How does AI support accountant jobs?
Accountancy and financial services have come a long way from its bookkeeping and payroll infancy, and like many industries, continue to evolve alongside digital transformation. Whilst it might appear as though technology can hinder how we comprehend financial services, we’re learning that these emerging technologies (such as analytic software and cloud services) are enriching disciplines like accountancy jobs as a whole.
Similar to many organisations, a widespread concern about incorporating technology into the accounting sphere was that technology will take over and automate existing financial tasks. Automation will not only replace human intervention altogether, but will also reduce creativity accountants have in brainstorming problem-solving strategies.
Enter the Covid-19 pandemic, and the world of finance as we know it alters dramatically. As one of the later industries to welcome the latest in technology (the other being healthcare, for these industries necessitate human contact as they deal with sensitive information) many organisations had to quickly adapt and incorporate software tools to serve a largely virtual consumer base.
Surprising to these organisations, technology such as big data helped control large volumes of information—altering the perspective in which technology serves to accommodate humans, rather than replace their roles entirely.
What are the current industry trends regarding technology?
AI systems reduce a large amount of an accountant’s workload by removing the need to manually input data and implement certain tests. These are usually the more administrative and tedious tasks in an accountant’s job, leading their focus onto more creative endeavours and assignments that require collaboration with team members.
Further, in managing data information in terms of quantity for employees to work with AI and use gathered data to analyse and interpret results. Like the above points, this allows for individuals to question data with more time and dedicate their expertise to relay their findings with more accuracy.
Another commonplace example discussed within finance communities is the implementation of virtual/augmented reality technologies. At first glance, this seems like a stretch—as these technologies are standard for video game software’s and appears as though there’s little room to amend in an accounting sphere.
However, the idea in transferring this technology for financial services is more simplistic—to use such technologies to visualise data when shared with stakeholders. Accountants often double as advisories and must showcase their findings and describe these to relevant business professionals. In this way, virtual/augmented reality will help bridge a connecting point between the research and communicating these to professionals from diverse departments and levels of expertise.
Lastly, blockchain has been introduced in financial services for some time as a means to support process development, auditing, and managing records. This potential has raised the demand for accountants with knowledge in blockchain technology and use it for the benefit of their role and an organisation. The technology itself can be quite intricate to understand, leaving these experienced accountants the added desirable quality of being able to teach it to others where supported.
What should finance leaders expect in the near future?
Leaders in finance (most notably the CFO) are used to making predictions for future trends to influence investments and minimise business risks. Although these should always be taken with a pinch of salt due to ever-changing and uncertain times, understanding current and future trends are important to ensure organisations keep on track in building a successful culture.
In terms of digitalisation and emerging technologies, this is perhaps the riskiest area in predicting due to the accelerating nature of technology generally. However, the following represents a collection of financial insights in this sphere:
- Real-time data: rather than produce regular and timely reports, data will be generated when it’s needed. It’s no longer useful to produce quarterly data when it can be gathered almost instantaneously. This will be used to satisfy both internal and external company needs.
- Self-service components: alongside data automation, many financial services will be automated to service customer needs. Particularly, this will be done by including voice recognition software that interacts with consumers via call to understand and vocalise solutions to their queries, removing the need for human intervention altogether. However, such solutions must work effectively, as when used improperly can turn bothersome for consumers.
- Technical talent: future finance jobs in Malta and abroad will hold impressing skill sets that include technical skills to keep up with workplace trends. Newer talents will be data scientists and business analysts, cultivating a shift in traditional finance departments. CFOs and other leaders should look for talent that serves the future of their organisation and ensure these align well together.
- Imperfect technologies: whilst we may enjoy the comfort's technology brings in removing the need to attend to mundane tasks, AI systems are still far from perfect. They do make fewer errors compared to humans on a quantifiable scale, however the data itself can appear nonsensical at times. A random comma and awkwardly spaced sentences can create new bothersome workloads for humans, and this is something we need to cater for until these systems improve.
- Shared insights: immense data collection allows for companies to conduct internal research that can influence market trends. Although this is something already seen in the financial sphere, the sheer quantity of data will generate large reports, significant to generalise across populations. Whilst many organisations are comfortable in sharing valuable insights and knowledge with each other, one drawback is that internal information is open to criticism on a public scale.
On the whole, a once feared technological phenomenon is now a sought-after support mechanism for financial services internationally. Rather than replace, technology works to help humans in taking care of tedious tasks and allowing individuals the time and ability to prioritise their workload. Nevertheless, AI systems are far from perfect, and whilst it is an exciting time to implement these emerging technologies, we need to look out for their present limitations to ensure optimal benefit reached in organisations for the future.