With finance and tax teams under pressure to do more with less, many are already embarking on digitisation programmes to streamline manual and repetitive tasks.
The emergence of generative AI is also creating fresh opportunities to transform the finance and tax function by giving finance professionals access to a range of digital assistant tools that can save time and allow them to focus on higher-value work.
To benefit from these tech advances, however, finance and tax teams face several challenges. First, budget constraints or a lack of buy-in among senior leadership can limit investment in such projects. Second, even if projects get the green light, organisations often have data quality issues (not in the right format) or data access issues (stored in disparate systems), that make it difficult to properly use AI tools.
Here, three senior finance leaders discuss these challenges, some of the potential AI use cases that could transform the tax and finance function, and what this will mean for finance roles in the future.
We’ve spent a lot of time cleaning up our data and getting everything on an even keel to make sure we’re classifying things correctly and maintaining high data quality. You can’t automate or do any fancy stuff with AI if you don’t have the right data foundation. Data quality is important, otherwise the integrity of our financials goes out the window. If you don’t have the data and you don’t have the processes, none of that other stuff matters.
About three years ago, we started using Microsoft Power Automate tools to automate processes, and we do a lot of our approvals through there. Another AI tool we’re using is called BoostUp. This sits on top of Salesforce and looks at your sales pipeline and predicts future revenue based on the status of that pipeline.
When it comes to automating tax, if we had one ledger around the world and if our accounting software stayed up to date with every single nuance in all of the tax jurisdictions, we could automate the whole thing – but that isn’t possible at the moment. We operate in 10 different jurisdictions; some are still very manual and others are more advanced.
The finance and tax function is ripe for AI and machine learning transformation. If you think about the core principles of finance, much of it revolves around reconciliation, which, in its simplest form, is just comparing two numbers. There’s no reason why computers couldn’t handle that. There are more complex aspects of reconciliation, but the more we can automate that base level, the more leaders can empower their teams to do what we would define as more value-added activities. AI can help elevate finance functions to decision-makers and move them away from being labelled as a back office function.
We’re still in the early stages of understanding exactly what the best AI use case is for us. We’re currently using external tools that consolidate multiple data sources for automated reconciliation. This frees staff up to look at things on more of an exceptions basis, so less time is spent on the process and more time is spent on review.
Going forward, the finance role will become much more consultative. Finance teams should see AI as an opportunity to upskill, not as a threat. With AI, finance teams can become far more analytical and provide more meaningful insights to the business.
From our conversations, around 50% of finance leaders express a desire to know more about AI. While they have a basic understanding, many wish they had deeper insights into the specific benefits of AI, particularly in compliance, risk management and productivity. The first hurdle for them is often the educational gap – understanding how AI fits into broader business processes.
Budget constraints are also a key factor, especially in the current economic climate. We see in many companies, particularly those experiencing growth, that investments are frequently directed towards sales and product development, while support functions are often left behind. It’s only when these support functions become overwhelmed that companies begin to consider technology solutions that could help them scale more effectively.
There are a few things that companies are looking at with AI. One is making policies clearer and more accessible for employees. For example, an employee travelling to Barcelona for business could use AI to check the expense allowances for that destination. Meanwhile, the system can also use that employee data to predict travel costs more accurately. This can help organisations forecast and plan accordingly, which impacts cash flow and budget, and may affect future business travel decisions.
VAT reclaim and VAT submissions are also areas where AI and automation could support businesses, as these are still largely manual processes. Automating this will really allow finance teams to focus on more value-added tasks and move away from manual data entry processes.
Three takeaways for finance and tax leaders
- Data quality is crucial for AI success – It is vital to tidy up data and ensure its integrity before implementing AI and automation tools. Without accurate, well-organised data, advanced AI solutions cannot deliver meaningful results, which could undermine the financial accuracy of organisations.
- Investment in skills is a must – There is a big leap between recognising the potential of AI and knowing how to apply it. Many finance leaders lack a strong understanding of the benefits of AI from a compliance, risk management and productivity perspective. Upskilling should therefore be a priority.
- AI can free up resource and elevate the finance function’s position – The finance and tax function is ripe for transformation. Automating routine tasks such as reconciliations and manual processes will allow finance professionals to shift their focus to higher-value, consultative tasks. AI can elevate the position of the finance function, enabling employees to contribute to business strategy and decision-making rather than just handling back-office tasks.
