In many finance departments, time seems to stand still. While other areas of the business already operate in real time, accounting and controlling still struggle with Excel files, manual reconciliations, and reporting obligations that do more to paralyse than to guide. This isn’t a new problem but its cost is rising. Regulatory pressure, volatile markets and growing demands for speed and transparency are no longer manageable with traditional means.
At the same time, technologies like artificial intelligence and intelligent process automation are opening up new opportunities. Not in theory but in practice: automated booking runs, AI-powered forecasts, and digital audit trails are already in use. What’s been missing is a strategic shift in perspective: away from transactional execution toward a finance function that enables decisions, reveals risks and creates value. That requires more than technology. It calls for new roles, new skills and the courage to challenge established patterns.
From Repetitive to Strategic: What AI Can Already Do
The maturity level of finance tech has reached a point where automation is no longer experimental, but commercially essential. In many organisations, the proportion of repetitive tasks in accounting remains high—whether in accounts payable, account reconciliation or monthly reporting. This is precisely where AI-based systems deliver the greatest value.
Using optical character recognition (OCR) and machine learning, incoming invoices can be captured, classified and booked automatically. Processing times drop significantly. At the same time, rule-based automation ensures traceability and compliance. Even forecasting, once the domain of experienced controllers, is increasingly data-driven. Algorithms analyse historic transactions, external factors and trends to simulate reliable scenarios.
AI is also gaining ground in compliance-related fields: transaction analysis for fraud detection, automated documentation requirements and regulatory threshold monitoring are handled faster and more consistently by intelligent software. Not least, the combination of process mining and RPA with AI allows dynamic process optimisation in real time, with concrete recommendations for action.
Crucially, the technology doesn’t replace judgement. It handles repetition, not responsibility. Its value lies in freeing up skilled professionals to make sound decisions based on data, not gut feeling.
From Controller to Business Partner: How Roles Are Being Redefined
If you're still writing job descriptions like it’s 2014, you're asking the wrong questions in 2025. Roles in finance-adjacent functions aren’t just shifting—they're dissolving. Traditional tasks are disappearing or moving toward technology. In their place, new demands are emerging: communication, analytical thinking, and system fluency.
Take the traditional controller, once responsible for cost centre reports, budget oversight and period-end closings. This role is evolving into a Finance Business Partner. Less number cruncher, more sparring partner. What’s needed are people who can not only generate reports, but interpret their meaning. People who understand how operational decisions affect the bigger financial picture and who can identify risks early, develop scenarios and provide management with fact-based advice.
Specialised profiles are also emerging: The Finance Data Analyst operates at the interface between BI systems and the CFO’s office, turning data into actionable insights. The Process Automation Lead oversees the implementation and coordination of automated processes. In regulated areas such as compliance or governance, new roles like AI Assurance Specialist are emerging responsible for ensuring that AI-driven decisions are documented and auditable (cf. EY, 2023; Frischmuth, 2025).
Equally interesting: neighbouring fields such as legal and real estate management are also evolving. They are seeing new demands for interface competence in contract analysis, ESG evaluation, or regulatory risk assessment. Functional silos are giving way to integrated role profiles, requiring more interdisciplinary thinking and less rigid responsibilities.
All of this doesn’t just change the work it changes the people who thrive in it.
Future-Ready Skills: What Matters Now
New roles demand new capabilities. But what actually makes a professional future-ready in an environment that’s increasingly automated, data-driven and networked? The answer lies in a skill set that combines technical know-how, analytical depth and strong communication.
Top of the list: the ability to work confidently with data. Data literacy, the ability to read, interpret and contextualise numbers, is a fundamental requirement. This includes working knowledge of digital systems: basic SQL, experience with BI tools like Power BI or Tableau, and a grasp of automated workflows and interfaces. Anyone shaping or analysing processes must understand how the systems function.
Second: processes can only be automated if they are understood. There's a high demand for professionals who can not only deliver figures, but also grasp their origin, dependencies and impact. Process comprehension is no longer the task of a few experts, it’s expected across teams.
Third: we need people who can translate across domains. Those working with AI must be able to convert business requirements into technical specs—and vice versa. This translation skill between business and technology often determines whether projects succeed or stall.
And then there are the so-called soft skills—which are anything but soft: communication, adaptability and ethical judgement. Especially when working with AI, professionals must be able to ask the right questions—and challenge decisions, even if they come from an algorithm (cf. McKinsey, 2024; Frischmuth, 2025).
The labour market is shifting toward hybrid profiles: people who are technically sound, digitally literate—and distinctly human. These are the individuals who make teams resilient, connected and decisive.
The Race for Hybrid Talent: Why Recruiting and Upskilling Are Crucial
While AI continues its advance into finance departments, the talent market isn’t keeping pace. Demand for professionals who can navigate numbers, optimise processes and master digital tools far exceeds supply. What we’re seeing is a competitive race for hybrid talent.
The most sought-after professionals combine a strong finance background with thinking rooted in IT, process management or data analytics. Those who can think beyond silos from accounting to ESG reporting, or from controlling to business intelligence—provide clear competitive advantages.
But here’s the challenge: such profiles don’t grow on trees. Companies must significantly step up their strategic recruitment and talent development efforts. Traditional job ads with lengthy requirement lists rarely attract the right candidates. The focus should shift to recognising potential and enabling upskilling. Training programmes, on-the-job learning and cross-functional projects are becoming key tools.
Leadership is also evolving. Managers must become talent architects, spotting strengths early, opening up development paths and having the courage to take new approaches, including hiring career-changers with digital mindsets.
Trying to solve the talent issue through hiring alone is short-sighted. Those who identify and grow existing potential will build long-term stability especially in highly regulated business functions where both technical excellence and human discernment are vital (cf. Deloitte, 2023; Numeris Consulting, 2023).
Conclusion: Act Now Before the Talent Gap Becomes Real
Technology changes structures. But it’s people who shape the future. Leaders in economically critical roles are facing a fundamental decision not about tools, but direction: Will the finance function remain a reporting unit? Or become a strategic nerve centre?
Artificial intelligence and automation provide the operational backbone for this shift. They save time, enhance quality and open up new perspectives. But they also require new role models and new skills that go beyond numerical fluency.
Forward-thinking organisations are acting now. They’re investing in skill strategies that link data-driven analysis with entrepreneurial thinking. They’re reimagining career paths. And they’re building teams ready to take responsibility not just for the outcome, but for how they get there.
Because in the end, it’s not the algorithm that determines a company’s future-readiness. It’s the people who understand it and give it direction.
Competence gains depth
AI and automation don’t just change processes they shift the demands placed on those in key financial roles. Today, hiring the right talent requires more than résumés. It requires data-driven selection methods, well-defined skill profiles and a deep understanding of tightly regulated, business-critical functions. At Numeris Consulting, we help you align your recruiting with this new reality future-focused, skills-based and compliant.
Looking to strengthen your finance and governance functions? Get in touch. We look forward to hearing from you.
References
- Deloitte (2023): Shaping Workforce Strategy for Future of Finance.
- EY (2023): Wie kann die Controller-Rolle mehr Vertrauen schaffen?
- Frischmuth, M. (2025): Künstliche Intelligenz im Finanzbereich – 10 Thesen.
- KPMG (2025): Digitalisierung im Rechnungswesen 2025/2026.
- McKinsey & Company (2024): How Finance Skills Are Evolving in the Era of Artificial Intelligence.
- Numeris Consulting (2023): Emerging Job Roles in Finance: What Skills Are Needed Now.
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Digital tools for skill-based recruiting: From ATS to AI-supported skill matching
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