• TECHNOLOGY
December 6, 2024
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Artificial intelligence (AI) is a hot topic, with countless industries exploring its potential to drive efficiency and productivity. While still early, AI now offers tangible opportunities for CFOs and finance professionals in growing companies, even if it hasn't yet made meaningful changes to day-to-day operations.
At Fintelos, we specialize in providing strategic finance guidance for growth-stage companies, and we’re eager to learn how AI can serve our clients. In this article, we’ll share what we’ve discovered so far about how AI is beginning to influence strategic finance and the office of the CFO.
Most early AI use cases target customer-facing functions — like sales and support — where AI’s ability to improve and automate language-driven processes has the most direct impact on revenue. While moving at a slower pace, AI’s application in "back-of-the-house" operations, particularly within finance, is becoming more apparent. Although early large language models (LLMs) often struggled with mathematical calculations, recent advancements in AI methodologies, like chain-of-thought prompting, are making AI better at managing complex quantitative tasks. Chain-of-thought prompting breaks down financial problems step-by-step, simulating human reasoning and enhancing AI’s ability to analyze and manipulate structured data.
In its current capacity, AI is an accelerator and a safeguard for finance teams, speeding up processes and improving accuracy — not a replacement for human expertise. Let’s explore some of the leading finance-related AI use cases emerging today.
Invoice management is a foundational finance and accounting task; traditionally, it’s been a manual, and sometimes error-prone, process. As an improvement to fully manual processes, data extraction tools like Nutrient optimize invoice processing by reading and extracting critical information — such as dates, addresses, and amounts — reducing or eliminating the need for manual input.
AI-centric platforms, like Kodexa, take this one step further, layering AI capabilities on top of extraction tools to enhance the understanding and analysis of loosely structured invoice data. While intentionally keeping a human in the loop, Kodexa’s technology speeds up accounts payable processes across new and existing vendors while reducing errors, helping finance teams operate more efficiently.
In the growth stage, one of a CFO’s principal roles is securing capital to fund internal investments. Innovative AI platforms like Capwave assist at various points in the fundraising process — reviewing and optimizing pitch decks to create compelling narratives for investors and generating customized investor lists based on specific company attributes, ensuring that CFOs reach the right stakeholders.
AI can be a valuable asset for CFOs managing the details of M&A processes. Tools like Seraf leverage AI to investigate internal company documentation and provide quick answers to questions (e.g., “What is our company EIN?”), removing the need to manually open and search numerous documents. Applied internally in the M&A context, this functionality can help sellers seamlessly respond to due diligence requests; applied externally, these tools can help buyers extract critical insights from files stored in a seller’s data room, shining a light on potential focus areas and leading buyers to ask the right questions.
High-quality data is the backbone of any finance operation. AI-powered tools can significantly improve data management. For example, with natural language queries, solutions like Querri allow finance professionals to ask questions in plain English about spreadsheets they upload to the tool. Querri interprets and processes the underlying data, providing clear, actionable insights — turning complex financial data into understandable, easy-to-access information.
With some knowledge about AI prompting and financial forecasting, finance professionals can use publicly available LLMs to accelerate the creation of financial models and budgets. CFOs can upload financial data (from QuickBooks, P&Ls, balance sheets, etc.) and use AI prompts to generate draft models or budgets. LLMs can also predict trends and assist in scenario planning, providing finance professionals with quick forecasts to inform strategic decisions. On this front, dedicated AI financial planning and analysis (FP&A) tools are emerging from new and established vendors, and we continue to learn and monitor. If you’ve integrated one of these tools into your workflow, we’d love to hear about your experience.
Before you open up ChatGPT and feed it any of your company data, remember that public AI systems may train their models on user inputs. Many tools allow users to opt out of providing training data — and for ChatGPT’s business products, organizations are opted out of data sharing by default — but chat history may still be stored for a limited period. Although user inputs aren’t the primary source of training data for these models, the fact that data is stored in the system raises some concerns about data privacy. Businesses working with sensitive or confidential financial information should review the data retention and privacy policies of AI tools before using them. In particular, avoid sharing client or customer data with AI platforms unless you fully understand and agree with their data-handling practices to mitigate compliance risks.
AI’s potential is significant and growing, and it’s important for CFOs to approach it strategically:
Fintelos can help. We partner with growth-focused software and professional services businesses to apply strategic finance playbooks that get you closer to your goals. Explore our capabilities, or reach out today to learn more.
