We are AI. But, are you?

I’m often asked: Will open AI models not suffice for financial services; and that we'd not need the vertical AI as these models further evolve? Maybe.

But would they really? And why isn’t vertical AI just a GPT wrapper?

Ai is everywhere. It’s in our searches, our conversations, our recommendations. But is AI truly embedded in industries that demand precision, compliance, and real-time decision-making? That’s where the distinction emerges—between generalist AI wrappers and vertical AI built for action. Do we need purpose-built, vertical AI models for finance, or can open, generalist AI models do the job?

Same, same. But different.

A GPT wrapper looks specialized on the surface. It may use fine-tuning, structured prompts, and domain-specific data, but beneath it all, it still relies on a generalist AI model. It can answer questions, summarize information, and assist workflows—but it does not execute decisions, integrate deeply with industry-specific infrastructure, or enforce regulatory compliance.

A vertical AI model, on the other hand, is engineered for a specific industry. It doesn’t just analyze—it acts. It retrieves, reasons, and automates decision-making within structured environments like finance, healthcare, or cybersecurity, where precision is not optional.

Where wrappers work well:

• Automating FAQs for customer service in banking
• Generating financial summaries or legal briefs
• Providing general investment insights based on historical data

Where wrappers fail and vertical AI is needed:

• Continuous behavioral analysis and execution across multiple financial touchpoints
• Dynamic risk assessment based on real-time financial data, not just past trends
• when portfolio needs to act on live market movements, cash flow shifts, and economic indicators

What's interesting is that those who know the gap are moving beyond the generics. The reason? Complexity. General AI can automate, but it cannot execute nuanced decisions.

Now, why wrappers won’t break much in financial services..

Finance is one of the most context-heavy, regulated, and behavior-driven industries. Every transaction has a real-time risk factor, every investment is influenced by macro and micro trends, and every financial decision is deeply personal.

A generic AI wrapper won’t break finance, but it won’t move it forward either. Open AI can tell you how to improve your credit score, but vertical AI will adjust your credit utilization in real time. It doesn’t just provide insights—it acts. Finance must also operate within regulatory frameworks such as open banking and data localisation requirements, which vertical AI models are designed to navigate from inception.

Financial decisions are not purely computational; they involve behavioral patterns, emotional triggers, and market psychology. Vertical AI integrates all these layers to create real-time financial intelligence rather than static insights.

Financial services can’t rely on general AI models that don’t integrate with live data, can’t justify their decisions, and don’t take action. AI in finance needs to be embedded deeply into workflows, not just layered as a chatbot or an automation tool.

• Open AI will still play a role in automation, document processing, and customer interactions
• But, vertical AI will drive decision-making, risk management, fraud detection, and personalized financial automation.

The real competitive edge will be in how well AI is embedded into financial operations—not just as a knowledge tool, but as an agent that understands, reasons, and executes.

Finance is evolving, and AI is evolving with it. But there’s a difference between AI that assists and AI that acts.

General AI provides automation. Vertical AI provides intelligence.

The future of AI in financial services belongs to those who understand the difference—and choose to build, not just wrap.