In an era where artificial intelligence (AI) is changing the way we work, the question arises: What does AI mean for the economics profession? An increasingly important topic is artificial intelligence and economists, given the strong impacts of this technology. Is this new technology a threat to jobs, or a powerful tool that will help financial professionals do their jobs better? Below, we will examine how AI is impacting the work of economists and accountants, what the main opportunities and risks are, and what practical steps can be taken to adapt to this change. We will also connect this discussion to the concepts of Jim Collins on the advantages of technology in business, to understand whether AI is an enemy or an ally for finance professionals.

What is AI and how does it work?

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Artificial Intelligence is a field of technology that enables computers to perform tasks that typically require human intelligence. These tasks include learning from data, recognizing patterns, making decisions, and even generating text or analyses. In simple terms, AI is like a very fast and intelligent digital assistant: it can process large amounts of information in seconds and draw conclusions or predictions that would take a human hours or days.

An AI program can be trained with millions of financial data points to learn how markets move. Then, it can predict future movements or suggest investments based on those patterns. Unlike traditional programs that only follow predetermined rules, AI learns on its own from outcomes: the more data it analyzes, the more accurate it becomes at predictions.

It's important to understand that AI is not magic or some conscious being – it's simply advanced software. It works thanks to mathematical algorithms and computing power, which enable it to find correlations in data and offer solutions. In fact, AI has already become part of our daily lives: from the apps on our phones to automatic recommendations on websites.

Why does AI matter to economists?

Economists, accountants, and finance professionals are constantly dealing with data, analysis, and decision-making. AI is of particular importance to them because it can ease the burden of routine tasks and help them focus on the more complex aspects of their work. That's why AI is seen as a very important factor and actor in the financial field:

Fast data processing

AI can analyze thousands of pages of figures, reports, or invoices in seconds. This means that tasks such as daily record-keeping, account reconciliation, or invoice verification can be easily automated. As a result, economists gain valuable time that they can devote elsewhere.

Better predictions

With advanced machine learning algorithms, AI can predict financial or economic trends with greater accuracy based on historical patterns. For example, forecasting cash flows or seasonal sales becomes more reliable when AI models that take hundreds of factors into account are used.

Informed decision-making

By analyzing data, AI can help financial managers understand the consequences of various decisions. For example, an AI-equipped Chief Financial Officer (CFO) can test how the company would be affected by changes in exchange rates, raw material prices, etc., and make more informed strategic decisions.

Reduction of human errors

Manual processes (e.g., manually recording financial transactions) are often accompanied by errors or discrepancies. AI-driven automation reduces this risk, as the system can automatically detect anomalies or incorrect calculations. This increases the accuracy of financial reports and lowers the likelihood of costly errors.

Essentially, the main opportunity that AI brings is an increase in the productivity and value that economists deliver. By delegating tedious tasks to machines, finance professionals can focus on deeper analysis, strategic advice, and generating insights for businesses.

Some practical examples of using AI in finance

AI is no longer just theory – it's already in action in the financial sector. Many firms, large and small, are integrating artificial intelligence into their workflows. Here are some concrete practices where AI is being used today:

Audit and financial control

Large auditing firms have begun using AI for automatic document review. For example, Deloitte has developed an internal platform that analyzes contracts and financial documents using AI., automatically highlighting the key information that auditors need to verify. Also, EY (Ernst & Young) They have integrated AI into the auditing process – their intelligent system scans unstructured data, such as contracts or invoices, and flags potential risks of fraud or financial misstatement.

Accounting automation

For smaller businesses, there are now AI-powered accounting software programs that serve as “accounting assistants.” These programs can scan invoices (using Optical Character Recognition and AI), convert them into structured data and automatically record them in the financial system. Tasks such as processing purchase invoices, recording daily expenses, or reconciling bank accounts are becoming increasingly automated, saving time and reducing errors.

Risk analysis and fraud detection

Banks and financial institutions use AI algorithms to detect suspicious transactions or patterns that indicate fraud. AI can monitor thousands of transactions per minute and automatically flag anything that appears out of the ordinary (e.g., a transaction of an unusual value or in an unusual location for the customer). This greatly helps prevent financial fraud and money laundering.

Virtual assistants and customer service

Many banks and investment firms have implemented AI-powered chatbots to answer customer questions. These virtual assistants can provide basic information about balances, transactions, and even initial investment advice, 24 hours a day. This allows economists and financial advisors to focus on more complex issues while the AI handles routine questions.

