Controlling in the age of AI: why Excel alone is no longer enough and what to learn next

AI is changing the way companies work with data, plan for the future and make financial decisions. Does this mean that controlling or financial management is losing its importance? Quite the opposite.

The role of the controller is gradually changing. A professional who once spent a large part of their time preparing spreadsheets and reports is becoming a business partner who can interpret data, identify connections and help companies make better decisions.

The future of finance will not belong only to those who know Excel. It will belong to people who can combine finance, data, technology and strategic thinking.

What does a controller actually do and why is the role changing?

Controlling is not only about checking numbers or creating tables. Its main purpose is to help companies plan better, manage costs and make more informed decisions.

A controller is responsible for areas such as:

• planning and preparing budgets,
• monitoring actual results,
• analysing differences between plans and reality,
• evaluating financial indicators,
• preparing information for company management.

Modern financial controlling, however, does not end with the question: “What happened?” Increasingly, it also looks for answers to:

• Why did it happen?
• What could happen next?
• Which decision would be the best for the company?

This is where AI in financial management creates new opportunities. Technologies can process large amounts of data quickly, but they still need a person who understands the context and can interpret the results correctly.

According to the IMA and Deloitte research on the future of controllership, AI and emerging technologies are transforming the role of controllership. The importance of technological skills, data analytics, risk management and the ability to use data for strategic decisions is increasing.

Excel in finance is not disappearing. It is simply no longer enough on its own

Excel is not outdated and still plays an important role in finance. It remains useful for analysis, calculations, financial models and everyday work with data.

The challenge appears when companies need to work with larger amounts of data, automate repetitive processes and create more accurate forecasts.

Modern financial management therefore combines Excel with other tools, such as:

• business intelligence solutions,
• reporting automation,
• data analytics,
• predictive models,
• data visualisation.

One example is Microsoft Power BI, which allows users to connect data from different sources, create clear dashboards and gain valuable insights for decision-making.

Excel is not disappearing. Its role is simply changing. It remains an important foundation, but a modern controller needs to work with a wider range of technologies as well.

Where AI in financial management is already helping today

AI in financial management is no longer only a topic for the future. Companies are already using it to automate routine activities, analyse data and prepare information for decision-making.

However, it is important to understand AI as a tool, not a replacement for financial expertise.

Automating reporting: less manual work, more time for analysis

One of the areas where AI and automation bring the biggest benefits is reporting.

Controllers no longer need to spend as much time manually copying data between spreadsheets or preparing repetitive reports. Automated processes can speed up reporting and reduce routine tasks.

The result is not a less important role for controllers. On the contrary. They have more time to focus on what matters most: explaining what the numbers mean and how companies can use them.

Predictive models: moving from looking at the past to planning the future

Traditional reporting often answers the question of what has already happened. Modern financial management increasingly focuses on future development as well.

Using predictive models and forecasting, companies can better estimate:

• revenue development,
• future costs,
• cash flow,
• possible business scenarios.

However, a forecast itself is not a decision. A good model does not automatically lead to a good conclusion.

Controllers need to understand data quality, business operations and the wider impact of individual decisions.

When data highlights potential problems

AI can analyse large amounts of financial data and identify, for example:

• unusual transactions,
• unexpected changes,
• deviations from normal patterns.

This does not mean technology can decide on its own whether something is an error or an important business change.

People still need to understand the context and evaluate situations from a broader perspective.

Turning numbers into decisions

One of the key responsibilities of a controller is transforming data into information that management can understand and use.

For example:

• What happens if costs increase by 10%?
• How would lower demand affect company results?
• Where is there potential for savings?

AI can help prepare these scenarios faster. However, the controller remains the person who explains their meaning and helps identify the best course of action.

The controller of the future will do more than just work with numbers

The biggest change in controlling is not only technological. The role of the financial professional itself is also evolving.

The controller of the future will combine several areas:

• financial expertise,
• data skills,
• analytical thinking,
• the ability to communicate results,
• understanding of how businesses operate.

A controller is becoming more than someone who prepares reports. They are increasingly becoming a business partner for management who helps explain the impact of decisions and identify the best possible solutions.

According to ACCA, AI can help finance professionals move further towards interpreting results, strategic decision-making and solving complex business challenges. Technology is therefore not reducing the importance of finance, but expanding the possibilities of professionals who understand how to use it.

What should you learn next if you are interested in controlling?

If you are interested in controlling, financial management or working with data, focusing on a single tool is not enough. Future finance professionals will need a combination of economic knowledge, analytical skills and technological literacy.

Financial and management accounting

A strong understanding of finance remains the foundation of a good controller.

It is important to understand:

• accounting principles,
• costs,
• financial statements,
• the relationship between numbers and business performance.

Without this foundation, it is difficult to correctly interpret the results generated by any analytical tool.

Financial analysis, KPIs and budgeting

It is about evaluating company performance and identifying the reasons behind changes.

