AI transforms accountants’ responsibilities

Four key themes emerge, with measures reflecting on the way accounting work and related responsibilities could be reshaped.

• contraction in routine processing, 

• expansion in strategic and advisory decision-making, 

• evolution of mid-level roles to incorporate more judgement and client interaction, 

• and new responsibilities at the intersection of accounting, technology and strategy. 

In terms of how we work, organisations will develop more integrated workflows that realise effective AI adoption is not just about distinguishing high versus low-value activities – but focusing on outcomes, quality and value.

The key to effective AI adoption will be maintaining local, human judgement for critical tasks – while improving overall efficiency and scaling judgement for routine exercises. 

New responsibilities and tasks will emerge in finance teams focused on improving controls and specifying the desired information outcomes from machine use. They will also need to maintain oversight and ensure AI systems remain accurate and compliant with professional standards and regulations.

The challenge is understanding how the connection of human and tech capability create advanced ways of working and generate new skill demands. The two are inseparable in our world – what will change is how these unions emerge and adapt.

Automation, specifically, tends to result in a change in the nature of job responsibilities. As AI systems become increasingly capable, they excel at specific functions that were once the exclusive domain of trained professionals. This is particularly evident where there are well-defined processes and significant data components. Tasks that once defined the profession – calculation, categorisation, data entry, and basic analysis – could be subject to automation, if easily codified, or AI could be used to provide additional information to support decision-making.

In terms of contraction in routine processing tasks, the natural follow-on question is: who is primarily affected by this partial automation? Given the low-risk, repetitive nature of tasks undertaken by entry-level professionals – they are expected casualties. This raises subsequent questions around how organisations can sustain and develop a talent pool that will feed through to the higher-level roles.

On the one hand, the answer might partly lay in what we expect of entry-level roles; their responsibilities and composition. Many tasks currently undertaken by early career staff could be partially automated in coming years. But an important aspect of this debate is regarding the way in which technology and innovation tend to create new occupational and career pathways – and new responsibilities for managing these developing workflows. 

Some organisations are already contemplating moving from a traditional pyramid-shaped organisational structure – where hiring is focused on a large pool of entry level talent – to a diamond-shape, where there are fewer entry-level roles and a focus on bringing talent into mid-level roles.

This is clearly an unsustainable trajectory, potentially choking off development pathways and having negative implications for institutional memory, even in the short-term. So, the function of entry-level jobs, training, and responsibilities – alongside organisational structures – will need to adapt. The structure underscores the importance of carefully considering the implications of how and which tasks are automated, even partially.

But to understand what is required of entry-level staff in the future, we need to understand how mid and senior-level roles are changing or need to change to embrace new opportunities – and how new pathways are opening. Topics ACCA will be exploring in an upcoming Career Pathways project.

A key determinant of how AI will impact the profession is the attitude of hundreds of thousands of finance professionals around the globe who are tasked with turning the chatter about AI into an everyday reality of working life in firms and finance departments. Implementing and integrating AI needs some context. While AI holds much promise many accountants face significant hurdles when integrating AI into their workflows. In other words before AI takes over accountancy, accountants need the tools and they need the skills to make it happen.

83% of Gen Z financial professional feel confident in their ability to learn and apply AI related skills. Hardly a figure suggesting a sector in terminal decline. However, that stat –from ACCA’s Global Talent Trend 2025 survey, the largest annual talent survey of accountancy and finance professionals across the world – should not hide the fact that our research prompted the question: is AI upskilling in the accountancy profession currently falling short?

Not having the skills required for the future workplace is a major concern – with 50% of respondents worried they’re not developing the necessary skills. Unsurprisingly, AI is identified as the most valuable workplace skill in demand (36%). However, only 38% are confident in their current AI knowledge – with many (44%) citing poor opportunities to learn as a barrier to skills development. Our global respondents feel particularly exposed by technology – with 44% worried about the impact of AI on their jobs.

It can come as little surprise that younger age groups are most concerned about not developing future-ready skills, the pace of technology change, and the impact of AI. Only 30% of Gen Y and 27% of Gen X say their employer is currently providing upskilling opportunities in AI.

An emerging consensus is that the real risk isn't AI taking jobs — rather it's someone who knows how to use AI taking them instead. However, in terms of the accountancy profession, all the evidence suggests that accountants are determined to be masters of their own fate, mastering AI to ensure a flourishing accountancy profession continues to serve the public good.