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6 Seiten, Note: 1,4
To determine how humans perform better with machines, there has to be an understanding that both parties complement each other. Machines are more proficient at processing information and evaluating patterns from big data. Whereas humans get tired and slow down at some point which makes them prone to error, machines have the perfect accuracy, provided that the input and the task to be fulfilled have been entered correctly. Moreover, machines are better at storing memory, enabling them to process large amounts of information and recall it immediately (Whitney, 2017). When it comes to motivation, machines do not have needs that must be met for them to function properly, as described by Maslow’s hierarchy of needs. Maslow distinguishes between five motivational needs, starting with essential physiological needs, such as sleep or food, that are required for humans to exists (Maslow, 1943). An interrupted workflow induced by fatigue, resulting from a lack of sleep, leads to humans being less productive than machines (Whitney, 2017). However, humans are still superior to machines in different ways. For instance, we possess human judgement based on an understanding of context, nuance and gut feeling, or creativity and imagination, which can be imitated but never experienced the way we do (Whitney, 2017). In business, these differences or comparative advantages of the natural over the artificial – and vice versa – can be an immense opportunity for technological development. Drawing on the strengths and weaknesses of each party can help achieve higher performance. This will be further discussed in the course of this essay.
Technological unemployment, i.e. the loss of jobs resulting from advancing technology, is not a recent phenomenon but has been observed throughout history at multiple times (Frey & Osborne, 2013). One example is the beginning of the industrial age around 1800 when goods and services were first being produced by machines. These early machines were driving forces of the industrialisation that lead to increased productivity and more efficiency, but at the same time, they replaced many workers resulting in social unrest (Wisskirchen et al., 2017). As skill-level and job displacement have been proven to be interrelated, low-skilled workers, such as factory workers performing simple physical work, have a higher risk potential to be replaced than high-skilled workers. Coming back to the present, some occupations that are hard to automate by AI are those that involve managing people, creative work, decision-making, strategic planning and have only a small number of repetitive tasks (Dodgson, 2018). For instance, the responsibilities for auditors include analyzing and interpreting accounting statements prepared by others, examining areas of financial statements and note disclosure to ensure they meet accounting standards. Because this profession implies a high level of routine and a large number of repetitive tasks, the likelihood of the job being taken over by AI technology in the future is estimated to be 94% (“Will robots take my job? SOC Code: 13-2011.00,” 2018). The job of a consultant or business analyst on the other hand, is not likely to be automated by AI (13%), as it includes conducting organizational studies and evaluations, giving advice on strategy enhancement and on how to manage people (“Will robots take my job? SOC Code: 13-1111.00,” 2018). Other examples of humans outperforming machines include IT management and science, teaching professionals and creative occupations such as humanistic, social science and artistic professions (Wisskirchen et al., 2017).
Humans are adaptable, and people in organisations will adjust to technological progress. While some jobs will become obsolete and others will emerge, the majority of professions will go through significant changes. The field of audit is one of them, as discussed by Julia Kokina and Thomas H. Davenport in ‘The Emerge of Artificial Intelligence: How Automation is Changing Auditing’ (Kokina & Davenport, 2017). The paper gives an overview of the impact of AI on accounting and auditing, the implication of how new technology will change current responsibilities, as well as industry examples. For many years already, the field of audit has been supported by technology. A big part of the responsibilities of an auditor includes analyzing numbers, i.e. algebraic analysis, which is progressively undertaken by business intelligence and supported by analytical programs to visualise results (Kokina & Davenport, 2017). Non-routine cognitive tasks, which would usually be labour-intense if performed by humans, are more and more guided by AI-fueled programs (Frey & Osborne, 2013). Thus, the job of an auditor will have lower focus on the ticking and tying process and greater focus on the bigger picture painted by data (Kokina & Davenport, 2017). I believe, with the industry changing, managers have to understand the newly arising responsibilities and skills for successful auditing. That includes working alongside AI computers and algorithms to monitor their performance in internal and external audit processes, evaluating results, and also carrying out such tasks that cannot be conducted by AI assistance, e.g. client communication or translating audit and financial results for senior staff and board members (Kokina & Davenport, 2017). In general, the application of AI can be optimized through control and collaboration (Walker, 2017). In my opinion, supervision can be a crucial tool to reduce the possible risk of AI in business. Managers need to train employees to draw samples of data and challenge results received from intelligent accounting machines. In the long-term, I believe it is likely that management decisions will fully rely on the abilities of AI, as no human will understand the data and algorithms used by machines to make further recommendations.
With the evolution of AI, management and leadership of today’s companies will change, i.e. the responsibilities of managers on all levels will shift. According to a recent study by Accenture ‘The promise of artificial intelligence: Redefining management in the workforce of the future’, managers spend half of their time on administrative and routine tasks, e.g. resource allocation or scheduling; responsibilities that should easily be mastered by AI in the future (Kolbjørnsrud, Amico, & Thomas, 2016, ). With that newly won time, managers can put greater emphasis on judgement calls. Judgement is a distinctly human skill, which requires the application of experience, critical thinking, and strategy development and enhancement for critical business decision (Kolbjørnsrud, Amico, & Thomas, 2016, ). AI can assist with the provision of data-driven simulations to accelerate human learning. While the development of AI in business may evoke excitement, it will also lead to certain challenges managers will have to face. With a change in responsibilities, managers need to reconsider their respective roles. This will go hand in hand with specifying new operating principles and setting clear priorities for time allocation. A good manager of the future will also encourage collaboration between both humans and machines and adapt training, performance, and supervision to facilitate a well-working environment. (Kolbjørnsrud, Amico, & Thomas, 2016, ). When assessing the impact AI has on me, I am optimistic that AI assistance will make my life easier to some extent. Looking back at all the ways algorithms and software have improved my work as a consultant, I believe a broader application of AI will free time to do more meaningful work. This will also lead to work being more enjoyable, and it might cut some working hours, thereby benefiting my work/life balance (Walker, 2017). As a millennial, a good work/life balance is a priority to be happy with my job. Moreover, AI will help me be more efficient with my personal time and improve time management. It will help me get things done by scheduling and reminding me of appointments and sending alerts if I am missing something. Overall, it will give me more time to focus on thinking and creating, and things I enjoy.
Artificial Intelligence will revolutionize work and organisations in the upcoming years, simplifying workflow and increasing overall productivity. Contrary to the existing influence of computer technology, AI will reshape all major industries and all levels of management within them (Kolbjørnsrud, Amico, & Thomas, 2016, ). As technology changes, so will the people and their roles in organisations. Managers will face the challenge of integrating modern technology into the workspace and encouraging collaboration between humans and machines. Machines will take on administrative and routine tasks for managers and support employees with the automation of labour-intensive tasks. This way, human and artificial intelligence can unleash each other’s full potential for an effective and productive workforce.
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