Key areas include:

• financial analysis,
• setting and evaluating KPIs,
• budgeting,
• variance analysis.

Modern controlling is not only about monitoring the past

Advanced Excel, Power Query and Power BI

Excel remains an important tool, but modern controllers should also understand automation and data visualisation.

Useful skills include the ability to:

• process larger amounts of data,
• automate repetitive tasks,
• create clear and meaningful reports.

Basics of data analytics, SQL and statistics

Data is becoming an increasingly important part of financial decision-making.

Future controllers do not need to become programmers, but they should understand the basics of:

• working with databases,
• SQL,
• statistical thinking,
• interpreting data.

According to the World Economic Forum Future of Jobs Report 2025, skills such as AI, big data, analytical thinking and lifelong learning are among the most important abilities shaping the future of work.

AI literacy: knowing how to use and evaluate AI

Working with AI is not only about knowing how to write a prompt.

Finance professionals also need to understand:

• how to create effective instructions,
• how to verify outputs,
• how to identify errors or inaccurate information,
• how to work with data security.

Generative AI can produce inaccurate answers or so-called hallucinations. That is why human oversight and responsibility for results remain essential.

Communicating results to management

Numbers alone are not enough. They become valuable when someone can turn them into a clear conclusion.

A controller needs to explain:

• what has changed,
• why it has changed,
• what impact it may have,
• what decision makes sense.

Why AI will not replace a good controller

The idea that AI will simply replace finance professionals is an oversimplification.
Technology can process data quickly, but it cannot fully understand:

• the specific context of a company,
• long-term relationships and strategy,
• the consequences of decisions,
• ethical and practical considerations.

Good financial decisions are not created only through calculations. They come from combining data, experience and the ability to evaluate situations correctly.

How STING prepares students for the future of finance

Studying finance today means much more than working with accounting tables. Modern financial professionals need to understand numbers, data and how analysis supports business decisions.

At STING, students in the Management Accounting and Controlling specialisation learn about areas such as:

• fundamentals of controlling,
• controlling applications,
• financial analysis,
• management accounting,
• practical use of financial data.

An important part of the programme is connecting theory with real-world practice.

Frequently asked questions about AI, controlling and the future of finance careers

What is controlling and what is it used for?

Controlling helps companies plan, monitor results, analyse deviations and make better financial decisions. A controller connects data with practical recommendations for company management.

How is AI changing financial management?

AI helps with reporting automation, data analysis, forecasting and identifying unusual patterns. However, it does not replace human judgement and understanding of business context.

Will AI replace controllers?

AI will not eliminate controllers, but it will change the nature of their work. Routine activities can become more automated, while the importance of interpretation, strategy and decision-making will grow.

Why is Excel alone no longer enough in finance?

Excel remains an important tool. However, it is not sufficient on its own for working with large amounts of data, automation and modern analytical methods.

What does a future controller need to learn?

A future controller needs to combine financial knowledge with data analytics, technology, AI literacy and the ability to communicate results.

What tools are used in modern controlling?

Common tools include Excel, Power BI, reporting automation solutions, database technologies and AI tools for data analysis.

The future of finance belongs to people who can work with new tools

AI will not remove the value of finance professionals. It will change the way they work.

The biggest advantage will belong to people who combine financial knowledge, analytical thinking and the ability to use new technologies.

If you want to understand numbers, data and business decision-making, explore the Management Accounting and Controlling specialisation and submit your non-binding application to STING.

Sources

• IMA + Deloitte: Next-Gen Controllership: Harnessing AI and Emerging Technologies to Transform Finance and Accounting
  https://www.imanet.org/en/Research-Publications/IMA-Reports/Next-Gen-Controllership-Harnessing-AI-and-Emerging-Technologies-to-Transform-Finance-and-Accounting
• IMA Press Release: New Deloitte, IMA Survey Emphasizes the Importance of AI in the Future of the Controllership Function
  https://www.imanet.org/en/Press-Releases/2024/12/New-Deloitte-IMA-Survey-Emphasizes-the-Importance-of-AI-in-the-Future-of-the-Controllership-Function
• Deloitte: Next-gen controllership
  https://www.deloitte.com/us/en/programs/center-for-controllership/blogs/controllership-automation-data-management.html
• ACCA: Smart alliance: accounting expertise meets machine intelligence
  https://www.accaglobal.com/gb/en/professional-insights/technology/smart-alliance.html
• ACCA Magazine: AI and accountancy join forces
  https://abmagazine.accaglobal.com/global/articles/2024/sep/business/ai-and-accountancy-join-forces.html
• World Economic Forum: Future of Jobs Report 2025
  https://www.weforum.org/stories/2025/01/future-of-jobs-report-2025-jobs-of-the-future-and-the-skills-you-need-to-get-them/
• Microsoft: What is Power BI?
  https://learn.microsoft.com/en-us/power-bi/fundamentals/power-bi-overview
• NIST: AI Risk Management Framework
  https://www.nist.gov/itl/ai-risk-management-framework