Is artificial intelligence truly intelligent? Sometimes it struggles with elementary school math problems. Yet, on the other hand, it can recognize when to win a difficult chess game or generate graphics. How will technology impact the professions of accountant and analyst?
What is artificial intelligence (AI)?
Predicting machines, or more professionally, predictive algorithms. This is the name given to new AI technologies and their description in the book "Predicting Machine: The Simple Economics of Artificial Intelligence" (authors: Ajay Agrawal, Joshua Gans, Avi Goldfarb), which simply describes how we have evolved from common mathematical models into a technological revolution. And today we are talking about implementing generative AI.
AI, or rather a predictive algorithm, uses the data it possesses to provide us with information we lack. I ask if Orlen shares are worth buying. ChatGPT responds: " I can't provide individual investment recommendations, but I can present objective factors worth considering when deciding to buy Orlen (PKN Orlen) shares." The information I received is available online, likely scattered across many websites. In this case, chatGPT presented me with information based on publicly available data and experience from millions of user inquiries. By experience, I mean the feedback it received from people who asked similar questions before me. Artificial intelligence is a vast collection of data, based on which it performs tasks or predicts what information we are missing.
What tasks are financiers already performing with AI today?
Finance relies heavily on data, especially accounting and controlling. Many companies have already begun implementing AI tools to automate and streamline financial processes.
Financial data analysis
AI has changed the approach to data analysis and, consequently, the requirements for financial analysts. Just a few years ago, an analyst's job involved reviewing data in systems, arranging it logically, drawing conclusions, and preparing reports. Today, AI can perform these tasks. Artificial intelligence can quickly analyze vast data sets—sales reports, operating expenses, results from several companies or years. An example of a tool that performs well in controlling is Microsoft Power BI with the Copilot AI add-on. It can automatically generate financial summaries and answer questions like: "Why did the margin in Q2 decrease compared to Q1?"
Revenue and cost forecasting
AI not only analyzes historical data but can also predict future outcomes, taking into account seasonal factors, market changes, and demand dynamics. Predictive models support better budget planning and financial scenarios.
Automation of accounting and reporting
This isn't a new topic. I first heard about OCR (Optical Character Recognition) in 2004 while working at IBM BTO. One of the first shared services in Krakow handled the accounting of companies like Unilever and Coats. Thousands of invoices landed on our desks, then on the scanner, and then in the accounting system. Today, OCR is a given; in addition, a good program will record invoices based on the template, recognize VAT, and finally prepare reports and declarations. The accountant's role is reduced to control and analysis. Artificial intelligence will replace people performing simple accounting tasks, but it won't take responsibility for the accuracy of settlements.
Risk assessment and credit analysis
Organizations, not just in the financial sector, using AI can instantly analyze a customer's creditworthiness, payment history, and capital affiliations. The models evaluate not only financial data but also behavioral and industry-specific data.
What AI Can't Do Yet—and Why It Matters
Artificial intelligence can analyze data faster than humans, but it still struggles to understand the context of a changing business reality. It doesn't make decisions based on intuition, experience, or interpersonal relationships—though these often play a significant role in the work of CFOs. AI lacks emotional intelligence, so it can't read tensions within a team, assess the credibility of an interlocutor, or build trust. It also can't handle ambiguous tax situations that require interpretation of regulations, not just their application. A machine won't ask "why?" when the numbers are correct but their meaning is questionable. Humans give meaning to data—AI merely organizes them.
AI as a tool, not a threat: the new role of the corporate finance professional
According to the report "The State of AI in Finance 2025" 85% of US CFOs see AI's potential in financial planning, but only 39% of teams have implemented actual solutions. Why? Organizations lack the skills to implement and use AI-based tools. Employees fear job losses, and therefore their motivation for change is low.
The situation is completely different in Europe. According to the report Europe's Race to
According to BCG's Tech Readiness Survey, France signals greater digital ambition by 2026, with 28% of top executives planning to allocate 30–50% of their total budget to technology. By comparison, in Germany, only 18% declare this level of investment, and 46% allocate less than 20% of their budget to this purpose.
AI won't replace the emotional intelligence of an expert who builds trust within a team, translates complex data, and prepares leaders for critical decisions. In practice, this means that the role of a finance professional is evolving—not as an automator, but as an advisor who can base their recommendations on analysis, intuition, and experience.
How to prepare your finance department for transformation?
Preparing finance for the changes associated with implementing AI tools requires a strategic look at current ways of working and identifying where AI can add the greatest value. Success involves moving from gut-based decisions to management fully supported by reliable data—this requires investing in data organization. The team must acquire new skills: from analytics, through practical AI use, to critical thinking that truly informs business decisions. Management faces the challenge of creating a coherent strategy that combines the capabilities of technology with the talents and experience of employees. Transforming the finance function from an administrative hub into a strategic business partner—a team that not only responds to change but co-creates and drives it. True transformation always begins with a team that understands the possibilities of new technologies and is ready to leverage them.
Summary
Artificial intelligence in finance is no longer a futuristic vision, but a tool that can significantly accelerate analysis, streamline reporting, and improve forecast accuracy. However, it won't replace experience, intuition, and the ability to build relationships—elements that give data context and meaning. In the coming years, the winners will be those organizations that combine AI capabilities with the competencies of their teams, transforming finance departments into strategic partners. This requires courage, investment in people, and a willingness to shift the role of finance from a process executor to an advisor who connects the world of numbers with the reality of business.