Improving internal efficiency

Leading companies in the financial sector are also using AI for internal processes. A example It is PwC, which has equipped its employees with a customized version of ChatGPT to assist them with tasks such as document drafting and coding. The result was a 20% to 50% increase in productivity in some software engineering processes. This shows that when used properly, AI can significantly accelerate the pace of work in many aspects.

Although many of these practices are initially adopted by large companies (such as the “Big 4” in auditing), it's worth noting that AI isn't just for giants. Today, powerful tools and platforms exist (some even free or low-cost) that an accounting office or a small business can use. A significant portion of financial professionals are simply using publicly available open tools like ChatGPT for their daily needs, alongside industry-specific tools. This means the barriers to entry have lowered – anyone can experiment with AI in their field without massive investments.

The risks and challenges of AI for economists

As with any new technology, alongside opportunities, AI also brings risks and challenges that need to be carefully managed. Here are some of the main issues that raise questions:

Fear of job replacement

The question that often arises is whether AI will make economists, accountants, or financiers redundant. This fear is not without precedent—decades ago, there were similar concerns when personal computers and Excel were introduced. In fact, history shows us that such technologies initially replaced some roles but created new roles and increased demand for higher-level skills. For example, after the proliferation of Excel, the number of people employed as data processors decreased, but the number of accountants, auditors, and financial analysts increased significantly by 2000. This indicates that AI is expected to transform the role, not eliminate it entirely. Nevertheless, the fear remains a real psychological challenge and must be addressed.

The loss of some traditional duties

We cannot deny that some routine tasks that were performed by junior economists or support staff until yesterday can now be performed by AI. For example, the initial preparation of financial statements, standard reports, or basic expense checks can be automated. This could reduce the need for entry-level employees for these tasks. The challenge for the profession is to redefine the value that economists bring: the focus will shift to qualitative analysis, data interpretation, and strategic decision-making, things that AI alone does not do well.

The risk of errors

The expression “garbage in, garbage out” applies greatly to AI. If the data used to train a system is inaccurate or biased, the results will also be incorrect or skewed. An AI model can make interpretation errors if, for example, the data is missing specific cases (e.g., an unforeseen economic crisis). Similarly, algorithms can inherit incorrect assessments from historical data – for instance, they might underestimate women in financial leadership roles if historical data contains few women, etc. These errors can lead to wrong decisions if there is no human context to correct them. Therefore, human oversight and intervention remain essential.

Ethical issues and privacy

The use of AI in finance also raises ethical questions. It must be ensured that decisions made by AI (e.g., to grant a loan to a client or to recommend an investment) are fair and transparent. There is a risk that even users themselves may not fully understand the reasoning of a complex AI model. Furthermore, the handling of large amounts of financial data raises concerns about confidentiality – care must be taken to comply with privacy regulations and protect sensitive data.

Non-compliance with legal changes

In the financial and fiscal sectors, laws and regulations change often. One challenge is teaching AI with rapid legal changes. If an AI model is trained on old rules, it may provide recommendations that are not in compliance with the new law. This requires continuous maintenance of the AI system and expert intervention to update it with the latest legal information.

It's clear that AI doesn't come without risks, but most of them can be mitigated with the right steps. One of those steps is education – both of AI systems themselves with quality data, and of human professionals on how to use AI and its limitations. This brings us to the next question: Should we be afraid of AI, or see it as something temporary?

Will AI replace economists? (Should we be afraid?)

Fear of the unknown is human, and AI is, to some extent, an unknown territory for many professionals. However, facts and experts suggest that AI will not completely replace the economist but will change the way they work. Here are some reasons why panic may be excessive:

AI is a tool, not a replacement for human reasoning.

Even the most intelligent artificial systems operate within defined limits. They lack human judgment, creativity, or contextual understanding like an experienced professional. As stated earlier in the article, AI can analyze data and provide recommendations, but only humans can fully grasp the overall framework, cultural nuances, political or emotional influences in economics. A good economist brings intuition and experience – elements that are not easily coded into an algorithm.

History of technologies in finance

Many times in the past, the “elimination” of a profession by technology has been predicted, and often the opposite happens. The example of ATMs is illustrative: when ATMs were invented, it was said that they would eliminate the role of bank tellers. In reality, ATMs lowered the cost of opening bank branches, banks opened more branches, and hired even more tellers than before (but with slightly different duties). The same is expected with AI: there will be a shift in duties, but not a complete disappearance of the role. Perhaps we will have fewer accountants shuffling papers, but we will have more analysts, financial advisors, and fintech experts.

