Technology is altering all aspects of business life and compelling adaptation in processes and product utilization.
Disruptive technologies usually bring in cheaper and simpler products with features valued by new customers and often cause radical industry changes. In the era of disruptive technologies, accounting will inevitably change and be progressively automated in order to continue to be of great importance to the enterprises and stakeholders (Christensen & Raynor, 2013).
The world driven by technology is filled with potentials and challenges – Cars that drive themselves, machines that read X-rays and algorithms that respond to customer-service inquires etc. are all manifestations of powerful new forms of automation.
These technologies increase productivity and improve our lives as their use will substitute for some work activities humans currently perform.
The fast pace of technological innovation continues to interrupt traditional processes in all spheres, the accounting profession inclusive.
Consequently, the author examined the likely effects that disruptive technologies will have on both the profession at large and accounting education specifically (Chanyuan, Jun & Mikkos, 2018).
They provide suggestions for educators and universities on how to shape their curricula to meet the needs of the new environment. It is predicted that the traditional mix of jobs in accounting firms will change substantially, and accountants will need to learn new skills when the more traditional tasks become automated and the technical maintenance and analytic needs of the work increase substantively.
A major wave of educational change is also emerging with the advent of distance education, various forms of unorthodox training, and a large set of new learning needs. Given these disruptive information technologies, business measurement (accounting) and assurance (audit) will inevitably change and be progressively automated in order to continue to be of great importance to the enterprises and stakeholders (Li, Duo & Mikkos, 2017)
Concept of Disruptive Technology
The term “disruptive technology” as coined by Christensen (1997) refers to a new technology having lower cost of performance measured by traditional criteria but having higher ancillary performance.
Christensen finds that disruptive technologies may enter and expand emerging market niches, improving with time and ultimately attacking established products in their traditional markets.
This concepti ways. By emphasizing only “attack from below” Christensen ignores other discontinuous patterns of change, which may be of equal or greater importance (Utterback, 1994; Acee, 2001).
Further, the true importance of disruptive technology, even in Christensen’s conception is not that it may displace established products, rather, it is a powerful means for enlarging and broadening markets and providing new functionality.
In Christensen’s theory of disruptive technology, the establishment of a new market segment acts to channel the new product to the leading edge of the market or the early adopters. Once the innovation reaches the early to late majority of users, it begins to compete with the established product in its traditional market.
Robotic Process Automation
Robotic Process Automation (RPA) automates repetitive tasks via the use of software robots that mimic human motions on a screen and extends automation to interfaces that are complicated or lack an Application Programming Interface (API).
That is why RPA is excellent for automating activities that are typically performed by humans or need human interaction. Responsive robots adapt to changes in the display and maintain process flow in the case of a change.
When RPA robots are powered by Artificial Intelligence-based machine learning, they are capable of recognizing screen objects (even the ones they have never seen before) and mimicking human intuition in understanding their function.
They read text (for example, text boxes and links) using optical character recognition (OCR) and visual components using computer vision (for example, shopping cart icons and login buttons).
Artificial Intelligence (AI)
According to John McCarthy “the father of Artificial Intelligence”, It is “The science and engineering of making intelligent machines, especially intelligent computer programs”.
Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software to think intelligently, the way intelligent humans think.
AI is accomplished by studying how human brain thinks, learn, decide, and work while trying to solve a problem, and then use the outcomes of the study as a basis of developing intelligent software and systems.
While exploiting the power of the computer systems, the curiosity of human lead to wonder, “Can a machine think and behave like humans ?” Thus, the development of AI started with the intention of creating similar intelligence in machines that we find and regard high in humans.
Artificial intelligence (AI) is the ability of a machine or computer to replicate the attributes of human brain. AI makes use of a range of technologies to empower computers with human-like intelligence in terms of preparation, acting, perceiving, and detecting (Cozac, 2021).
Artificial intelligence systems are sensitive enough to detect their surroundings, recognize objects, make decisions, settle conflicts, learn from experience, and simulate daily situations. These abilities are combined to accomplish activities that are usually undertaken by professionals.
According to Cozac (2021), artificial intelligent systems adhere to specific principles. It is founded on the reverse engineering of human abilities and traits transferred to a computer.
The system utilizes computer power to perform tasks that are beyond the capability of average human. The machine must be trained to recognize and respond to certain behaviours. It uses historical data and algorithms to build propensity model.
Through experience, machines gain the capacity to perform cognitive functions usually reserved for the human brain. The system self-learns from the features or patterns in the data.
Concept of Accounting Profession
A common international definition of the term professional accountant that could be widely understood, faithfully translated, and effectively applied would have utility to all stakeholders.
It would support the International Federation of Accountants (IFAC) mission to serve the public interest by contributing to the development, adoption and implementation of high-quality international standards and guidance. It would acknowledge the applicability of the international standards to professional accountants is not limited to those who have membership in IFAC member organizations.
Further, while it may not be possible to achieve a common definition that satisfies all conceivable objectives, a common international definition, descriptive in nature, could serve as a universal foundation from which further adjustments could be made on different national levels and in different professional contexts – acting as a focal point of consideration for the diverse functions of professional accountants.
