Integrating AI in accountancy and finance presents challenges and opportunities for the profession. However, ACCA research suggests that while there is a need to evolve the skillset and knowledge base continuously, there are also strong foundations from which finance professionals can position themselves and their organisations 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, so it’s no surprise that employers are emerging in demand for data science and engineering skills as well as data management skills.
‘That reflects the importance of data-driven decision-making within organisations. But it also reflects a profession 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 backwards-looking dashboards requires a change in tools and skills.
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 currently using AI, ACCA found that organisations anticipate 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 accountants can play is 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 integrating AI and machine learning.
On the other hand, the research underlined 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. Still, success depends on effective guidance from domain experts like accounting and finance professionals to help them obtain value from those technologies and tackle serious risks.’