AI as an assistant, not a competitor

A good way to eliminate fear is to see AI as an ally. The combination of humans and machines yields better results than humans alone or machines alone. As emphasized, the question is not whether the computer is more accurate than the human, but whether the human, aided by the computer, is more accurate than the human alone – the answer is yes. For example, an economist with a tool like AI at their disposal will avoid calculation errors, have more complete information, and thus provide a much higher quality service than someone without these tools.

Professionals' attitude toward automation

One Global survey It has been discovered that 89% of employees say that automation (including AI) has made their work easier, and 91% of them admit that it saves them time and gives them a better work-life balance. So, the majority of those already working with automated tools don't want to go back. This shows that once they've experienced the benefits, professionals no longer view AI with fear but with confidence that it makes them more productive and their work more interesting.

Instead of thinking, “AI will replace us,” a more helpful approach is: “How can we use AI to replace the tedious parts of our jobs?” Because, as it's become a meme in professional circles, “AI will not replace economists, but economists who use AI will replace those who don't.”In other words, the greatest risk isn't that you'll be replaced by a machine, but that you might be “replaced” by a colleague or competitor who has embraced technology and is offering more efficient services.

Is AI something entirely new or just the next change?

Economists are accustomed to rapid changes, especially in legislation and regulations. Every year there are new tax laws, new reporting standards, new accounting rules, and so on. Often, economists have to learn and adapt their practices overnight to comply with a new law. Compared to this reality, is AI a bigger revolution, or just another change, albeit a technological one?

What is it?

It can be argued that AI represents a more fundamental shift, as it is not simply a new rule to be applied but an entirely new way of doing work. Instead of the economist manually changing their own procedures, with AI they must learn a new tool, a new work partner. It is more or less like the transition from manual calculation to using a computer and Excel decades ago – a huge change.

However, at the same time, the basic principles of the profession remain the same. The goal of an economist's work does not change: providing accurate financial information and advising on the best possible economic decisions. Professional and ethical standards do not change – integrity, diligence, and critical analysis are the same.

In this sense, AI can be seen as another step in the evolution of the tools economists use, comparable to: electronic calculators, accounting software, cloud-based financial software, etc.

Why does it matter?

What makes AI perhaps more challenging than rapid legal changes is its speed and scale. New laws emerge one by one; AI is developing in many directions simultaneously and exponentially. Therefore, the learning curve for professionals can be steeper. Many new concepts need to be grasped (e.g., what is machine learning, what is deep learning, so, how does a language model like ChatGPT, etc., work).

However, a good approach is to build upon existing skills. Just as when a new law is passed, a good economist reads it, studies it, and incorporates it into practice, so too with AI: first, a basic understanding of the technology must be created, then tested in practice in daily tasks.

In other words, the flexibility and tendency to adapt that finance professionals have already gained from dealing with legal changes is also the main weapon for this technological change.

AI is a bigger change than just a new law, but not something extraordinary that the world has never seen before. It is part of the long technological evolution in finance. Those who have survived and thrived professionally - moving from ledgers to computers, from national standards to international standards, from paper tax returns to online declarations - have every ability needed to survive and thrive in the age of AI as well.

How Economists and Businesses Can Adapt to AI – Practical Tips

To successfully embrace AI, economists and businesses must take proactive steps. Here are some practical tips for integrating AI into daily work and developing the right skills:

Start with small steps (test)

There's no need to transform all your processes immediately. Identify a routine task that takes up a lot of your time – for example, processing monthly invoices – and explore an AI tool that can do that job. Try it out for a short period as a pilot. This will give you a practical idea of the benefits without taking too much risk.

Invest in training and education

Just as you take courses for legal changes or professional certifications, take time to learn the basics of AI. There are plenty of free online courses on “AI for beginners” or specific training on using tools like Excel with automated formulas., Business Intelligence with AI features, etc. The more informed you are, the more confidently you'll use the technology.

Improve the quality of your data

AI feeds on data. Ensure that the financial data you work with (e.g., accounting records, customer database, etc.) is clean and well-organized. Avoid duplicates, correct errors, and standardize formats. This “data hygiene” will make any AI tool produce much more reliable results. Remember: bad data in, bad results out.

Don't disregard professional judgment.

Even when you start using AI regularly, always review the results critically. Consider AI your consultant, not your director. If an AI-generated analysis seems strange or counterintuitive to you, investigate it further. Combining your experience with the speed of AI will be the best recipe.

Collaborate with IT departments or external experts.