The term professional accountant describes a person who has expertise in the field of accountancy, achieved through formal education and practical experience, and who: Demonstrates and maintains competence; complies with a code of ethics; is held to a high professional standard; and, is subject to enforcement by a professional accountancy organization or other regulatory mechanism.
This definition encompasses the first two descriptive levels by stating what a professional accountant is and what a professional accountant does.
Disruptive Technology and Accounting Profession
Recently, disruptive technologies such as robotic process automation (RPA), artificial intelligence (AI), blockchain, smart contracts, and advanced analytics have reshaped existing business models and facilitated the emergence of new ones wherein repetitive and mundane tasks are becoming less important and the need for high-level skills increasing. Though it will still take some time before deriving own algorithms and refining them in time (Shimamoto 2018).
“Teaching” the computer by using data sets requires special attention to quality and internal control procedures. This should be implemented to mitigate the risk associated with inherent biases and other limitations of AI applications.
Among the technical skills are the big data analytical skills as “there is an increasing focus on Big Data for the accounting profession” (Gamage 2016). As stated by Ellis King, the manager of a global professional services recruitment company, Morgan McKinley, there is a big shift in the required skills for entering the labour market and big data analytics plays a central role.
Even young and less experienced accountants are
10 most important communication skills for accountants are: presentation skills (storytelling), credibility, confidence, friendliness, eye contact, understanding people’s point of view and ability to give and receive feedback (Jazaie 2017).
On the other hand, critical thinking skills have been “widely accepted as a key requirement for success in most practical and professional spheres, not just accounting”, since at least the 1980s (Sin, Jones &, Wang 2015). The ability to think critically was even then considered as a prerequisite for a successful transition from the classroom to the professional workplace. The development of critical thinking needs to become a main objective in the accounting.
The automation of repetitive tasks will cause substantial reduction of the work-force needed for traditional assurance work, but it will also lead to an increasing need for employees who possess skills such as IT and data analysis.
Consequently, the advent of disruptive technologies is forcing members of the accounting profession to learn new skills, especially IT, statistics, and modeling. To satisfy the constantly changing needs of the workplace, the education model should also be up-to-date.
Both the accountancy professional bodies like ICAN and Financial Reporting Council of Nigeria (FRCN), which develops the qualifying professional examination, and standard setting body in Nigeria should focus more on higher-level skills, especially analytical, critical, and innovative thinking skills, and decrease the emphasis on memorization and the mechanical application of rules.
The institute should also consider increasing the content of IT, cybersecurity, and data analytics within the examination space. Business schools for accounting programs are encouraged to open new courses related to IT and data analytics to diversify the course
pool.
Alternatively, accounting educators may also feel it useful to blend big data analytics and IT into existing traditional accounting courses such as financial accounting, managerial accounting, auditing, and taxation. This requires accounting educators to change their mindset and expand their skill sets; while this may take time, PhD students who possess these new skills may help facilitate the change.
Traditional business schools such as study Centres should also explore new teaching models, such as online teaching, course modularization, or a hybrid of online and physical teaching.
Business schools can also consider offering special certifications for new course modules, such as cybersecurity and audit data analytics. Classes can be taped and stored online for the purpose of review and reuse.
Educators should also encourage a philosophy of lifelong learning and teach students to learn new things and adapt to the changing environment, cultivating accountants who are prepared for the future.
these technologies will affect the workplace significantly , the current “entry-level” jobs that require no or low-level cognitive skills may eventually disappear.
According to McKinsey Global Institute (2017), it has been estimated that at least 50% of the work that accountants and other professionals are paid for have been automatable through technologies, with additional 15% process to be automated in the nearest future.
One of the most required skills is the technical expertise in machine learning and the depth of knowledge depends on the size of the organisation, investment policy and innovation strategy.
Despite these factors, it is important for accountants to understand the significance of data and data quality. Machine learning implies recognition and application of patterns based on existing data points or examples,
expected to be creative with data and produce useful analysis thus contributing by forecasting potential growth, new markets or competition (King 2014).
According to some recent research estimates, 77 per cent of companies, which exploited the benefits of data analytics, achieved better financial performance (Gamage 2016).
Moreover, decision-making driven by data leads to 5-6 per cent efficiency gains depending on sector specifics (Tene & Polonetski 2013). Machine learning “also benefits from having very large data sets – the more data points there are, the more times the model can run, learn and test the accuracy of its results” (ICAEW 2014).
In addition, communication skills and critical thinking will become increasingly important in the AI age (ICAEW 2017). According to Jazaie (2017), among the
education.
Leadership skills will become more important with the changes of accounting roles. As the professionals increase their participation in company’s strategic management and collaboration and partnership with other parts of the organisation, certain types of leadership will become indispensable.
Among them are: strategic and organizational leadership; coaching and mentorship; a strong sense of ethics and cross- functional leadership.
Conclusion and Recommendation
It is really a disturbing fact that accounting profession has been estimated as having high probability for automation in some well accepted, among academics and practitioner empirical studies.
But we have to neglect such dark prophecies as the profession is far away from its inglorious ending. AI should be considered as a beginning of its renewal and will once again prove its potential to adapt to the recent changes in business environment and the shift in management requirements.
In fact, accountants can benefit from the intelligent systems by taking advantage of AI capabilities to solve broad problems (ICAEW 2017).
Emuebie Emeke,
Internal Audit Department, Union Bank Plc
