Integration of AI in accounting and finance presents both challenges and opportunities for the profession. But ACCA research suggests that while there is a need to continuously evolve the skillset and knowledge base, there are also strong foundations in place from which finance professionals can position themselves and their organizations for success in this new era.
An ACCA skills analysis of 25,000 accountancy-related jobs found that analytical and audit roles were most likely to require advanced capabilities – such as data science knowledge – while data management skills were in greater demand for transactional roles.
Alistair Brisbourne, Head of Technology Research, ACCA, said: ‘Data skills are always evolving and so it’s no surprise to see that there is emerging demand for data science and engineering skills as well as data management skills by employers.
‘That reflects the importance of data-driven decision making within organisations. But it also reflects a profession that is looking to become more pre-emptive in how we use data to solve challenges.’
The research – AI Monitor: Skills to drive responsible AI adoption – found that shifting to forward-looking predictive analytics and away from backward-looking dashboards requires a change in tools and skillset.
Predictive analytics is a route to tackling important areas including ESG/sustainability and even elements of risk management. Accounting professionals are now expected to understand a wider variety of data types. Indeed, in a survey of over 900 senior finance leaders who are currently using AI, ACCA found that organisations are anticipating that almost half of finance function roles will be more data-centric – i.e data science or engineering type roles – in the future.
Brisbourne said: ‘The integration of AI provides extra impetus to the skills evolution, but one of the most important roles that accountants can play is in being stewards of innovation. That means focusing on value and responsible use of technologies like AI.’
AI Monitor: Skills to drive responsible AI adoption points out that there is a crucial balance to be struck. On the one hand, data literacy is evolving to incorporate specific needs associated with the integration of AI and machine learning.
On the other hand, the research underlined the fact that AI adoption cannot be tackled by specialists alone – accountancy and finance professionals have a unique role to play in bridging the gap between technical teams, the business, and regulators.
Brisbourne concluded: ‘AI adoption is still gathering pace, but the benefits are not a foregone conclusion. That will rely on the right skills and understanding, on the one hand; but success also depends on effective guidance from domain experts like accounting and finance professionals to help them obtain value from those technologies and tackle serious risks.’
