The Disruption Confidence Cycle in Fintech & Payments

By Joel Comm | A Trusted Voice in a Noisy Tech World

The payments industry is asking the wrong question about AI.

Instead of “How do we implement AI?” they should be asking “How do we stop panicking and start positioning ourselves for what comes next?”

I’ve watched this pattern repeat itself across six major technology revolutions over my 45 years in tech. The internet in the 1990s. Mobile payments in the 2000s. Cloud computing. Blockchain. Social commerce. And now artificial intelligence.

Each time, the same cycle emerges. Each time, the winners aren’t necessarily the first movers or the biggest companies. They’re the ones who understand where they are in what I call the Disruption Confidence Cycle and act accordingly.

Right now, fintech and payments is deep in the Doubt stage. And that’s actually good news.

Why Fintech & Payments Is Drowning in Doubt

When I keynote at fintech conferences these days, I see the same expression on every executive’s face. It’s the look of someone who knows they need to do something about AI but isn’t sure what that something is.

The doubt is everywhere. In boardrooms where VPs are asking if their fraud detection systems will become obsolete overnight. In product meetings where teams debate whether to build AI features or buy them. In strategy sessions where leaders wonder if their entire business model is about to get disrupted by some startup they’ve never heard of.

I remember similar conversations when I spoke at Microsoft about Twitter as social platforms were upending business communication. “Should we build our own?” executives asked. “What if we miss this one?” The anxiety was palpable — different decade, identical pattern.

The payments industry is experiencing that same anxiety multiplied by ten. AI in fintech and payments isn’t just another feature upgrade. It’s fundamentally changing how transactions happen, how risk is assessed, how customer service operates, and how financial products are designed.

Consider what’s happening right now:

• Customer service is being reimagined through conversational AI that can handle complex payment disputes
• Risk assessment is evolving from rule-based systems to predictive models that learn in real-time
• Regulatory compliance is shifting as AI systems make decisions that auditors struggle to understand
• Competitive landscapes are blurring as tech companies enter finance and financial companies become tech companies

The doubt isn’t just about technology. It’s about identity. Are you a payments company that uses AI, or are you becoming an AI company that happens to process payments?

This identity crisis is exactly what I watched play out during the cloud computing revolution. Traditional software companies suddenly had to decide if they were cloud companies. Many that hesitated too long found themselves irrelevant.

But here’s what most fintech leaders don’t realize: being in Doubt isn’t a weakness. It’s a strategic position if you understand what comes next.

The Path Forward: From Doubt to Confidence

The Disruption Confidence Cycle follows a predictable pattern with five stages: Disruption, Doubt, Clarity, Confidence, and Momentum. Disruption has already arrived for fintech and payments. Most of the industry now sits in Doubt. The companies that win aren’t those that skip stages, but those that move through them deliberately.

Clarity is where fintech companies start small. They pilot AI chatbots for customer service. They test machine learning models for fraud detection. They explore blockchain integration for cross-border payments.

I’m seeing smart payments companies enter this stage right now. They’re not betting the farm on AI. They’re placing small, strategic bets and learning fast.

Confidence is where the real magic happens. This is when companies stop thinking about AI as a separate initiative and start seeing it as integral to their operations. They understand which use cases work and which don’t. They know where humans still add value and where automation excels.

Momentum is where market leaders are made. These companies aren’t just using AI; they’re using it to create entirely new business models. They’re not just improving existing processes; they’re inventing new ways to think about payments altogether.

The timeline for moving through these stages varies. In my experience, early internet adoption took about five years. Mobile payments took three. AI in fintech and payments will likely take two years or less.

Why the acceleration? Because the infrastructure already exists. Cloud computing is mature. APIs are standardized. Development frameworks are robust. The building blocks for AI fintech and payments are already in place.

Six Revolutions, One Clear Pattern

In my four decades of watching technology revolutions unfold, the pattern is always the same. The companies that survive and thrive understand that disruption isn’t an event. It’s a process.

When the internet became mainstream in the 1990s, I watched traditional retailers struggle with the same questions fintech companies are asking about AI today. “Do we need a website?” became “Do we need e-commerce?” which became “Are we an internet company?”

The winners didn’t just build websites. They reimagined what it meant to serve customers.

When mobile payments emerged in the 2000s, I consulted with financial institutions that were terrified of becoming irrelevant. “What if people stop using banks?” they worried. The smart ones realized mobile wasn’t a threat to banking. It was a new way to do banking.

Now we’re seeing the same pattern with AI in fintech and payments. The question isn’t whether AI will disrupt the payments industry. It already is. The question is whether your company will lead that disruption or be victimized by it.

