Unintended consequences: how third-party plug-ins hold finance teams back from AI

There is no denying that the accounting industry is in pursuit of digital transformation. In a world where the ability to access real-time data is becoming mission critical for better managing finances and adapting to fast evolving regulatory demands, accounting professionals are turning to automation and analytics to unlock new efficiencies and advanced insights.

Over the years, many finance departments have resorted to using third party plug-ins in a bid to improve processes, boost operational productivity and gain access to new capabilities.

On the surface this seems like a sensible way to circumvent the challenges associated with updating legacy accounting software and accessing new features. However, longer term it can create problems that will derail modernisation efforts and make it difficult to fully embrace new AI functionality.

The problem with third-party plug ins

Legacy accounting software is increasingly ill-equipped to meet the demands of doing business in today’s fast-paced global markets.

While many major providers may have updated their user interfaces, their solutions are not truly cloud native. As a result, finance leaders have looked to accounting software plug-ins to enable new features or functionality. However, there are a number of unintended consequences that can arise as a result of taking this approach. For example, when data resides in multiple systems it can prove difficult to maintain a single source of truth.

Similarly, utilising multiple add-ons can make it time consuming and challenging to access the right information, especially when this has to be repeatedly re-entered into the core system. This disparity can create major challenges for organisations when they undertake month-end reporting.

This should sound alarm bells for organisations that are reliant on a patchwork of third-party systems that underpin everything that they do. If tasks are primarily being actioned via third-party integrations rather than the core operating system itself, this is a clear signal that the core operating system is no longer fit for purpose. It is also a powerful indicator that native AI functionality is unlikely to be available anytime soon.

AI opportunities on the horizon: why it’s time to move on

Organisations using traditional on-premises solutions risk falling behind those that have embraced cloud-native accounting solutions that can quickly and seamlessly integrate new AI-based enhancements.

Eliminating the constraints of on-premises systems and ensuring data consistency across the board, cloud-native accounting systems unite AI, automation, BI and analytics in a single yet scalable core platform. Alongside eliminating compatibility risks, these solutions provide the open APIs that make it easy to connect with other systems and future-proof functionality.

Alongside initiating more advanced automation for core accounting and finance teams processes, making the move to a native cloud accounting solution opens the door to capturing new AI functionality on the horizon.

For example, organisations can use AI to go beyond the basic character recognition provided by Optical Character Recognition (OCR) technology and elevate their data collection capabilities. They could also use AI to capture invoices, allocate a supplier or pay invoices below a certain amount and handle other basic administration tasks such as reconciliations or the creation of new supplier profiles. It could even embark on zero-touch invoice management that eliminates the need for manual processes and results in faster payment collection.

Similarly, it becomes possible to embed AI-driven reporting within accounting and finance software, delivering data interpretation, insight and visualisation tools like Microsoft Copilot without going outside the platform. With AI in play users will be able to ‘ask’ the software to display the balance sheet for the last quarter, highlighting all outstanding invoices after 30 days. A facility that could prove game changing when it comes to the preparation of month-end and board reports.

Alongside automating workflows, eliminating the need for multiple manual interventions and enabling sophisticated financial analysis, the introduction of AI also helps address a number of workforce challenges.

Creating a more rewarding future for accounting practitioners

Today’s firms are struggling to attract the new talent or improve how they relieve the pressure on their existing in-house teams of accounting professionals.

While AI can’t replace the critical judgement of experienced finance professionals, it can certainly alleviate much of the repetitive drudgery that grinds these workers down. For example, AI is more than capable of efficiently automating the many mundane data entry, reconciliation, invoice processing, risk assessment and audit tasks that get in the way of finance professionals focusing on higher-value work such as financial planning and data analysis.

For newly qualified and tech-savvy university graduates, working with modern AI-powered systems holds a strong appeal and enables them to get on with the job they have trained for. Meanwhile, these systems can significantly improve day-to-day working life for existing employees, giving them the bandwidth they need to focus on more complex and strategic work.

Grasping the future today

The technology to achieve all this exists today, but cloud-native accounting and software providers have the edge when it comes to delivering AI functionality within the core product itself. For them, it’s a matter of configuring and implementing it in the most user-friendly way possible.

By contrast, vendors that offer solutions built on outdated technology will resort to fast-tracking this functionality using authorised third party plug-ins. However, as we’ve seen, this approach can have lasting repercussions for firms and prevent them from fully embracing AI so they can focus on analysis and other high value tasks.

Ultimately, relying on third-party add-ons might provide a short term fix but is unlikely to be sustainable for the long term. For organisations that want to leapfrog the limitations of their existing legacy systems and avoid reliance on a patchwork of third-party systems, embracing cloud-native platforms is an easier and more workable way to embed new AI capabilities across their operations.