Can Human Auditors be Replaced by Artificial Intelligence (AI)?
The rapid development of Artificial Intelligence today precipitated the topic of replacement and acquisition of several human jobs. Citing The Telegraph UK, accountants and auditors are amongst the most likely professions to be replaced by robots. According to a study of over 2,000 work activities in more than 800 occupations by the McKinsey Global Institute released in 2016, the easiest jobs to automate are those involving predictable physical activities such as assembly line work in manufacturing. The next easiest jobs to automate include data collection and processing activities. At the other end of the spectrum, the hardest activities to automate are those that involve managing and developing people or require deep expertise in decision-making and planning (Chiew, Yeong, 2017). Since auditing is not based solely on collection of data and activities and further analysis and understanding from the auditor is required to conclude whether the financial statements are presented fairly, it is less likely for auditors to lose their jobs in the near future.
1.1 Artificial Intelligence
Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans (techopedia, N.d.). AI makes it possible for machines to learn new experiences, adjust to new inputs and thus, perform human tasks. It was first coined in 1956 and today, it formed an integral part in our healthcare, sport, manufacturing and retail industry due to increased data volume, advanced algorithms, improvements in computing power and storage (“Artificial Intelligence- What it is and why it matters”, N.d.). The difference of AI and hardware driven machines lies in the capability of performing frequent, high-volume, computerized tasks reliably, with incredible accuracy and adaptation to progressive learn algorithms (ibid.). A popular example of AI is Apple’s internally developed Siri.
1.2 Overview of audit profession today
Technology has revolutionized the way businesses are conducted today. Maintaining operational efficiency, financial inclusion and greater insights to data are inevitable without the adoption of technology (Freeman, Drake, N.d.). Thus, the techniques of auditing businesses eventually change to balance the transformations in business environments.
Auditors need to adapt to the changing needs of users and therefore, provide meaningful interpretations of data. An example is to provide the holistic view of the state and prospect of the company (Cohen et al. N.d.). Automation makes it possible to remove the more time-consuming, mundane, process-heavy work that auditors did manually, leaving them areas of the audit that matter most, such as identifying potential risks and responding to them (Sidhu,2019).
The objective of the report is to analyze whether Artificial Intelligence can replace the role of auditors, through their growth and usage in the industry twenty years from now. The following sections will discuss in further details the role of human auditors to the technology they adopt, as well as the current auditors’ and students’ anticipation towards the technological changes.
2. Findings and Discussion
2.1 Artificial Intelligence in Audit
As we have discussed in the preceding section, Artificial intelligence refers to machines undertaking tasks which require some kind of ‘intelligence’, including activities such as learning, knowing, sensing, reasoning, creating, achieving goals and generating and understanding language. Artificial intelligence involves using computers that can simulate human intelligence. AI software uses fast, repetitive processing and algorithms to “learn” from large amounts of data and complete decision-based tasks (“what is AI”, N.d.). They provide outputs that can be extremely accurate, replacing and, in some cases, far superseding human efforts (“Artificial intelligence and the future of accountancy”, N.d). Recent progress in AI has been based on techniques such as machine learning, deep learning, and algorithms. These machines learn how predict values, or classify objects through statistical analysis of large amounts of data, rather than through explicit programming (Freeman, Drake, 2015). Studying the popularity of AI today, new products and services will be developed for more efficient audit. (Anwer, Shabbir, 2015).
During the planning stage of the audit, AI acquire initial knowledge of the client and their industry. AI can collect, aggregate, and examine data from the financial statements, operational methods and organization structure. At the contracting phase, AI will estimates the number of hours the engagement would require and calculates audit fees. Next, AI assesses the internal control, and risk factors of the audit client. Flowcharts, narratives, and questionnaires will be examined to identity anomalies and then reported. AI depends on pattern recognition and visualization method at this stage. For substantive testing and details balance stage, data quality and provenance from the entire population is checked. Lastly, a conclusion is reached based on the findings of AI (Issa et al, 2016).
These AI technologies facilitate auditors to automate those tasks that have been conducted manually by humans for decades, and thus enabling them to fragment what was once a tradeoff between speed, cost, and quality. Auditors can plan their focus on improving quality by evaluating advanced analytics, spending additional time providing insight and applying better professional judgement (Greenman, 2017). Today, manual vouching and clerical tasks have been replaced by software, along with the development of data analytics for easier access to data. Data analytics is the science of examining raw data for the purpose of drawing conclusions. Auditors utilize data analytics in various forms for years, but rapidly decreasing technology storage and processing costs made data analysis even more attractive because of the potential for significant scale and depth. Machine learning can be used to automatically code accounting entries, while deep learning of AI can analyse unstructured data like email, social media and conference call for fraud detection. Another example of AI in the audit field is review of large number of contracts in a shorter period of time. Important information from an agreement usually a lease contract is extracted using a pre-selected criteria, and a summarized information is conferred (Boillet, 2017). In addition, auditors do not have to take samples as an entire population can be audited with the help of AI. All the former mentioned effects of AI generates more efficient and systematic audit procedures, and thus, a higher quality audit is achieved.
2.2 Role of auditors with technology they adopt
Even though auditors are supported by the benefits of Artificial Intelligence, the basic role of auditor- understanding the clients’ business and its potential risk, determining compliance with established standards, compilation of audit evidence, and exercising professional scepticism is not fully replaced by AI. Additional judgement is required to further process, interpret and communicate data to audit clients, which is what AI today is not capable of doing. The technology adopted will help them eliminate repetitive, tedious, and mundane tasks. The job of auditors hence broadens beyond the degree of only looking at financial statement to come up with an opinion, but to provide an assurance service as well that can mitigate the risk of client’s company (Freeman, Drake, N.d.).
