to protect merchants. How rigorously they evaluate their embedded payments partners will determine whether AI becomes a catalyst for growth or an unintended source of risk.
AI’s expanding role in embedded payments
Already, 71% of companies are using AI in their finance operations, as the market for finance-specific AI tools barrels toward a $250 billion valuation by 2032.
For embedded payments providers, implementing AI can strategically enhance their services. Use cases for fraud prevention and risk management are well established, but continued AI investment in domains like B2B payments and credit and underwriting are expanding providers’ ability to improve diverse workflows.
In turn, ISVs can provide a better experience for end users by choosing an embedded payments partner with AI-powered capabilities. For example,
document review during merchant onboarding is a traditionally tedious and time-intensive process that can delay activation. If a payment provider uses AI to rapidly analyze identity documents and identify fraud signals, ISVs can shorten the time between a merchant’s application and first transaction to start generating revenue.
However, ISVs working with AI-enabled payment partners must also prepare for new complexities around connectivity and data movement. Particularly for agentic systems, where AI can take multi-step actions or access information on a user’s behalf, payment providers need strong governance and data controls to reduce compliance exposure.
Across the financial industry, organizations are still shaping their frameworks for responsible AI use: 38% of financial firms lack an established approach to evaluating when and how AI tools should be applied. ISVs cannot afford to take this risk. To realize the potential of AI in embedded payments, they need confidence that their payment partner is approaching deployment with disciplined oversight.
How ISVs can evaluate embedded payments partners in the AI era
For ISVs to benefit from AI-supported embedded payments solutions, responsible adoption is key. Strategically evaluating payment partners at the outset can help mitigate security vulnerabilities and improve long-term performance. These core elements are important to look for:
- An established governance framework
ISVs should expect their payments partners to approach AI with a mature governance framework that demonstrates they can deploy AI within payments operations while maintaining a reliable audit trail.
One benchmark is alignment with ISO 42001, the international standard for AI governance, which signals that a provider has defined processes for ethical use and continual improvement of AI systems. However, ISO 42001 does not stand alone.
In practice, effective AI governance depends on how standards are operationalized. Applying AI TRiSM (artificial intelligence trust, risk, and security management) principles indicates that a provider is actively managing AI risks and cyber threats through controls that support model
explainability and protect sensitive data to comply with regulations like GDPR.
These practices can reassure ISVs that AI use in payment workflows is properly monitored and models are not training on sensitive data.
- Demonstrated focus on preventing bias
AI can streamline payment-related decision making but may introduce unintended bias if not designed and monitored carefully.
For example, when a merchant engages with a payment processor through an ISV, the payment processor initiates an underwriting process. This is a standard risk assessment that the merchant needs to pass before the payment processor approves the business to accept credit card payments.
A payment processor may leverage AI during the underwriting process to run financial health assessments and analyze key financial data. However, if an AI model overindexes certain risk signals like an applicant’s credit score, it may unintentionally shift the profile of merchants that get approved and flag or reject viable merchants, reducing potential revenue opportunities.
To avoid these errors, ISVs should look for payment partners that continually monitor AI outputs over time to ensure they are reliable, explainable, and free from bias.
- AI infrastructure that balances security and innovation
Payment providers must also balance the promise of emerging AI tools with awareness of potential risks.
For instance, the rise of Model Context Protocols (MCPs) enables conversational data querying, allowing teams to efficiently access and analyze payments-related information. However, MCPs can create vulnerabilities for data exposure without clear authentication standards and access boundaries.
A strong payments provider will capitalize on the advantages of MCPs while enforcing clear safeguards around their deployment. This ability to
innovate without compromising security will position ISVs to safely capitalize on future AI evolutions in payments.
Adopting AI responsibly to drive sustainable payments growth AI unlocks the potential for ISVs and their payment partners to jointly offer better services to merchants by bringing new efficiency to resource-intensive processes. The question for ISVs, however, is whether this evolution will be an advantage or a vulnerability.
To achieve meaningful growth with embedded payments, any underlying AI technology must be secure, transparent, and well-governed. Critically, ISVs own the relationship with their merchants, so it is their responsibility to vet and select payment partners carefully.
By choosing partners that approach AI with clear guardrails and operational rigor, ISVs are empowered to deliver reliable, intuitive payment experiences for the customers that count on them.
