AI, finance and the narrative we need to challenge.
Over the past months, one type of content has dominated LinkedIn feeds, newsletters, and industry discussions.
Charts showing which jobs AI will replace first.
Headlines about roles disappearing.
Statistics creating urgency. And often fear.
One widely shared example claims that more than 90% of finance tasks can be automated. That hiring among younger professionals in exposed roles is already declining. That we may be facing what some call a “white-collar recession".
At first glance, this may seem dramatic. And yes, there are elements of truth in it.
But at KOKAI, we believe this picture is incomplete. And if left unchallenged, it risks steering both companies and young talent in the wrong direction.
A familiar pattern. Technological shifts do not eliminate work
To understand what is happening now, it helps to take a step back.
The Industrial Revolution was one of the most transformative technological shifts we have seen. It changed how goods were produced, how companies operated, and how economies functioned.
Machines replaced manual labour at scale.
So what happened to the workforce?
Working hours did not decrease. On the contrary, historical data shows that they increased for long periods. Productivity rose significantly. New industries emerged. Roles we now take for granted did not previously exist.
What happened was not that work disappeared. It was redistributed and transformed.
This perspective is important when we discuss AI today.
AI is disruptive. But disruptive does not mean people are replaced
There is no doubt that today’s AI technology is powerful.
The tools being developed can already handle tasks that previously required specialised expertise. In finance, this includes reporting, forecasting, reconciliation, and parts of decision support.
That is likely why the discussion is so intense.
But the question is not whether AI can perform tasks.
The question is what happens to the role of the professional when those tasks change.
Because this is where the narrative often becomes too simplistic.
From task execution to value creation
If we look more closely at how AI is actually being used today, a clear pattern emerges.
AI is particularly well suited for:
Processing large volumes of data
Automating repetitive processes
Generating first drafts and analyses
Identifying patterns and anomalies
These are important capabilities. But they primarily impact how work is done, not why it is done.
The role of finance is not only to produce numbers. It is to create understanding, support decisions, and contribute to the direction of the business.
This means the shift we are seeing is not about “jobs or no jobs".
It is about the kind of work we do.
From producing reports to interpreting them.
From collecting data to validating and questioning it.
From executing tasks to contributing to decisions.
This is a shift in focus. Not a loss of relevance.
Domain expertise becomes more important, not less
One of the most underestimated factors in this discussion is the importance of domain expertise.
It may seem as though AI makes deep knowledge less necessary. In reality, the opposite is happening.
To use AI effectively, you need to understand:
Which questions to ask
Which data is relevant
Which assumptions are behind the output
What limitations and risks exist
Without this understanding, AI becomes a tool that produces answers without ownership.
This is especially critical in finance, where decisions have real consequences.
Research from organisations such as McKinsey clearly shows that while certain tasks are automated, the demand for skills like analytical thinking, problem-solving, and domain expertise increases.
In other words. AI raises the bar.
What this means for FP&A and modern finance functions
For finance teams, especially within FP&A, this shift is already underway.
We see a clear movement away from static reporting toward continuous planning, real-time insights, and scenario-based decision support.
This is where technology plays a critical role.
Solutions like Aimplan enable more dynamic and collaborative planning processes. Microsoft Fabric brings data together across the organisation and makes it accessible. Power BI turns complex datasets into insights that can actually be used for decision-making.
But these tools do not replace people. They amplify them.
They remove friction in data collection and processing, allowing teams to spend more time understanding performance, challenging assumptions, and supporting the business.
The value is not in the tool itself. The value is in how it changes the way we work.
What this means for companies
For organisations, this requires a shift in mindset.
The question should not be “How can we reduce headcount using AI?”
It should be “How can we increase the value of our people using AI?”
The companies that succeed will be those that:
Equip their teams with the right tools
Invest in skills and continuous learning
Redefine roles with a focus on higher-value work
Combine technology with human judgement.
AI does not create value on its own.
Value is created when technology and expertise are used together.
A message to the next generation
We also need to address how this affects those entering the workforce.
Many young professionals in finance and analytics are now questioning whether their education is still relevant.
That is understandable. But it is also misleading.
Yes, some tasks will be automated.
But the need for new talent does not disappear. It evolves.
Future professionals will need to:
Understand their domain deeply
Think critically and analytically
Work effectively alongside AI
Translate data into insights and decisions
These are not less valuable skills.
They are more advanced skills.
Final thoughts. From fear to responsibility
It is easy to create attention by focusing on what might disappear.
It is more demanding, but also more useful, to focus on what needs to evolve.
At KOKAI, we see AI as a significant shift in how we work. But not as a replacement for people. We see it as an opportunity to elevate the role of professionals in finance and business intelligence.
This comes with responsibility.
We need to move away from fear-driven narratives and instead focus on the following:
Building competence
Sharing knowledge
Preparing for the roles of the future
Because the future of work is not about what AI replaces.
It is about how we choose to use it.
Curious how this looks in practice?
We regularly share how modern finance teams combine FP&A, AI, and platforms like Aimplan, Fabric, and Power BI to move from reporting to real decision support.
If you want to see what this means in practice, join one of our upcoming webinars or reach out for a conversation.
We are always happy to exchange perspectives.
Oskar Kristiansen
CEO, KOKAI
