Understanding Agentic AI in Financial Services

Is AI Really Coming for My Job?

Change often brings uncertainty. It’s human nature to feel uneasy about things we don’t fully understand — and artificial intelligence (AI), particularly in the workplace, is no exception. Lately, the fear that “AI is coming for my job” has become a growing concern across industries, especially in financial services.

Before jumping to conclusions, let’s ask a more useful question: What exactly is agentic AI, and how might it actually change the way we work?

What Is Agentic AI?

At its core, an AI agent is a software system that leverages artificial intelligence to perform tasks and achieve goals on behalf of a user. These agents can operate autonomously, adapt to new information, and complete specific actions — often faster and more consistently than humans.

Agentic AI refers to a network of these intelligent agents working in coordination, not just as tools but as collaborators. They’re not just doing one thing — they’re managing multiple steps of a process, learning as they go, and assisting humans in more intelligent ways.

Could AI Really Replace My Job?

Maybe parts of it — but probably not all.

Most jobs contain a mix of static, repetitive tasks and dynamic, judgment-driven responsibilities. AI is exceptionally good at the former and still very limited at the latter. In fact, when AI systems are asked to complete a series of complex tasks, their success rate drops significantly — to just 30%, according to The Register (https://www.theregister.com/2025/06/29/ai_agents_fail_a_lot/ ).

So, if AI can only do your job a third of the time, why worry?
Because it’s not about replacement — it’s about transformation. That 30% represents the portion of your job that’s time-consuming, tedious, and ripe for automation. And that’s where agentic AI comes in.

A Familiar Pattern: Is AI the New Outsourcing?

This isn’t the first time we’ve seen workforce anxiety caused by operational shifts. Over the years, business leaders have cycled between in-house staffing, outsourcing, nearshoring, and offshoring — often presenting each as a solution to inefficiencies. Eventually, someone proclaims the old method broken and moves on to the next iteration.

The same pattern is playing out today with AI. But this time, it’s not about location — it’s about intelligence.

A Real-World Example: KYC in Financial Services

Let’s consider one of the most foundational processes in financial services: Know Your Customer (KYC). This is a perfect candidate for agentic AI — a complex process made up of many smaller, automatable tasks.

The Four Key Stages of KYC:

1. Initiation
   A customer submits basic information through a form, an online application, or by speaking to a representative.
2. Data Enrichment
   Additional details are gathered either directly from the customer or from third-party sources (e.g., credit bureaus, government databases).
3. Due Diligence
   Depending on the customer’s profile, geography, and product type, various risk assessments are performed: AML checks, credit approvals, enhanced due diligence, etc.
4. Fulfillment
   Once approved, accounts are opened, credit lines are funded, and the relationship officially begins.

Could AI handle all of this? Eventually, perhaps. But not yet — and certainly not without oversight. For example, if an automated KYC process misses key red flags, who’s accountable? Is it acceptable to lose 17% of new business to reduce staffing costs?

More realistically, AI will play a supporting role, automating the predictable parts and flagging the nuanced ones for human review.

Where Agentic AI Shines

Agentic AI is already reshaping financial workflows. Here’s how it’s being used today:

• Form Assistance: AI agents guide customers through online applications in real-time.
• Data Verification: Agents check government sources to confirm addresses or identity.
• Voice Interfaces: AI-powered call agents answer questions, transcribe conversations, and summarize intent for audit trails.
• Document Handling: Agents extract data from scanned IDs, match it to internal records, and identify missing fields.
• Background Checks: AI agents initiate third-party screenings and compile results for compliance teams.

Think of it as a relay race: agents handle the repetitive legs so humans can focus on decision-making.

The Power of Coordination

Many of these tasks could be automated before — using APIs, rule-based systems, or workflow routing. What’s different now is the orchestration. Agentic AI ties together these moving parts, coordinates them in real-time, and ensures data flows seamlessly through systems.

It’s not just automation — it’s collaboration between human expertise and machine efficiency.

Don’t Fear AI — Build for It

A few years ago, I met a prospect wanting to improve on their current poor OCR (optical character recognition) of paper applications. Their system had just a 50% success rate. Instead of fixing the broken process, they doubled down on digitizing the paper — a classic case of automating inefficiency.

Today, financial firms are taking cues from Amazon and Netflix: intuitive design, simple onboarding, one-click experiences. Agentic AI plays a key role behind the scenes — enriching data, improving response time, and reducing human error.

Final Thoughts: The Future of Work Is Collaborative

AI won’t replace you. But someone using agentic AI might.

The most successful financial professionals in the coming years will be those who embrace AI as a partner — one that handles the heavy lifting while they focus on what matters most: relationships, judgment, and strategy.

The future isn’t man or machine. It’s man with machine.

Want to explore how agentic AI could enhance your operations? Reach out or leave a comment — let’s talk about what’s next for your team.