2.3 Future of auditing twenty years from now
It is impossible to predict the extent to which computers will replace human decision-making over the next 20 to 30 years (“AI and the future of accountancy”, N.d.). Automation will be used for more tedious tasks so that auditors can use their expert judgment for more pressing issues (Lombardi et al, 2016). This might cause audit methods to experience an unprecedented transformation to natural language processing and equipment of remote-operated drones and mobile tools to inspect assets. Citing the Journal of Emerging Technology in Accounting Vol. 13, No. 2 Fall 2016 pp. 1–20, the big four auditing firms are currently investing large amount of funds for their research and development of AI. They are expecting the technology can analyse anomalies in large amount of financial data or a contract analysis system to create cognitive models to review and summarize complex documents. The focus will be implanted on development of Deep Learning in Image Recognition, Deep Learning in Language Analysis, Deep Learning in Natural Language Classification and Deep Learning in Speech Recognition.
Deep learning in image recognition enables visual recognition techniques that understands the content of an image or video taken by drones and surveillance cameras and identify the object automatically. For example, deep neural network, which has the ability to learn from the abundantly existing product images, and then analyses inventory images captured by automated drones. Thus, it automates physical inventory checks of assets and fraud detection. On the other hand, Deep learning in conjunction with linguistic analysis is able to automatically analyse text, including both HTML/text documents and webpages. The trained text analysis model is capable of understanding the meaning of the given text, which in turn can be used for pattern identification. The machine will extract attributes from conference call transcripts and management discussions.
Deep Learning in Natural Language Classification understands the meaning of the text, and can be applied to classify it to the text file. It will be applied to group earnings conference call transcripts to either “fraudulent” or “not fraudulent” based on the established criteria, and a follow up procedure is required for potential frauds. Lastly, Deep Learning in Speech Recognition transforms audio files like phone calls and presentations into searchable audio data or transcript in written form. However, it might be difficult as speech contains error, accent and environment noise.
2.4 Can Human Auditors be Replaced by AI
As we have discussed earlier, advances in technology and the adoption of AI in the audit field will enhance the effectivity and hence, the quality of the audit done. However, it is inconceivable for the job of auditors to be replaced completely by AI. An auditor’s judgement, experience and sector knowledge remain essential. It is their deep understanding of the audit process allows technology to be seamlessly integrated into the areas where it will make the greatest impact (Sidhu,2019). Understanding the business and its environment, setting up benchmarks for material misstatements and providing an opinion requires human intervention as AI machines’ learning capability is limited to a certain extent. Simpler tasks, however such as collection of audit evidence through samples, reviewing contracts, and detecting irregularities in documents can be replaced by machines equipped with AI. Bringing up rear, human auditors will still dominate the audit process in the upcoming years and AI technology will empower and enable them to make key judgments and deliver high-quality audits despite the exploding data and ubiquitous information.
In the long run, auditors are constrained to work jointly with AI, by interpreting and communicating the results provided by AI. According to Deloitte, the concern of losing jobs because of AI is dismissed as the growth of recruitments in the audit field grew by approximately two thousand people. It was concluded that the evolution in technology has recast the talent mix- the skillsets and professional development needs of the auditor have evolved as well.
2.5 Auditors’ and students’ anticipation towards AI
According to Deloitte’s predictions, finance talent models are evolving rapidly specifically on the ability to translate data outputs for people. Combination of the right technology and the right talent and skill sets is required to thrive in the digital future (“New skills for the digital era”, N.d.). Auditors can embrace the advances by continuously learning to work alongside with AI and maximizing the benefits it offers. Extension of audit procedures to overcome risks arising from the implementation of Robotic Process Automation and Cognitive Intelligence, strategic planning on the audit procedures, training and recruitment of competent personnel will be necessary (“Advising on the risk of new technologies- internal audit on the age of digitalization”, N.d.). In line with the auditors, students are being more exposed to technology today. Schools and university have adopted AI tutoring systems which can help them with basic mathematics and writing (“Ten roles for AI in education”, 2018).
Global spending on artificial intelligence is rising and shows no sign of slowing down. Organizations are expected to invest $35.8 billion in AI systems this year, up 44% over last year, according to International Data Corp. AI spending is projected to more than double to $79.2 billion by 2022. This is also true in the field of audit. Artificial Intelligent has the ability to revolutionize the profession by gaining access to information and streamlining workflows. Repetitive and transactional tasks, will be replaced by machines allowing auditors more time to apply their expert judgments to riskier, more pressing areas. Besides, automation reduces the likelihood of biases in processing information, accordingly, external auditors can rely more on the work of internal auditors. This shift will lead to a decrease in audit time and subsequently the audit cost (“the current state and future of audit profession”). Benefits offered by AI will outweigh the drawbacks it brings. The elimination of physical inventory checks, manual vouching or taking samples and bearing the sampling risk allows auditors to focus on problems that require their judgement. Risk of embedding the wrong logic, algorithmic bias, and risk of cyberattacks can be dealt with extensive research and development (Boillet,2018). Nevertheless, AI and human developed machine learning are not equipped with the ability to apply professional judgement and consider factors beyond its programmed logic. This grants the opportunity for auditors to preserve and hereinafter enhance the quality of their job by working in apace with AI. Not only auditors, students today are anticipating the trend too. Schools and universities have reshaped their goals of not only educating through traditional methods, but to cater the skill of working with technology. To conclude the report, audit is not becoming a machine led industry and AI will not replace the role of auditors. Instead of replacing the role of the auditor, automation is enhancing it, equipping audit professionals with more reliable and detailed insights to build greater trust and confidence in the capital markets. (Sidhu, 2019).
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