Artificial intelligence (AI) is no longer a futuristic concept; it's a daily headline. Large language models (LLMs) can generate an email, write code, and answer questions effortlessly. This wave of generative AI has captured the world’s imagination, but for a CFO, imagination isn't enough. When it comes to financial planning and analysis (FP&A), you don't need creativity; you need certainty.
The very thing that makes consumer-grade AI so impressive — its ability to make creative leaps and generate novel content — is what makes it a liability in the world of finance. These models are often probabilistic; they are designed to predict the most likely next word or idea based on vast datasets scraped from the public internet. This can lead to "hallucinations," where the AI presents beautifully written but factually incorrect information with complete confidence. For a finance team, a single hallucination can have disastrous consequences.
The problem with ‘probable’
The fundamental flaw of using probabilistic AI for financial analysis is that business decisions can't be based on a best guess. You wouldn't run your company on financials that were scraped from the internet and potentially based on another company, so why would you trust AI that operates on the same principle?
For business use cases, the answers from AI must be grounded in reality, not possibility.
This means AI outputs need to be deterministic, derived purely from your organizational data. Not from what's in the ether that LLMs use to generate probabilistic outcomes. This distinction is at the heart of what separates enterprise-grade AI from the tools capturing today's headlines.
The power of deterministic answers
Deterministic AI operates on a completely different principle. Instead of guessing based on public information, it calculates answers based on your private, secure business data. This provides several critical advantages for financial planning:
- It delivers verifiable certainty. A deterministic model provides a single, correct, and verifiable answer to a query. It's math, not prose.
- It minimizes hallucinations. Because it operates exclusively within your company's data, there is little to no risk of AI inventing facts or introducing external, irrelevant information.
- It provides answers you can act on. Leaders gain the confidence to take decisive action when they know the analysis is based on their business's unique reality.
- It handles complex, specific scenarios. It can answer precise questions like, "What is the financial impact on our long-range plan if we exceed our annual revenue target by 8%?" by incorporating your actual revenue and long-range plans.
This approach is the difference between asking an artist to paint a picture of your financials versus having a seasoned analyst run the numbers. The answer isn’t just a probable outcome; it’s a reliable forecast.
AI at the core, not just on the surface
As the AI hype cycle continues, many software providers are rushing to bolt on LLM capabilities as a thin layer over their existing products. This approach often fails to address the foundational need for computational power and data integrity. True business AI isn't a feature; it's part of the architecture.
This has been a part of Anaplan's DNA from the beginning. Unlike vendors bolting AI onto existing products, Anaplan is truly AI at the core. Our platform's calculation engine is built on linear algebra, a foundation that has been refined over many years. And notably, linear algebra is the basis for neural networks, which in turn is the basis for LLMs.
This means Anaplan's ability to perform complex calculations on your business at scale isn't a new AI-driven trick — it’s a core competency that has been refined for years. This foundation allows for the development of our intelligent role-based AI agents that don't just talk about your business; they understand it, delivering insights you can trust to run your business and plan its future.