The development and maintenance of AI solutions may require technical expertise. Do not hesitate to seek help from IT specialists within your organization or external consultants. They can assist you in choosing the right tool, integrating it with existing systems, and training staff for its optimal use.

Be careful with security and privacy.

When using AI tools, especially cloud-based or third-party ones, consider the security of the financial data you are providing. Read the privacy terms; ensure confidential information (e.g., payroll, business plans) is handled according to regulations. If possible, use “enterprise” or licensed versions that offer more control over data than free public versions.

Create an ethical approach to AI

As a financial professional, maintain ethical principles even when using AI. Be transparent with clients or management if a recommendation is influenced by analysis from an AI model. In critical decision-making, use AI as a second opinion, but do not let it replace your professional judgment.

By following these steps, economists and businesses can gradually benefit from AI, without disruption and with control. The right approach is to be proactive: AI is here to stay, so it's better to start getting to know it and put it to work for yourself, rather than ignoring it until it becomes indispensable.

Technology as an Advantage: What Jim Collins Teaches Us

In his books and studies on successful companies, Jim Collins (a well-known author of “From good to great”) has a very significant observation about the role of technology. He notes that companies that excel do not see technology as an end in itself, but as an accelerator of their goals. They already have them clear.. In other words, technology is an “accelerant”: if an organization has the right people, the right culture, and the right strategy, then technology (whether AI or something else) will accelerate its success. But if these foundations are missing, technology alone cannot make a business great.

Technology as an instrument

How does this relate to economists and AI? According to the Collins principle, a financial consulting firm or an independent professional must first clarify what they excel at, what unique value they offer clients, and ensure they operate with discipline and integrity. Once these things are in place, AI can serve as an additional competitive advantage – it enhances your capabilities, multiplies the effect of your efforts, and increases the speed and scope of your services. But AI does not replace vision or strategy. A business economy without a clear vision can waste money on expensive AI technology and still not achieve results because it doesn't know what to do with it.

Jim Collins also found that successful leaders were curious yet cautious with technology. They don't jump on every new trend just because it seems interesting; they evaluate if that trend (e.g., implementing AI) aligns with their business model and serves their customers. This is a valuable lesson: AI implementation must be strategic. Key questions any economist or business should ask are: What specific problems do I want to solve with AI? How will it improve my customer service? Do I have the capacity to maintain it? By answering these, technology takes the right direction.

So, Collins' message in our context is: use AI as a tool to achieve your goals better, not as a substitute for goals. Technology should serve humans and their vision, not the other way around. An economist who understands this has no reason to fear AI; on the contrary, they will turn it into a competitive advantage against those who fall behind.

Conclusion

Artificial intelligence is bringing significant changes to the economics profession, just as it is in every other field. Like any major change, it comes with extraordinary opportunities, but also with challenges to overcome. The good news is that the role of the economist is not doomed to extinction; it is destined to evolve. AI will take over repetitive, routine tasks, but this will only give the modern economist more room for value creation – whether in in-depth analysis, strategic consulting, or client communication.

What does history teach us

The key is to adapt and adjust: those who embrace technology and invest in their skills will find AI a powerful ally. Those who remain passive risk being left behind in a rapidly advancing industry. But there's no need for panic – history teaches us that humans have coexisted with and benefited from new technologies whenever they've been willing to learn and use them wisely.

To illustrate, we can use the analogy mentioned earlier: when Galileo used the telescope, he didn't replace the work of the astronomer – on the contrary, he enabled them to see further and understand more. AI is the telescope of the modern economist. By using this “tool” to extend our vision towards data details and future predictions, we can make more informed, faster, and smarter decisions. What's important is to use it carefully, ethically, and with good intentions.

Jim Collins

To conclude, let's return to Jim Collins' idea: technology, including AI, can be your accelerating force towards success – as long as you put it in service of your goals and don't let it deviate you from them. AI is neither good nor bad in itself; it all depends on how we use it. By being informed, open to change, and at the same time faithful to the basic principles of our profession, we can turn this technological revolution into a benefit for both ourselves and customers and the businesses we advise.

What has changed from September 2025 to today

AI models like Claude, ChatGPT, and Gemini have made great strides in analyzing financial documents and automatic reporting. Today, an economist can upload a financial statement and receive structured analysis within seconds.

Accounting tools like QuickBooks and Xero have integrated AI functionalities directly into their interfaces, automating transaction categorization and bank reconciliation without manual intervention.
The debate “AI replaces or helps” has taken a clear direction: firms that have adopted AI are reporting not job losses, but the reallocation of economists' time towards strategic consulting.