For tax and finance leaders at most enterprise-scale businesses, generative AI (GenAI) is both an exciting prospect and an unknown quantity. Many have started to dabble with the technology and a small but growing minority are integrating it into their practice with promising results.
Despite the excitement around its potential benefits, some businesses are unsure of how to harness the new technology effectively. Concerns also linger over the reliability of AI models, access to the data needed for training, data security and the shortage of skilled AI talent.
This is perhaps why many tax and finance leaders felt pessimistic about AI last year, with some 85% saying GenAI would not positively impact their department, according to the EY Tax and Finance Operations Survey 2023.
However, confidence in the technology is growing fast and this same cohort now feels more optimistic. Some 87% of leaders told EY this year they felt GenAI would increase effectiveness and efficiencies within the tax function in the next three years.
So, what’s behind the shift in mindset? Where are businesses on their AI journey? And how can companies get the most out of this new technology while avoiding the risks?
Like most big businesses, the wealth management firm Quilter is at an exploratory stage of its AI journey. Mark Satchel, its CFO, sees the integration of AI into the finance and tax functions as “a natural progression” that could yield significant benefits as the technology evolves.
However, he says the firm’s current use of AI is “limited”, focusing on improving management reporting and business planning.
“These enhancements have not yet fundamentally replaced existing processes and methodologies,” he says. “But looking ahead to the more immediate future we expect AI to assist with tasks such as expense analysis, both within accounting and tax, and for its use to expand into other areas over time. This growing optimism reflects our belief in AI’s potential to transform and elevate the efficiency and effectiveness of finance and tax operations.”
According to EY’s survey, 52% of finance and tax functions are at an early stage of their AI journeys, meaning they are investigating and experimenting with the technology but have no concrete plans to implement it.
Around 17% are classed as “emergent”, meaning they have developed strategies to implement AI and are running pilot projects, while just 9% have fully integrated the technology into their business processes. Almost a quarter of leaders say their AI maturity is “non-existent” and that they haven’t explored or adopted any of these technologies.
This could soon start to change, however, thanks to a distinct shift in mood about AI, says Ian Pay, head of data analytics and tech at The Institute of Chartered Accountants in England and Wales (IEACW). Businesses have become more familiar with the technology, its quality and capability are improving rapidly, and viable ideas about how the tech can be deployed in enterprises are emerging.
“We are seeing a lot of activity in the software vendor space,” he says. “In October, for instance, it was announced that Thomson Reuters had bought Materia, a GenAI accounting platform.”
According to the EY research, CFOs and tax leaders believe AI could impact many parts of the tax function. This includes data acquisition and cleansing, accounting, compliance, analytics and reporting and planning.
The shortage of qualified tax professionals reinforces the need to automate
Bas Kooijman is CEO of DHF Capital, an asset management company based in Luxembourg. He believes AI’s enormous potential to reduce operating costs and increase productivity makes it an appealing solution for managers aiming to maximise profits.
“AI’s ability to process large volumes of structured and unstructured data – such as invoices and tax reports – enables faster, more accurate analysis, boosting confidence in the technology,” he says. “Moreover, the shortage of qualified tax professionals reinforces the need to automate, which in turn helps attract new talent by reducing routine tasks.”
Datasite is a software business that supports companies around the world with deal-making activities. Merlin Piscitelli, its chief revenue officer for Europe, the Middle East and Africa, says AI is already transforming some areas of his industry. For example, it is helping to reduce weeks of due diligence work into “days or hours”.
Not only does this save time, but it also minimises human error, which can improve regulatory compliance, Piscitelli adds.
“AI can also aid in the valuation process by providing objective analyses based on historical data and market factors. Additionally, by automating repetitive and time-consuming tasks, AI can enable dealmakers to focus on strategic-level decisions and creative thinking.”
But there are clear barriers to adoption, one of the most notable being cost. Creating, deploying and maintaining AI systems requires substantial ongoing investment and there’s a continuous need for computing power, data storage and security measures.
Moreover, around one in ten tax and finance leaders find justifying return on investment as a significant barrier to AI use cases, according to the EY survey, which makes it harder to rationalise investments.
“Many companies are grappling with questions about how best to leverage AI within their specific business contexts,” notes Piscatelli. “This experimentation, while necessary, can be costly and time-consuming. It also means that many organisations have yet to find the perfect fit for AI within their operations, further delaying the payoffs.”
There are significant data privacy, security and compliance risks around AI too. Poorly calibrated algorithms or AI models that lack transparency can lead to incorrect decisions, potentially endangering the business in an increasingly stringent regulatory environment.
“Breaches or improper sharing can severely damage a company’s reputation,” says Kooijman.
Naturally, there is a lot of “nervousness” about going “all-in” on AI, says Ian Pay of the ICAEW. Members of his group want to see clear and concrete examples of how AI can be deployed before they invest.
However, he says businesses can cut through the hype “by being laser-focused on the problems you are trying to solve and honest about whether AI is the right solution to those problems”.
This is reflected in the EY 2024 Tax and Finance Operations Survey, which confirms that companies testing the waters should start with pilot projects, gradually scaling these up as they gain confidence. External experts like EY’s consultants can provide support while using industry benchmarks to measure AI’s ROI. Such an approach can help businesses focus on initiatives that deliver the most value and ensure investments are carefully managed, minimising risks while maximising returns.
Regardless of the risks, AI will likely become a key competitive differentiator: tax and finance leaders cannot afford to ignore it. As they face growing pressure to keep costs down, improve productivity and tackle skills shortages, AI could offer irresistible solutions to persistent problems, provided the risks can be managed and investments in the technology align with business objectives.
