In finance and across other sectors, Artificial Intelligence isn’t just a layer of tech we bolt onto existing systems—AI is reshaping the business model, the business processes, and even the talent models that define the industry. This post explores how AI (Generative AI and Agentic AI in particular) is transforming financial services through intelligent automation, next-gen portfolio management, real-time compliance, and human-AI collaboration. The wave of AI excitement is more than a hyped trend; it represents a fundamental shift in how we think, work, and lead. But as we ride that wave, we have to keep to the human side of the fence—using AI not to replace judgment, but to elevate it.
AI in Finance: A Personal Starting Point
I opened a recent talk with a simple invitation: find me on LinkedIn so we could start a real connection. Why? Because the faster you build your network, the faster you accelerate your learning, and learning is once again the premium currency. In this new AI-driven paradigm, it’s not just what you know; it’s how fast you adapt. Connection is a force multiplier.
When I entered the industry, human intuition still held court. Decisions were driven by experience, instinct, and Excel models—plenty of Excel models. Quants—my people—had their corner of the floor, building quietly, challenging the status quo with code, statistics, some early forms of AI, and an appetite for scale. We spent a lot of time (constructively) debating our fundamental colleagues (and ourselves!) on modeling assumptions, data hygiene, and whether the alpha signal was even there.
Today, the conversation has shifted. The models aren’t just part of the process—they’re steering it. AI is no longer experimental. It’s embedded, end-to-end.
Intelligent Automation: Lifting the Floor
Operational excellence has always been the backbone of competitive advantage in finance. But let’s be honest—most operational work is a grind. That’s where Intelligent Automation steps in and rewrites the rulebook. When you combine RPA with NLP and machine learning, you don’t just automate the task—you can start to rethink the task itself.
Otherwise, you find yourself promoting the practice of dumb optimization—solving the wrong problem faster, with more confidence, and at greater scale. Yeah for you.
Take invoice processing. What used to be a manual slog—chasing PDFs, cross-checking amounts, and keying into systems—can now be handled by bots that read varied formats and learn which exceptions to flag. And they’re not static scripts. They get smarter with every cycle.
But the real unlock is in compliance. AI-powered automation creates workflows that anticipate risk rather than react to it. Real-time transaction monitoring. Automated alerts. On-demand audit trails. These systems speed things up, reduce exposure, and boost confidence in the governance model. In an industry where a fat finger error can cost millions, that’s a shift from box-checking to strategic advantage.
The Human Factor
Let’s be clear: the goal isn’t to replace people—it’s to raise the ceiling on what they can do. When you automate the repetitive, you create space for human judgment, empathy, and creativity. That’s the hybrid workforce we’re building—a mix of AI-native tools and human insight working side by side.
Of course, this transformation isn’t without friction. Legacy systems don’t always play nice with new tech. Employees worry about being replaced. Integration takes real investment—in infrastructure, in culture, and most importantly, in people.
That’s why education and change management are non-negotiables. The firms that win won’t just install new tools. They’ll train their people, clarify their vision, and lead transparently.
Looking at Some Examples
AI in Portfolio Management: From Newsfeeds to Neural Nets
Let’s zoom in on the investment side of the house. Natural Language Processing (NLP) and Generative AI are retooling how we manage portfolios and build trading strategies.
Picture a portfolio manager trying to track geopolitical news, earnings transcripts, and analyst updates across dozens of positions. NLP lets AI systems process all that noise, extract the signals, and even assess sentiment in seconds.
That’s not just speed—it’s leverage.
And what about GenAI? Generative AI doesn’t invent in the traditional sense—it predicts, and it predicts exceptionally well. What makes it powerful isn’t raw creativity but its ability to synthesize vast amounts of information and surface patterns we’d otherwise miss. It uncovers relationships buried in noise, connects signals scattered across datasets, and distills what was always there—just hidden. We sometimes confuse this with creativity.
Generative AI and Agentic AI do not just represent smarter code; the architecture is more exploratory by design. For quants (read: data scientists), that’s a shift in role. We’re no longer just writing instructions—we’re co-creating with systems that learn and adapt alongside us.
It’s less code monkey, more conductor.
From Triage to Trust: AI in Post-Trade and Compliance
In post-trade, AI is quietly killing off one of finance’s most significant pain points: reconciliation. Instead of waiting for a break to be spotted, AI systems can now compare records, identify discrepancies, and suggest corrections—before a human even logs in.
This has a downstream effect on compliance. Real-time monitoring, automated alerts, audit-ready documentation—AI is turning compliance from a retrospective burden into a proactive shield.
Client Servicing: Where AI Meets Empathy
Client expectations are changing. They want personalized advice, real-time answers, and zero friction. AI can deliver on all three.
Robo-advisors are democratizing financial planning. Chatbots powered by NLP and LLMs are resolving client queries at scale. And virtual assistants are learning to understand nuance, context, and sentiment.
The human touch isn’t going away—it’s being redefined. Humans will own the high-empathy, high-complexity moments. AI will handle the rest.
The Rise of the AI-Native Workforce
We’ve all heard of digital natives. But what’s coming next are AI natives—a generation entering the workforce using tools like ChatGPT and Midjourney as second nature. These workers don’t just adapt to AI—they expect it.
The most innovative firms will lean into this shift. That means investing in upskilling, fostering a learning culture, and embedding AI literacy across roles. Everyone from coders to compliance officers will need a baseline fluency in how these systems work.
Stay on the Human Side of the Fence
We’re in the middle of a transformation—not just to new digital tools, but to a new way of thinking about work. AI is changing the pace, the structure, and the expectations of the financial services industry. But its full potential will only be realized when paired with human intuition, creativity, and leadership.
This is our moment to step forward—not just as operators but as translators between what AI can do and what our organizations need. The firms that thrive won’t just build more intelligent systems. They’ll create more innovative teams.
Thanks for reading—and if you were at the talk, thanks for the questions. Keep learning. Keep leading. And stay on the human side of the fence.
Disclaimer: All views are my own and do not reflect those of my employer. No confidential information is disclosed here.