It seems like every tech headline in 2025 has one thing in common: AI agents.
From boardrooms to coffee shops, everyone’s talking about how this year belongs to AI agents that go beyond chat – they act. And while large language models (LLMs) dominated the last few years with their ability to generate endless streams of text, we’re now seeing a new shift.
Enter LAMs – Large Action Models – the doers of the AI world.
This isn’t just a name change for the sake of hype. It’s a signal of how AI is stepping up. Where LLMs excelled at holding a conversation, brainstorming ideas, and answering questions, LAMs are designed to take the next logical step: executing tasks, solving problems, and making things happen.
Why the Hype About 2025?
LLMs were revolutionary in their own right. They made it possible to extract information, generate content, and provide insights with an almost human-like fluency. But let’s be honest—they were still passive tools.
They talked; you acted. That’s great for creativity, but not enough for workflows that demand precision and execution – think financial analysis, invoice reconciliation, or month – end close.
In 2025, the conversation is no longer just about generating answers. It’s about taking action. Companies are tired of juggling multiple tools and manually bridging the gaps between insights and implementation.
That’s where AI agents step in.
What Sets LAMs Apart?
LAMs aren’t just another chatbot rebranded as an AI agent. They’re a true evolution in how AI integrates into workflows. Imagine an AI that doesn’t just tell you your quarterly revenue but also consolidates financial reports, flags anomalies, and even sends the final draft to your stakeholders – without you lifting a finger. That’s the power of action-oriented AI.
Here’s what makes this different:
1. Task Execution:
Need to allocate expenses across departments? LAMs don’t just guide you through it; they do it for you, ensuring accuracy every time.
2. Seamless Integration:
They connect to your existing finance software, ERPs, and reporting tools, acting as an extension of your team.
3. Proactivity:
Instead of waiting for you to ask a question, LAMs identify potential issues, like duplicate invoices or unusual spending patterns, and take steps to resolve them.
4. Time-Saving Automation:
From routine tasks like generating reports to more complex operations like compliance checks, LAMs don’t just assist; they complete tasks end-to-end.
Why Finance Teams Need LAMs?
Finance and accounting are fields where precision is non-negotiable. When LLMs emerged, they were helpful for generating insights, but they left too much room for manual follow-up. LAMs bridge this gap.
They combine the conversational strengths of LLMs with the ability to act, making them perfect for:
1. Audit Preparation:
Consolidate and verify documentation with minimal human intervention.
2. Forecasting:
Not only building financial projections but also running “what-if” scenarios in real-time.
3. Compliance:
Automatically checking transactions against regulatory requirements.
The Bigger Picture
AI isn’t just a trend—it’s becoming an indispensable tool for businesses that want to work smarter, not harder. With the rise of LAMs, we’re witnessing a shift from reactive AI that requires constant input to proactive AI that delivers results.
For finance teams, this shift is game-changing. Instead of spending hours on repetitive, manual tasks, professionals can now focus on strategy, decision-making, and driving growth.
LAMs aren’t here to replace accountants and finance experts; they’re here to empower them.
Final Thoughts
2025 is shaping up to be the year of doing. With tools like these leading the charge, we’re moving into a future where AI doesn’t just support your work—it shares the workload.
So let’s leave the era of just talking behind and embrace the age of action. LLMs laid the foundation, but LAMs are here to build the future. And for finance teams, that future is already looking brighter.
