Tech misuse: Wasted budgets and missed ROI
At the top of the webinar, Georgi Ivanov, our Communications Lead at Payhawk (and a former CFO), set the stage by highlighting a pervasive issue in the finance world. He warned:
We’re about to make the same mistakes with AI that we made with ERPs, BI tools, and RPA. Despite paying premium prices, many finance teams only use 20-30% of their finance software capabilities… an underutilisation that is costing organisations millions every year!
The crux of the problem? It lies in expecting transformation from technology without first addressing fundamental workflow and process issues. Simply implementing a tool, whether it’s for AI or an ERP system, will never be enough. These tools, however slick, can quickly fail to deliver the promised transformation if underlying processes remain inefficient.
Tsvetina Yancheva, our Director of Product Marketing, agreed, saying, “In the early days of Payhawk, we focused on digitising processes. But we learned quickly that if your customer’s process is broken or inefficient, ‘just’ digitising it won’t help. You need to fix the process first.”
In truth, finance teams often miss out on new features and capabilities of even their most beloved tools. Why? They’re often understandably too caught up in day-to-day tasks to stay updated on their software’s full potential.
The panel agreed: Finance leaders must ensure that their teams not only adopt digital tools at the initial onboarding, but also continually adapt their processes to fully utilise these systems.
Starship's approach to software: Calculate the ‘real’ costs & savings
Andrew Rudchuk, Head of Finance Transformation at the autonomous robot company, Starship Technologies, shared an important insight from his experience of researching and onboarding tools:
When we’re buying software, we’re not just buying a tool; we’re buying the ability to properly execute our processes… and that means understanding efficiency. Calculate the ‘real’ cost per task — be it processing a reimbursement or handling a bill.
Take reimbursements, for example: After factoring in software costs and payroll hours, they found that each cost a potential €100; clearly, something had to change.
Andrew’s method of calculating the ‘real’ cost per task gave him and his team complete clarity on where time and money were slipping through the cracks.
These new, very detailed calculations transformed how Starship Technologies approaches ROI. And Andrew and his team went on to dig deep into every financial process — reimbursements, invoice approvals, etc — and attached the real costs belonging to each beyond the potential ROI on paper.
Unlocking the potential of AI in finance operations
With finance technology firmly under the microscope, the conversation naturally progressed to the next big chapter in finance tech: AI.
While AI has been heralded as the next big thing, many finance teams are still in the very early stages of research and adoption. However, the future looks bright, as Tsvetina described:
We see from early AI agent usage at Payhawk that AI in finance operations is already making a significant impact, especially when it comes to speeding up time-consuming tasks like receipt chasing and spend reconciliation.
The panel agreed. The best finance AI is not designed to replace people but instead to enhance their efficiency. Modern finance teams need AI that can handle repetitive, low-value tasks, freeing up finance teams to focus on strategic decision-making and higher-value work. “We want AI to act alongside finance teams, helping them to be more efficient rather than replacing them!”
This kind of smart collaboration is exactly where AI in finance operations can deliver the most value, by automating the routine so humans can focus on strategy.
But with new technology comes new demands, and Andrew and Tsvetina agreed that the next generation of finance leaders will need a completely different skill set. “Finance professionals need to understand AI, not just use it,” Andrew explained.
It’s about becoming proficient in how AI works and how it can be leveraged to streamline processes and drive strategic decisions. Tsvetina stressed the importance of creating a solid data infrastructure that can seamlessly integrate with AI technologies.
AI’s effectiveness relies heavily on well-managed, structured, and integrated data. If your finance function is using fragmented solutions, AI won’t be able to provide the insights needed to optimise operations. Tsvetina continued:
You need to prepare for AI now because, in five years, it will be too late.
In a nutshell? The future of finance is not about adopting AI but preparing the underlying infrastructure to support AI seamlessly. This includes ensuring that finance data flows effortlessly between systems, creating a foundation that allows AI to operate efficiently.
The top five takeaways:
- Understand your processes: Before adopting new tech, understand your existing processes. Know your cost per task and identify where inefficiencies lie.
- Don’t just digitise — optimise: It’s not enough to digitise a process; first, you need to fix any broken parts. Fix your processes > then integrate the right tech.
- AI is here to support you. Embrace AI as a tool to make your team more efficient, not as a replacement. Focus on using AI for repetitive, low-value tasks.
- Build the right infrastructure: Ensure your finance systems are integrated and your data is well-structured. This approach will allow AI to provide the full value it promises.
- Stay curious and keep learning: The next generation of finance leaders will need to understand AI. Start learning how AI can support your work today and get ready for the future.
As the finance industry continues to evolve, adopting AI in finance operations and optimising existing processes will be crucial for finance teams to stay competitive.
As our panel discussed, the key is not “just investing” in the latest tools, but truly understanding how to use them to their full potential. Discover how AI in finance operations looks with Payhawk, explore our AI agents, and find out more about the impact so far.
