AI is poised to deliver much-hoped-for automation to finance and accounting teams—but is everyone ready?

By Charis Thomas, Chief Product Officer and Chris Tredwell, Chief Operating Officer at Aqilla

Compared to software serving other sectors of the economy, innovation within accounting and finance software innovation is generally slower and more conservative. True, major players have updated their UI and added new features that give it a cloud feel. They might also have shifted to subscription-based models and updated their pricing structure. But, in the end, there’s no hiding that the basic underpinning architecture in some solutions still used in our sector could be over 30 years old. The result is that development cycles are usually slow, and new features take time to reach users.

Many organisations have turned to third-party plug-ins and extensions to sidestep these issues, but the approach isn’t without problems. For example, maintaining a single source of truth gets more complicated if data resides in multiple systems. Finding the information you need can also be more challenging and time-consuming—especially if you then have to re-enter it into the core system. This is one of the main reasons month-end reporting can be such a struggle for so many finance and accounting teams.

It’s no bad thing to compliment your solution with a few pieces of specialist software. The problems start if you become reliant on a mismatch of third-party systems to carry out your core tasks. If that sounds familiar, it’s probably an indication that your core system isn’t fit for purpose. It could also be a potential red flag that AI functionality may be slow to arrive or might not even be possible.

First past the AI post with cloud-native solutions?

Those with cloud-native solutions—supported by more agile development processes—are likely to benefit sooner from AI-based enhancements, more advanced automation and improved efficiencies. Research conducted at our last user conference supports this view, with 63% confident that AI, when integrated into accounting and finance software, can speed up processes and procedures such as bank reconciliations, invoice processing and month-end report generation. They also believe AI will increase efficiency within their role (46%) and across their team (43%)—and that these efficiency gains could be the catalyst for productivity increases at an organisational level.

If true, this will widen the productivity gap between teams that use more modern (and often cloud-based) accounting solutions that can quickly integrate AI-based components—and those that continue to use older (and often on-premises) solutions.

Some vendors might implement a quick fix with third-party AI enhancements. They might even enter into partnerships and recruit systems integrators to package up disparate software solutions. These and similar approaches mean AI washing is a common problem across all business software. So read the small print and get independent advice if you’re unsure or concerned.

To simplify things, we believe keeping AI, automation, BI, and analytics within the core product is a more viable long-term strategy. This strategy should help deliver higher-value services to users at a far more competitive price.

Practical applications of AI in the near future   

AI-driven reporting, analysis and data visualisation

It should soon be possible to embed AI-driven reporting within accounting and finance software. We envisage some form of data interpretation, insight, and visualisation tools like Microsoft’s Copilot, but operating within rather than outside the platform. It’s our preferred option as it means users have one less security issue to deal with.

Rather than adding data to spreadsheets and creating images, this would allow users to ask the software to display different charts and graphs in a way that’s reminiscent of ChatGPT. For example, users might type (or say), “Show me a balance sheet for the last six months and highlight all outstanding invoices after 30 and 60 days.” This could be a game changer for preparing board reports and presentations.

Purchase-to-pay

AI could also deliver more advanced automation of core accounting and finance team processes, providing a more reliable way of importing data and allowing us to move away from Optical Character Recognition (OCR).

It could allocate suppliers, capture invoices, and pay invoices, with users free to introduce maximum amounts and specify pre-agreed suppliers. There is no conceptual reason this couldn’t happen very soon. However, AI is still a relatively new technology— and some users might not be ready to hand over their responsibilities to a machine.

One answer might be to offer zero-touch invoice management by default but give more cautious users the opportunity for manual, human involvement at each stage and at a level that suits them and their business. In this scenario, the software could learn the company’s processes and become more accurate. Users could also have the opportunity to build trust and understand AI capabilities (and limits) in a space they can fully control.

Basic admin tasks

Plenty of other basic admin tasks could be handed over to AI, including creating new supplier profiles and preparing reconciliations—all of which could save time and allow teams to focus on higher-value work.

Better tools to retain brighter talent

We’re cautiously optimistic that advanced automation delivered by AI will make jobs more rewarding and less repetitive. One consequence of this might be that businesses using older software might see brighter, more forward-thinking, and ambitious people move to companies with more advanced finance and accounting software so they can benefit.

Tech-savvy university graduates, newly qualified and coming on to an old system with a big admin burden, may also feel frustrated—as could anyone who has worked for a few years in the industry and doesn’t want to return to old systems. That’s bad news in a sector with a long-term skills shortage problem.

It’s been decades, but AI can finally improve account and finance team processes. If we’re being honest, no one wants to key in data anymore; everyone prefers to work on analysis and other high-value tasks. So, let’s facilitate that change and make life better for us all!