Asaf Darash is the founder and CEO of Regpack, an online payment management platform. He holds a Ph.D. in New Media.
AI has become the defining theme of 2025. Nearly every boardroom conversation, industry conference and investor deck includes a reference to AI. But behind the hype, leaders are asking a more pragmatic question: What does AI actually mean for the way we run our organizations?
For some software-as-a-service (SaaS) leaders, the answer includes AI integration and embedded fintech. From my experience providing automated SaaS billing software, I’ve learned that when AI and fintech are deployed strategically, and with careful considerations for the risks, SaaS platforms can position themselves as proactive business partners to their users.
Horizontal Versus Vertical SaaS: Where AI And Fintech Can Create Value
Horizontal SaaS platforms have reshaped how modern businesses operate. Their strength lies in scalability and flexibility, offering solutions that work across many industries. However, broad-based platforms often fail to account for sector-specific workflows or compliance challenges. That’s why I believe vertical SaaS and, increasingly, hybrid approaches that combine horizontal scale with vertical specialization are well-positioned to maximize the value of AI and fintech.
The SaaS market overall is on a steep upward trajectory, expected to reach $720 billion by 2028, growing at nearly a 26% compound annual growth rate. And many companies are already using AI both internally and in their products. SaaS Capital’s annual survey found that 88% of SaaS businesses using AI in their company operations had also deployed it in their product. (The annual survey received about 1,000 responses from executives, according to a blog post by the company titled “SaaS Capital AI Update for 2025 Q1.”)
Embedding Financial Workflows Into SaaS
In SaaS, billing and payments are not side features; they’re core to retention, trust and growth. Disconnected payment systems can create friction for both businesses and their customers. This is why some platforms are embedding fintech; they’re trying to close that gap.
Embedded finance already processes $2.6 trillion in U.S. transactions, with projections surpassing $7 trillion by 2026. Integrating payments, accounting and financial options into their software has the potential to support new revenue streams and improve the customer experience.
Best Practices For Getting Started
Successfully embedding financial workflows into SaaS starts with alignment between your business model, your customers and your technical capabilities. In my experience, it’s common for organizations to partner with external fintech providers, rather than building from scratch, but choosing the right partner requires clarity.
If you’re looking for a provider, I recommend asking about their compliance coverage, including payment card industry (PCI), know your customer (KYC) and anti-money laundering (AML); whether their APIs are scalable and can integrate cleanly with your existing systems; and whether their reconciliation tools are transparent. Questions like “Who owns the data?” “How do we handle failed transactions?” and “What level of control do we retain over the user experience?” should be answered before implementation begins as well.
Moreover, keep in mind that the most common hurdle isn’t technical, in my experience; it’s operational. Finance, product and engineering teams must work together to embed fintech in a way that’s invisible to users but dependable behind the scenes. The goal isn’t just to collect payments; it’s to build an infrastructure that customers can trust without thinking about it.
Where AI Comes In
If embedded fintech aims to make payments simpler, AI aims to make them smarter. Organizations can consider using AI to analyze usage and billing data, identify patterns, predict churn risk and recommend optimized pricing or payment structures.
The adoption trend is clear. One survey of 1,000 business and tech leaders across 10 countries found that 71% of respondents are actively using or piloting AI. Keep in mind that AI shouldn’t be used to replace human strategy, however; your goal should be to gain visibility, predictability and control in financial and operational decisions.
Challenges To Consider
It’s also important to note that there are limits and risks to be aware of when using AI. The most immediate challenge is data integrity. AI systems need to be trained on quality data; incomplete or biased datasets are likely to result in flawed predictions, inaccurate credit assessments or compliance blind spots. Financial workflows demand precision, and even minor algorithmic errors can erode trust or trigger regulatory scrutiny.
Another growing concern is explainability. Leaders should be able to articulate how AI-driven decisions are made, especially when they impact billing, credit or customer approvals. Black-box models may speed up automation, but they can expose organizations to reputational and legal risk if outcomes can’t be justified.
The best safeguard is human-in-the-loop design: pairing automation with oversight. Implement AI gradually, with clear testing protocols, bias audits and manual checkpoints during early deployment. In fintech, confidence comes not from replacing judgment but from reinforcing it. When AI is implemented responsibly, it can become more than a feature; it’s a trust multiplier.
From Utility To Strategic Partner
The most significant shift is relational. SaaS platforms considering integrating AI and embedded fintech can redefine their role in the business landscape if it’s done thoughtfully. When billing is seamless, when insights are predictive and when workflows scale automatically, companies can redirect their energy toward what software can’t replicate: building trust, innovating products or services and strengthening customer relationships.
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