As a finance professional, you’re operating in a landscape that keeps changing at speed. New technologies, stricter regulations, and rising expectations from the business all land on your desk. What does that mean in practice? Which trends really matter, and how do they affect your role? Based on our hands-on experience from the field, these are the developments that stand out most right now.
In our daily work, our experts see the same topics keep coming up. We notice how these developments directly affect priorities, roles, and decision-making. Based on what our experts encounter in projects every day, these are the trends that currently shape finance the most:
AI dominates almost every conversation in finance. And it will remain a key topic for the foreseeable future. At the same time, our experts note that real adoption of finance processes remains cautious.
We see many organizations enabling tools like Copilot to support employees with daily tasks. Also, some components of AI have been embraced by finance for years. One example is narrative reporting. Many finance teams use it to enrich financial data with automatically generated explanations and insights. As numbers change, the accompanying text updates instantly, keeping reports consistent and up to date. Narrative reporting also makes it easier to produce content in multiple languages without rewriting reports manually, which is especially valuable for international organizations. Another example is predictive planning and scenario-based forecasting. Both examples save finance teams time and improve insights, enabling finance to focus more on analysis.
When it comes to EPM, however, AI usage remains limited. In practice, finance teams hesitate to rely on AI-driven outputs, mainly because results still require clear explanations. If numbers cannot be traced and explained, trust becomes a barrier. Our experts see that AI in EPM is often perceived as not mature enough yet for high-impact financial decisions.
At the same time, interest is clearly growing. Our experts note that finance teams are actively exploring how AI could support their processes and how it will be integrated into EPM platforms. Many organizations want to move forward, but struggle with one key question: where do we start?
In our projects, we see a clear expectation that AI will significantly change the finance role. Not by replacing finance professionals, but by reshaping their daily work. As AI becomes more embedded in EPM solutions, repetitive tasks are expected to disappear. That opens up time for deeper analysis, proactive scenario development, and more strategic involvement in decision-making.
Finance teams are gradually shifting from a traditional controlling role towards a stronger business partner position. AI supports that shift, as long as it serves as an assistant rather than a black box.
Across organizations, our experts consistently see the same questions and requirements returning. The value of AI entirely depends on data quality, transparency, and security.
For critical use cases such as forecasting financial figures, finance teams want complete clarity. They need to understand how calculations are made, which assumptions are used, and where the limits of the model lie. Without that transparency, AI remains hard to rely on.
For lighter use cases, such as automated dashboards or exploratory reporting, expectations are different. In those cases, our experts notice that reliability and ease of use matter most.
Well-designed data models play a crucial role. The more structured and complete the data model, the better the output and reliability of the AI results.
Our experts see that all vendors position AI prominently, but implementations vary widely. We expect the number of organizations implementing AI to increase rapidly, especially if the solution meets business requirements transparently.
Most current solutions mainly use a company’s own historical data. Benchmarking against external data or macroeconomic developments remains limited. Currently, this is typically part of early-adopter scenarios, but it will deliver even more value.
We also see that some vendors use a different licensing model for AI. Instead of traditional module-based licensing, AI often comes with credit-based usage or separate tooling costs.
Cybersecurity has become a recurring topic. Regulations such as the updated European NIS2 (Network and Information Security) directive increase awareness, but our experts note that the focus extends well beyond compliance.
In practice, security, risk, and control increasingly influence decisions around architecture, hosting, and release management. Many vendors push cloud adoption, sometimes leaving organizations with limited alternatives. Our experts see that larger organizations often prefer private cloud environments to retain control and strengthen security.
Finance teams frequently ask questions about updates, interfaces, and changes introduced by third parties. At the same time, risk and compliance become increasingly important as the number of source systems grows. Especially in BI environments with data lakes, our experts see finance teams facing increased pressure to clearly explain data lineage, transformations, and audit trails to auditors.
EPM, BI, and ESG are no longer separate worlds. Our experts clearly see these domains integrating, both technically and organizationally.
A recurring discussion concerns ownership. Where does ESG belong? With finance, under the CFO, or within sustainability teams? In many organizations, finance plays a central role due to its experience with governance, reporting standards, and audit requirements.
This alignment strongly influences tool selection and data source integrations. Our experts see organizations striving for integrated setups that combine financial, operational, and ESG data into a single source of truth. The goal is clear: reduce reconciliation effort and increase consistency across reporting and analysis.
Technology continues to evolve rapidly, and finance teams feel the impact directly. Our experts notice that many organizations struggle with the sheer number of available tools, while lacking the capacity to develop all required skills at the same pace.
In addition, finance increasingly operates in complex data landscapes, integrating data from various sources, including ERP applications, BI solutions, and ESG data.
Even though technical topics are a part of the IT domain, they heavily influence the daily work of finance teams. Therefore, finance professionals need to have a high-over understanding of technical topics to consider the impact of decisions. At Swap Support, our experts understand both worlds and often create a bridge between IT and Finance. This is essential to keep applications stable, secure, and ready for future demands.
From our day-to-day work, one thing is clear. Finance operates at the intersection of data, technology, and decision-making. Across projects and client conversations, our experts consistently see four trends shaping the future of finance. These trends do not stand on their own. They reinforce each other and together redefine how finance teams work, which skills they need, and how they create value for the business.
To tackle these developments, we believe an integrated approach to strategy, development, and support is needed. Our experts help you to build solid foundations, make deliberate choices, and focus on practical value rather than hype.