AI agents and their impact on fintech and beyond

Tiffine Wang is a global venture capitalist focused on AI and tech, along with board advisory.

Over the past decade in Silicon Valley, I’ve witnessed the steady evolution of artificial intelligence (AI) reshaping industries and the nature of work itself. What began as rule-based chatbots has progressed into co-pilots and now AI agents. With each iteration, these solutions have become increasingly sophisticated.

AI agents represent the next step in intelligent systems, building on familiar technologies like chatbots and workflow automation tools in order to deliver more dynamic, goal-oriented capabilities.

While there has been talk of AI replacing humans, the reality is that your job will most likely be replaced by another human who knows how to navigate AI. AI agents are not revolutionizing the field entirely but rather extending it, enhancing the ways humans and machines collaborate meaningfully. 

Key differences between chatbots, copilots and agents

For much of AI's history, AI user interfaces were fairly limited. They were good at executing predefined tasks like answering basic questions or processing data. Early virtual assistants like Siri or Alexa could respond to commands, but could not dynamically adapt based on user input or usage patterns in an intelligent way. Many of us have experienced this. To enable adaptation, developers had to collect usage data—including everything the user is doing, what they are clicking on, what they are viewing, and more—and retrain the underlying models. It is a computationally intensive, time-consuming and data-heavy process, and these systems operate within a narrowly defined scope.

However, increased investment in AI agents and breakthroughs in large language models (LLMs) and other technologies have unlocked many new possibilities. Today, AI agents can “understand” complexity that was once thought impossible. They’re capable of holding conversations, analyzing data and even making recommendations. Unlike previous systems, they can learn and adapt, making them far more flexible and dynamic in their capabilities.

What sets an AI agent apart?

Is it just a collection of features, or is there something deeper that defines a true AI agent? The key differentiator lies in the intelligence and autonomy these agents can exhibit. Today, AI agents are not just rule-based tools, but instead, they have the potential to make decisions, and can now take early steps to adapt to new situations and learn from context. They are a major step towards an autonomous intelligence system that can think and act independently within a defined scope.

In fintech, this shift is already starting to show its impact. AI agents are being used not just to automate tasks, but to make smarter decisions in real time like detecting fraud or providing tailored financial advice. These agents could fundamentally change how businesses operate, delivering both efficiency and intelligence across various sectors. 

The key distinction between a chatbot, an AI agent, and the “holy grail” of artificial general Intelligence (AGI) lies in the level of autonomy and adaptability. AI agents have the potential to make decisions based on context, learn from their experiences, and continually improve.They can move them beyond mere features to become integral, intelligent players in their respective fields, whereas an AGI would not be bound to a specific field or set of them.

AI agents are revolutionizing workflows by automating tasks and collaborating seamlessly with one another. These interconnected systems share information, optimize processes and adapt collectively, thus driving efficiencies. This ability to work both independently and together enables businesses to scale, while improving precision and responsiveness. As AI agents become more autonomous, it's crucial to integrate them with ethical principles, transparency and human oversight. 

In finance, AI can act as a 24/7 personal advisor, continuously analyzing market conditions, monitoring individual portfolios,and automatically adjusting strategies to optimize returns while minimizing risks. For investors, this means reduced uncertainty and more confident decision-making as AI predicts shifts in the market before they happen. 

In the insurance sector, AI will automate claims processing and verify damages. Customers will experience a more personalized service, with AI tailoring policies and pricing based on individual behavior, lifestyle and health data, making it easier to find affordable coverage. 

Companies, however, would need to consider the negative effects of hyper tuning individual risks against the benefits of large pools in this example. Of course, the benefits come with potential risks. As AI takes on these routine tasks, human professionals will be freed to focus on high-level strategy and creative problem-solving. In this future scenario, our interactions with technology should feel more effortless and intuitive, making AI a silent partner in both our financial success and personal security, reshaping how we work, live and engage with the world around us.