Generative AI’s impressive abilities
Generative AI has become a buzzword in nearly every industry, and for good reason. These models can write compelling articles, analyse data, and even generate marketing visuals in seconds. In financial services, they’ve already started to streamline communication and boost productivity.
But here’s the catch: while generative AI is brilliant at producing content and identifying patterns, it can’t take action. It’s like having a super-intelligent colleague who can explain everything to you, but can’t actually do anything without you telling them step by step.
This limitation is what we call the glass ceiling of generative AI.
The ceiling: where generative AI falls short
Let’s explore what generative AI models do well – and why they’re still stuck behind that invisible barrier.
What they’re great at:
✅ Creating text, images, or code from prompts
✅ Recognising patterns in vast datasets
✅ Delivering coherent, human-like responses
Where they struggle:
🔒 They can’t independently verify if their answers are correct
🔒 They lack long-term memory – they only remember the current conversation
🔒 Most importantly, they can’t take actions in the real world on their own
In a world where clients demand seamless experiences and instant resolutions, this limitation matters.
From content to action: the missing piece
Imagine this in a financial advice setting.
You ask a generative AI model for market insights. It can summarise the data beautifully, but it can’t go further. It can’t make a decision, like recommending a portfolio change, or execute a transaction, like moving funds or updating a risk profile.
In essence, generative AI is a phenomenal content creator but not an action taker.
Examples of limitations in financial services
Let’s look at what this means for financial services professionals:
🔹 Compliance – A generative model can explain AML regulations in plain English, but it can’t review transactions or trigger alerts.
🔹 Onboarding – It can produce onboarding guides, but it can’t validate client documents or complete the process.
🔹 Customer queries – It can generate answers to FAQs, but it can’t take the next step of resolving the request or escalating a complex case.
That’s the glass ceiling in action.
How AI agents break through
Enter AI agents. They build on the conversational power of generative AI but add the missing piece: action.
Here’s what they bring to the table:
- 🧠 Goal-oriented reasoning – They weigh options and make decisions, not just produce content.
- ⚙️ Dynamic adaptability – They learn from results and adjust their actions.
- 🤖 Execution power – They interact with other systems to complete tasks.
Think of the difference like this:
- Generative AI: “Here’s a report summarising these accounts.”
- AI agent: “I’ve identified these risky transactions, notified compliance, and updated the customer profile.”
Key takeaways for financial firms
The leap from generative AI to AI agents isn’t just a technical shift – it’s a strategic one. Here’s what it means:
✅ Boosted productivity – AI agents can tackle repetitive tasks, freeing up your team’s time.
✅ Better customer experiences – They can handle routine queries and adapt to more complex situations.
✅ Stronger compliance – They can flag suspicious activity in real time and execute the next steps without missing a beat.
Importantly, they don’t replace human judgement. Instead, they complement it – acting as tireless colleagues who handle the admin, so you can focus on what matters most: building relationships and crafting great advice.
Moving forward: embracing the change
The white paper from Multiply puts it well: the future of financial services isn’t about smarter conversations alone – it’s about smarter actions.
As the sector becomes more complex, clients want quick answers and quick results. AI agents deliver this, helping you serve more clients, reduce risk, and stay ahead in an increasingly competitive market.
So, ask yourself:
- Where in your workflow are you stuck in “read-only” mode?
- Which processes need more than just answers – they need action?
Starting small – testing AI agents in a specific workflow – can unlock huge benefits. And the best part? You stay in control, shaping how these agents work for you and your clients.
Conclusion: Beyond the ceiling
Generative AI has changed the game, but the ceiling is real. AI agents break through it, turning talk into action.
As financial professionals, we stand at the edge of this next wave. Those who embrace the potential of AI agents won’t just keep up – they’ll lead.
Are you ready to break through the ceiling? 🚀✨
🚀 Want to explore this in more detail?
Download the full white paper to get the complete view – packed with insights and practical guidance for financial professionals.
