It’s a given that artificial intelligence and machine learning will change the job landscape in accounting, if it hasn’t done so already.
What is important for accountants, both existing and prospective, is to be adaptable – just as we have adapted from using pen and paper to computers, from physical ledgers to accounting systems (or enterprise resource planning (ERP) systems), and from gut feelings and hunches to using data analytics for data-driven business decisions.
The tech offers ‘content’; we humans bring ‘context’
Like it or not, AI and machine learning are here to stay, but we shouldn’t feel threatened by the technology. We should see this as a watershed moment, and make AI and machine learning our comrades in arms. We should see it as an evolution, starting by utilising the technology to automate mundane tasks, and gradually moving to apply it to our analytical work.
As we’ve read in the past, while AI at its core is good at collating relevant data and information at unprecedented speed, what it cannot replace (at least for the foreseeable future) is context, our human experience – our professional judgment and ethical considerations as accountants.
The tech offers ‘content’; we humans bring ‘context’. When we pair these two components, the potential is truly endless.
Business partners
Therefore, accountants should see AI and machine learning as being to our benefit, especially when it is we who are usually the ones who have access to data and are the conduit between businesses and regulators, operations and leaders.
Whereas previously we might not have had the luxury of time, spending most of our time simply on reporting, now, by automating so many of our processes, we can be real business partners to our CEOs and COOs.
For those who are content with simply raising manual journal entries and handling invoices, the future could be a worry, but for those who are interested in being ‘data-enabled’, what are the options?
You may continue to be in a conventional role, but with a deep understanding of data and technology
At one end of the spectrum, I have had former accountancy students and team members who have successfully ventured into the realm of technical roles in data science, software engineering and data analytics – with none of them having a formal background in technology.
But what they do have is the attitude and aptitude for anything data-related, to learn and re-learn through real-life projects, never shying away from taking on technology projects that might not necessarily be clearly defined, as we continue to explore the realm of possibilities with technology.
At the other end of the spectrum, you might want to continue to be in what one may consider a conventional role, such as audit partner, but with a deep understanding of what is possible with automation, data and technology.
This will enable you to provide leadership in the adoption and use of of technology in your team’s day-to-day work, and to speak the ‘data language’ when engaging with technology vendors or new staff hired to work on technology-enabled client projects.
Growing opportunities
Increasingly, there are also opportunities for roles in between those two ends of the spectrum. For example, you might prefer to sit within the finance team of a company but develop skills in database management (think SQL), programming knowledge (Python), data visualisation techniques (Power BI and Tableau) to be able to guide finance projects.
Careers calling upon technology skills can be achievable for most, if not all, ACCA members
This might include enterprise-wide finance data modernisation projects driven by either internal technology teams or vendors. Such individuals are increasingly valued by organisations, as they speak both languages – the language of data and the language of business and accountancy.
And at the end of it all, you can also opt to teach and train others, especially those who are eager to follow in your footsteps without a formal technical background. For me personally, that continues to be the most rewarding part of the path that I have taken – I continue to teach and train in educational institutions in Singapore, such as Nanyang Technological University.
Having moved between roles across the spectrum, I know that careers calling upon technology skills can be achievable for most, if not all, ACCA members if they put their heart into it.
More information
Listen to the webinar where Rina Lakhman and Tee Chong Yu discuss skills and roles in data analytics. See also Rina’s article on where to start with learning new data skills.
