The financial services industry is on the brink of a profound shift – not because of AI in general, but because of a new generation of AI agents that are set to redefine how banks and vendors operate, build, and compete.
Over the past year, we’ve seen the hype around generative AI settle into something more substantial: execution. AI is no longer just a powerful writing or summarizing tool. It’s becoming a workforce – intelligent, autonomous, and rapidly evolving.
We’re witnessing the rise of AI-first organisations, where agents aren’t just assistants, they’re builders, analysts, and decision-makers. And it’s already starting to reshape the finance sector.
The Shift Already Underway in Finance
Banking is ripe for AI agent disruption. It’s an industry driven by data, compliance, workflow-heavy processes, and customer expectations for speed and personalisation.
From underwriting to transaction monitoring, fraud detection to customer onboarding, AI agents can do more than assist – they can take action. The question is not if this will change financial services, but how soon.
The 5 Levels of AI Agent Evolution
Like any emerging technology, the development of AI agents follows an evolution. Each level brings new capabilities – and new implications for how banks build, staff, and scale.
Level 1: Generalist Chat
This is where most banks started. Generalist AI tools like ChatGPT helped automate knowledge retrieval, summarisation, and client communication. Useful? Yes. Game-changing? Not quite.
They were co-pilots – dependent on human input, without real understanding of the financial domain. These tools helped us understand AI’s potential, but quickly showed their limits in regulated, context-heavy environments.
Level 2: Subject-Matter Experts
Here, banks began integrating AI models trained on financial-specific data – compliance, legal, risk, even ESG. These were smarter co-pilots: AI that didn’t just respond but understood.
Vendors building vertical AI platforms started to outperform horizontal tools. Think of LLMs fine-tuned for insurance underwriting, or credit risk scoring – precise, reliable, and built for the realities of financial workflows.
Level 3: Agents (We Are Here)
This is the tipping point.
AI is moving from co-pilot to autopilot. Agents aren’t just generating insights – they’re executing tasks. Reviewing transactions for AML. Flagging exceptions in underwriting. Managing email queues. Completing KYC workflows.
In this phase, the value shifts from “what AI can suggest” to what it can do. Banks that embrace this shift will see exponential efficiency gains. Those that don’t? They’ll be outpaced by vendors moving faster, with fewer people.
Level 4: AI Agent Innovators
Soon, AI agents won’t just follow instructions – they’ll improve them. We’ll see the rise of creative, problem-solving agents that explore better paths to outcomes.
Imagine an AI team that doesn’t just manage loan origination, but optimises the process: reroutes bottlenecks, identifies friction, and proposes new strategies based on customer behaviour and real-time feedback.
For banks, this means moving from AI as a cost saver to AI as a growth engine.
But unlocking this stage requires one thing above all: trust. Trust in agent performance, auditability, and explainability – all non-negotiables in a regulated environment.
Level 5: AI-First Organisations
This is where things truly change.
AI-first organisations don’t just use agents – they run on them. From treasury management to investor relations, from customer support to real-time risk management, the organization becomes a network of intelligent systems, guided by a few strategic human operators.
In finance, we’re already seeing the early signs:
- AI-powered hedge funds running autonomous trading strategies
- Fully automated SMB lenders scaling without large teams
- Fraud engines retraining themselves in real time based on novel threat patterns
Eventually, we’ll see full-service financial platforms operated by AI agents across every vertical – a future where the balance of efficiency, compliance, and customer-centricity is orchestrated at machine scale.
Readiness is Everything
The shift is already underway – and for finance, the impact is profound.
A recent survey by the Bank of England revealed that 75% of financial firms are now utilizing AI, a significant increase from 53% just two years prior. Notably, over half of these applications involve some degree of automated decision-making, signalling a move beyond mere automation towards autonomous intelligence.
Goldman Sachs exemplifies this trend, having integrated AI tools across its operations. Their GS AI Assistant is currently aiding 10,000 employees, with plans to expand firm-wide by year-end. This integration has led to measurable productivity gains, including a 95% automation rate in drafting IPO prospectuses.
For institutions still anchored in co-pilot tools, the window to adapt is narrowing. The pace of agent evolution is accelerating, and those who move first will define the new standard.
Now is the time to ask:
- Which parts of your business can be reimagined with intelligent autonomy?
- What barriers – technical, cultural, or regulatory – are holding you back?
- Are you laying the groundwork for a future where explainability, trust, and control are built in by design?
You won’t just be competing with peer institutions or emerging vendors – you’ll be facing a new class of AI-native financial organisations that operate faster, leaner, and smarter.
The next generation of financial leaders will be those who build with agents, not just around them. The opportunity is here – and it favours the bold.
