Is Finance Still a Good Career Choice in the Age of AI?
How to build judgment and experience when entry-level roles are disappearing.
AI is automating reporting, forecasting, variance analysis, and even commentary. With all this development, is there still room for people who are considering a career in Finance?
I hear this question a lot. And the concern is valid.
I am convinced that many parts of Finance will not disappear. But the focus is shifting. And with that, the traditional ways into Finance are changing. This is what makes it harder to enter the field today.
Finance is broad, and not all areas are affected in the same way. Some roles are far more exposed to automation than others. My own experience sits in Financial Planning and Analysis, which I still consider a highly relevant and interesting field. So I want to focus this discussion on FP&A.
What is AI really replacing in FP&A?
AI is particularly strong at tasks that are repetitive, rule-based, and pattern-driven.
I still remember one of my first tasks after leaving business school. I spent days reconciling large Excel files, looking for inconsistencies across different data sets. It was tedious work, it took ages, and it repeated every month. Over time, I found ways to automate parts of it and make the process more efficient.
Looking back, the value of that task was never the manual work itself. The real learning came from understanding how data behaves, where errors typically arise, how to break down overwhelming problems, and how to think systematically about automation. It trained my way of thinking.
Today, AI can do much of this work faster and better than a junior analyst ever could. That is why classical entry-level FP&A tasks are under pressure.
AI is not killing FP&A. But it is compressing or removing the traditional entry layer.
And this leads to the real question behind the AI debate.
If entry-level roles disappear, how do you build experience?
For a long time, the implicit career path in FP&A was clear. You started with manual work, learned the basics over several years, and gradually moved closer to decisions. That path no longer works in the same way.
So where does judgment and intuition come from today? What do graduates or career switchers do if they never get that initial field to grow into?
This is the real challenge for people starting their careers now.
What becomes more valuable instead
As FP&A moves away from producing numbers, other skills gain importance. Understanding business models. Asking the right questions. Translating numbers into implications. Challenging assumptions. Connecting financials to operational reality. Communicating trade-offs clearly.
In short, FP&A is shifting from reporting performance to supporting decisions.
Why AI cannot easily replace critical thinking
AI excels at recognizing patterns in historical data. Most businesses operate within fairly stable patterns most of the time, which is why AI works so well for forecasting, trend analysis, and anomaly detection.
But the real value of FP&A often appears when something breaks the pattern. A sudden demand shock. A supply chain disruption. A strategic pivot. A regulatory change. A competitive move that did not exist before.
In these situations, there is no clean historical pattern to optimize. The question is no longer “what usually happens” but “what do we do now.” Which trade-offs do we accept? Which risks are acceptable? What matters most in this specific context?
These are judgment calls. Someone still needs to frame the decision, weigh imperfect options, and stand behind a recommendation. That is not pattern recognition. That is responsibility.
How to build experience without traditional entry-level roles
I do not have all the answers. But I strongly believe that experience does not come from job titles. It comes from understanding real business drivers and being exposed to real decisions.
That also means we may need to rethink what a good early finance role actually looks like. It is no longer about the volume of tasks. It is about exposure to decisions. A smaller scope with real accountability can be more valuable than a large role focused on producing numbers that no one truly uses.
You do not need an FP&A title to develop FP&A thinking. Working close to operations, sales, or product can be incredibly valuable. Studying real companies and real financial statements with a decision-maker mindset builds intuition. Using AI deliberately as a learning and sparring partner, rather than as a shortcut, can accelerate understanding.
We live in an age of abundant data and abundant learning resources. The challenge is no longer access to information, but developing the right way of thinking about it.
The way forward
Finance and FP&A are still worth pursuing if you are curious about how businesses work and want to support decisions. They are less attractive if you are mainly looking for stability through routine.
AI raises the bar. But it also accelerates learning for those who are willing to lean into it.
What kind of finance professional do you want to become in a world where the numbers are easy, but the decisions are not?
