With executives estimating that as much as 40% of their workforce will need to re-skill in the next three years due to the adoption of artificial intelligence (AI), the accountancy profession needs to tackle these challenges to avoid losing its competitive edge.

The World Economic Forum (WEF) predicts this evolution of dividing labour between AI and machines will disrupt 85 million jobs globally between 2020 and 2025. It will, however, also create 97 million new roles. What these roles are exactly isn’t yet fully clear, but we know that the workforce will need a radically different set of skills.

AI has already begun transforming many aspects of accounting and audit. The technical skills in most demand include knowledge of data analytics and visualisation, machine learning and predictive modelling, process automation, AI-assisted auditing and fraud detection, and natural language processing for financial reporting.  A basic understanding of AI and how to use specific tools is becoming more valuable. In some cases, accountants might be expected to learn how to build AI models.

A substantial 67% of businesses are encouraging their finance and accounting talent to explore generative AI (genAI) tools for the enhancement of day-to-day routine tasks, according to the 2025 Robert Half Salary Guide. In addition, 50% are planning for internal generative AI upskilling programmes, while 34% are exploring mentorships to boost skills.

Interestingly, problem-solving and critical thinking skills are in high demand across the sector, too, says Hannah Szymanski, Market Director, Finance and Accounting, at Robert Half. “There’re lots of different types of AI, and different use cases and applications of AI, and while everybody wants to know the end game such as exactly how AI will change a specific role, the reality is that we’re not there yet. There are few industries where leaders are already at a point of training people in exactly how to use AI in their role.”

Fay Bordbar, Global Digital Skills Lead at global accountancy firm Forvis Mazars, sees upskilling as the precursor to AI adoption. “We need to train people in the basics of what AI and generative AI are, and how they might use genAI tools such as copilots and chat interfaces, as well as other types of AI. Through showing them what might be possible, particularly with genAI tools, giving them ideas of how they might apply that in their role, the use cases will come in time.” 

Security first

One of the major challenges for employers is how to train staff to use AI safely, ethically and responsibly. Forvis Mazars is approaching its AI training by documenting user stories in a training context, highlighting the pitfalls as well as the benefits.

For example, with tools like ChatGPT or other co-pilots, staff can ask a co-pilot if an email is appropriate to send to a client without having anonymised any of the data. The risk is that the AI tool may absorb that confidential data and resurface it without knowing that the data should be kept confidential.

“As accountants, we check the accuracy of information and calculations. We’re trying to get that message across in training; that AI output isn't something that you can take as verbatim. You shouldn’t train someone on AI without telling them about the pitfalls, the limitations and how to mitigate those,” Bordbar says.

It’s clear that even in these early days of training staff on AI, it’s vital that companies have a clear AI strategy or policy and develop their training using that. Every company has a different approach and risk appetite, depending on how they’re using AI in different areas of the business, so it’s vital to take a bespoke approach. Governments also have a huge role to play in the evolution of AI and how it is used and in training the next generations. Bordbar says: “AI is a technology that affects everyone at all ages, so you can’t wait to train young people. You’ve got to train everyone at the same time, but in different ways.”

Leanne Wilkins, Head of Talent Acquisition and Resourcing at MHA, agrees with the need for greater collaboration: “This is a prime example of the need to partner with educational institutions to ensure the next generation of accountants are provided access to specialised AI and data science courses and modules. Teams should be focused on identifying candidates with AI-related degrees or certifications, and HR teams should be implementing re-skilling initiatives to close the gap for existing employees.”

Implementing a cultural shift around reskilling will help organisations accelerate this change. Organisations that recognise the value of human capital while embracing advanced technologies will be most prepared for the future of work. 

Wilkins says: “Accountancy is a competitive space, both in the client and employment markets. To remain competitive in both of these areas firms must step up quickly with AI and emerging technologies, not only allowing for the best service delivery but freeing employees from more manual, repetitive tasks in favour of interesting, varied work. This will drive operational costs down, provide efficiency gains and ultimately increase output and profitability.”

In some sense, of course, the onus is on individuals as much as it is employers to re-skill for the future. AI is constantly evolving and those serious about their accounting career will at least be exploring the potential opportunities of AI. Adaptability and a human touch remain, for now, essential though.