Jan Pautsch
Which finance profiles have a future with AI?
The finance function is changing rapidly. AI-supported tools, automated forecasts and real-time analyses are finding their way into CFO offices – from Scalable Capital to Klarna. But technology is not replacing management – it is increasing the pressure of expectations: on decision-making quality, speed and responsibility for results.
In recruiting, it is clear that today’s finance managers with AI expertise are in demand – people who understand systems but can lead teams. People who think operationally but implement strategically. In this article, I show which profiles exist in practice, where technology helps – and where it reaches its limits.
Contents
Finance Finding managers with AI expertise
Technology is changing finance management – but not replacing it.
FinTechs and scale-ups are under pressure: reporting obligations, governance, buy & build complexity, investor logic. At the same time, AI & automation are pushing their way into the boardroom. Real-time analytics, automated forecasts and AI-supported due diligence tools promise efficiency. But which finance managers have a future with AI? And what remains irreplaceable?
The new demands on finance management
2025 is the year of maturity: According to the Global FinTech Report 2025 (BCG & QED), 69% of listed FinTechs reached the profit zone. At the same time, funding has slowed significantly. The market is demanding:
- Governance instead of vision
- Transparency instead of speed
- Leadership that understands technology
But it is precisely this combination – M&A craftsmanship, integration skills and change expertise – that is becoming rarer. This is where technology comes in.
What AI can do – and what it can’t
AI takes the pressure off. But it does not lead.
Modern tools take over today:
- Real-time reporting & forecasts
- Automated due diligence
- Scenario modeling
- AI-based deal analytics
Example: Morgan Stanley is testing AI co-pilots for advisory meetings. Klarna is already replacing its first operational CFO functions with GPT-based assistants. Revolut is building crypto product lines with the help of generative AI. But: decisions, conflict resolution and stakeholder management remain human.
Source: Kooku X Finance, based on BCG & Sifted market analyses, 2025
Zuture profiles: Which finance leads are needed now
Managers who work with technology – without hiding behind it – are in demand.
Typical profiles:
- CFOs with experience in Buy & Build & Tools
- FP&A leads with real-time expertise
- Controller with process vision & AI affinity
- Transformation manager with stakeholder logic
Important: It is not tools alone that count, but the ability to use them in the context of culture, investor expectations and team structure.
Hybrid profiles are in demand: Managers who understand technology and lead teams through change.
Practical examples: Where AI works today – and why leadership remains
Artificial intelligence is changing operational practice in FinTechs – from customer service to forecasting:
Example Klarna:
An AI hotline answers customer inquiries as a digital CEO clone, feedback flows directly to product management. Two thirds of customer service is already handled by an AI chatbot – with drastically reduced processing times.
Source: The Verge
Take Revolut, for example:
2025 Revolut is launching an AI financial assistant. It analyses budgets, advises on saving and structures finances directly in the app – personalized and automated.
Source: sifted
But above all, these deployments show that AI has an operational effect – but leadership remains crucial.
Study perspective: AI eases the burden – but does not replace a decision
According to Wolters Kluwer, 67% of CFOs want to invest heavily in AI by 2025 – especially in the areas of forecasting, risk management and scenario modeling. However, the same study also shows that only 35% of companies consider their management teams to be sufficiently prepared to manage these technologies strategically.
Source: Wolters Kluwer
A Forbes analysis also confirms this: While tools such as generative AI bring efficiency benefits, the need for leadership expertise in change, culture and integration issues remains high.
Source: Forbes
My conclusion
Anyone looking for finance leadership with AI expertise today needs profiles that can do both: understand systems – and lead people. AI can bring speed. But structure, trust and clarity still create leadership.
How I support you as a headhunter
I find finance leaders who make an impact: with AI and experience. Whether CFO, FP&A or transformation roles: My network, my market knowledge and a structured process ensure speed and fit.
Jan Pausch
Head of Expert Search / Kooku X
Your Experts for Digital Finance & Transformation
Jan Pautsch is Recruiting Director at Kooku X. He brings leadership experience from the design and digital industry and today fills key roles in finance, design and transformation
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Finance Headhunter requestWhat decision-makers want to know now about leadership in FinTech scale-ups
Finance leaders should understand digital tools – but not be tech specialists. We need people who can handle forecasting, reporting and analysis tools, but who can also manage integration processes, communicate with stakeholders and lead teams through change. The combination of tech affinity and leadership experience makes all the difference today.
The key lies in a clear job description, an active network and targeted executive search. At Kooku X, we fill such roles – permanent or interim – with candidates who have both analytical depth and leadership skills. Our data-based matching approach shortens the time-to-hire and ensures that we not only serve tools, but also shape transformation.
With a precise briefing and an active network, we can often present the first validated profiles within a few days. Interim and fractional roles can also be filled at short notice.
In four steps:
Clarify objectives – understand organization and expectations
Market & search – benchmarking, mapping, direct approach
Calibration – first profiles, fine tuning with feedback
Conclusion – decision-making, contract process, onboarding