I’ve noticed something interesting across all six technology revolutions I’ve witnessed. The companies that succeed share three characteristics:

1. They start experimenting early but invest cautiously

2. They focus on customer problems, not technology features

3. They build partnerships instead of trying to do everything themselves

These principles are especially relevant for fintech and payments companies navigating AI adoption. You don’t need to become an AI company overnight. You need to become a company that uses AI to solve problems your customers didn’t even know they had.

The Questions Every Fintech Leader Should Ask

When I speak at conferences about AI keynote topics, executives always want a checklist. They want to know exactly what to do. But the right questions matter more than the right answers.

Here are the questions I’m hearing from the most forward-thinking fintech and payments leaders:

About customer experience: How can AI help our customers complete transactions they couldn’t complete before? This isn’t about making existing processes faster. It’s about enabling entirely new types of interactions.

About risk management: What risks are we not seeing that AI could help us identify? Traditional fraud detection looks at historical patterns. AI can identify emerging patterns in real-time.

About operational efficiency: Where are we still doing manually what could be automated intelligently? But be careful here. Not everything that can be automated should be automated.

About competitive positioning: How can we use AI to create value that competitors can’t easily replicate? The goal isn’t to implement AI. It’s to build sustainable competitive advantages.

About talent and culture: Do we have the right people to execute our AI strategy? This isn’t just about hiring data scientists. It’s about developing AI literacy throughout your organization.

About partnerships: Should we build, buy, or partner for AI capabilities? Most successful fintech companies are doing all three for different use cases.

The companies asking these questions are moving through the Disruption Confidence Cycle faster than those still debating whether to take AI seriously.

I remember being inside the room at Cisco during their digital transformation. The executives who succeeded weren’t those with the most technical knowledge. They were the ones who asked the best questions and surrounded themselves with people who could provide answers.

Moving from Anxiety to Action

The transition from Doubt to Confidence doesn’t happen by accident. It requires intentional leadership and strategic thinking.

Start with small experiments that have clear success metrics. Don’t try to revolutionize your entire operation overnight. Pick one customer pain point and use AI to solve it better than anyone else.

I often tell clients to think about AI implementation like building a fintech and payments product portfolio. You need some safe bets, some growth investments, and some moonshots. The safe bets fund the growth investments. The growth investments enable the moonshots.

For safe bets, consider AI applications that improve existing processes without requiring major infrastructure changes. Enhanced fraud detection. Automated customer service for routine inquiries. Predictive analytics for cash flow management.

For growth investments, look at AI applications that could create new revenue streams. Personalized financial products. Real-time risk pricing. Cross-border payment optimization.

For moonshots, explore AI applications that could fundamentally change your business model. Autonomous payment systems. AI-driven financial advisory services. Predictive commerce platforms.

The key is maintaining balance across all three categories while building organizational confidence with each small success.

Develop AI literacy throughout your organization. This isn’t about turning everyone into data scientists. It’s about helping everyone understand how AI might impact their role and how they can contribute to its successful implementation.

Create cross-functional AI teams. The best AI implementations happen when technologists, business leaders, and customer-facing teams work together from the beginning.

Establish clear governance frameworks. AI in fintech and payments involves sensitive customer data and regulatory considerations. Get the governance right early, or it will slow you down later.

Focus on customer outcomes, not technology capabilities. The most successful AI implementations solve real customer problems in measurably better ways.

As someone who has served as a trusted voice in a noisy tech world for nearly three decades, I can tell you that the companies winning with AI aren’t necessarily the most technical. They’re the most customer-focused and the most willing to experiment intelligently.

The Momentum Advantage

Companies that reach Momentum in the Disruption Confidence Cycle for AI in fintech and payments will have significant advantages. They’ll understand their customers’ needs better. They’ll operate more efficiently. They’ll identify and mitigate risks faster.

But perhaps most importantly, they’ll be positioned to create entirely new categories of financial products and services that don’t exist today.

I’m already seeing early examples. AI-powered micro-lending that approves loans in seconds based on real-time behavioral data. Payment systems that automatically optimize routing based on cost, speed, and reliability factors. Customer service experiences that feel more personalized than talking to a human representative.

These aren’t incremental improvements. They’re fundamental reimaginings of what financial services can be.

The fintech companies developing these capabilities aren’t necessarily the biggest or the oldest. They’re the ones that moved through Doubt quickly and are now in advanced stages of Clarity and Confidence.

Your Next Move

Here’s what I want every fintech and payments leader to understand: you’re not behind if you’re just starting to take AI seriously. You’re actually right on time if you act decisively now.

The Doubt stage is ending. Clarity is beginning. The companies that win will be those that experiment fastest and learn most effectively from those experiments.

The question isn’t whether AI will transform fintech and payments. The question is whether your company will help lead that transformation or spend the next five years trying to catch up.

What’s one AI experiment your team could launch in the next 30 days that would teach you something valuable about your customers’ needs?