Introduction
Artificial Intelligence is one of the highly celebrated forms of technology that has played an imperative role in improving service provision efficiency and quality. Virtually all sectors and industries have directly benefited from various technological inventions. Through technology, work has been made easier with machines used to doing most of the work (Bond & Gasser, 2014). Artificial technology is one of the most significant breakthroughs in technology. Artificial intelligence, commonly abbreviated as AI, refers to the imitation of human intelligence in machines and equipment set to think and act like human beings, mimicking their actions (Russell & Norvig, 2016). Artificial Intelligence may also be applied to any machine that shows traits allied to a human mind, such as learning and problem-solving. The research study will therefore offer a comprehensive discussion on Artificial Intelligence.
Types of Artificial Intelligence
Artificial intelligence is categorized into four; reactive Artificial Intelligence, Limited Memory AI, theory of mind AI, and self-aware AI (Zuiderveen Borgesius, 2018). Reactive AI is the most basic category of artificial intelligence, which is automated to offer a predictable yield based on its input (Jiang, Jiang, Zhi, Dong, Li, Ma & Wang, 2017). Reactive machinery always reacts to identical circumstances in the precise same way every time and cannot learn activities or conceive of past or future. Examples of reactive AI are; The Netflix Recommendation engine and Deep Blue (Zuiderveen Borgesius, 2018). On the other hand, with limited memory AI learns from previous actions, hence building experiential knowledge by observing actions or data (Jiang, Jiang, Zhi, Dong, Li, Ma & Wang, 2017). This type of Artificial Intelligence uses historical, observational information to amalgamate pre-programmed data to make forecasts and perform multifaceted classification jobs. It is the greatest widely-used type of AI today. Theory of mind AI is regarded as an emotionally intelligent robot that resembles and acts like a real human being. With this category of Artificial Intelligence, machines can acquire true decision-making competencies similar to humans (Zuiderveen Borgesius, 2018). Lastly, the most progressive type of AI is self-aware Artificial Intelligence. When machines can be conscious of their feelings and the emotions of others around them, they will have a level of consciousness and intelligence similar to human beings (Jiang, Jiang, Zhi, Dong, Li, Ma & Wang, 2017). This type of AI will also have desires, needs, and emotions.
Benefits of Artificial Intelligence
One of the most outstanding benefits of this technology is that it enables the execution of relatively complex tasks and activities without high cost outlays. Artificial intelligence further argues for the capabilities of differently-abled people (Yeasmin, 2019). Other important advantages of the technology include; reduced human error, always available, unlike humans that could be absent from work, offers digital assistance, provides unbiased decisions, and gives new inventions that offer solutions to complex problems (Yeasmin, 2019). The technology, therefore, makes work easier and less problematic.
Challenges Facing Artificial Intelligence
Despite having outstanding benefits to users and organizations. A close examination reveals that Artificial Intelligence attracts several disadvantages. Artificial Intelligence technology is highly expensive. Creating a machine that can simulate human intelligence requires a lot of money, other resources, and time (Russell & Norvig, 2016). Moreover, AI requires the most current hardware and software to operate; the software must stay updated, which is costly in the long run. Other disadvantages include; increased unemployment as human labor is replaced by machines, which makes humans lazy since most of the work is done by machines hence lowering the level of creativity.
Solutions to the Challenges facing Artificial Intelligence
To effectively address Artificial Intelligence’s challenges, it is imperative for companies using AI technology to work closely with skilled business analysts to determine their processes and IT systems that could benefit from artificial intelligence (Bond & Gasser, 2014). Considering various ethical issues that may prevent an organization from using Artificial Intelligence to the fullest is another imperative mechanism for solving the challenges of Artificial Intelligence (Yeasmin, 2019). Lastly, extensive research should be conducted to establish solutions to the challenges while determining how to merge human labor with technology.
Robotic Process Automation
Robotic Process Automation (RPAs) is software programmed and designed to automate high volume and repeatable tasks previously performed by a human. Also, they can interpret the available data, trigger responses, and communicate with other digital systems. AI is essential in automation processes, data trend analysis, and forward-looking intelligence to strengthen human decisions. Enterprise applications such as Salesforce, SAP, or Workday increasingly incorporate AI-based systems (Russell & Norvig, 2016). Research use of AI creates a long-term competitive advantage for companies by decreasing the costs of repetitive tasks and human error, allowing people to focus on other meaningful works (Bond & Gasser, 2014).
Future of Artificial Intelligence
Generally, the revolution of artificial intelligence is an attempt to replace, extend, and improve all tasks currently performed by humans, making them more efficient hence providing humans with real competition. The expected changes and consequences from the integration of AI technologies are difficult to predict due to the following two reasons; the continuous development of an intelligent computer program with the ability to develop new applications and techniques. Also, the consequence of this development is not identified (Russell & Norvig, 2016). Secondly, it is likely that at some point, AI technologies can perform non-repetitive and mental tasks, replacing humans currently responsible for these tasks. As a result, the company’s dependence on AI technology will increase in the long term, making it difficult to predict the effect of dependence. Pwc’s international job automation study estimates that the share of jobs at a potentially high risk of automation will be no more than 3% by 2020 (Yeasmin, 2019). However, the estimation of the longer-term automation is currently not available. Considering the arguments mentioned above, there is a clear potential for the growth of artificial intelligence technology soon.
Technology and their Usage
Management People
One of the critical success factors for any firm is having the right employees in this era of artificial intelligence. Employees are expected to have more exceptional skills necessary for the management positions enabling efficient operation of the firm and proper application of AI compared to their main competitors. Therefore, favoring talented and high-performing employees, those able to initiate innovative ideas and winning strategies, is necessary since it promotes again in competitive advantage (Nadimpalli, 2017). According to PwC’s research, a collaboration between AI specialists and economists, analysts, and traders in various sectors and industries results in the development of a design and training in AI technology to define needs effectively using the new techniques available (Nadimpalli, 2017). The Chief Innovation Officer (CIO) and the Chief Artificial Intelligence Officer (CAIO) strictly supervise the analysis and expansion of the AI-driven technologies in dominant and successful firms in the AI revolution (Russell & Norvig, 2016).
The United States and China are the artificial intelligence pioneer countries. AI companies in the United States absorb 66% of all external investments as of 2016, with China coming second with 17 %. Both countries have a national strategic growing plan backing up a tremendous budget funding for AI initiatives (Nadimpalli, 2017). However, it is expected that China will have the most significant impact from AI, with a 26 % increase in the GDP by 2030, with the United States having a 14 % boost potential. Also, other countries are taking steps to develop an AI technology plan. The UK leads the way after releasing a budget plan to improve data access, AI skills, and research (Nadimpalli, 2017). Also, Japan released an AI technology strategy plan which aims to incorporate AI in other technologies such as the internet of things, autonomous vehicles, and the blending of physical and cyber-spaces.
In conclusion, it is right to infer that Artificial Intelligence has played an imperative role in revolutionizing how work is done in various industries, improving both quality and efficiency. Artificial intelligence reduces the amount of time used in doing certain tasks; it further allows the completion of certain complex jobs without significant outlaws, besides augmenting the capabilities of differently-abled individuals. However, limited knowledge, trust deficit, data security, and privacy are among the problems facing Artificial Intelligence. However, more research should be done to reduce the challenges and negative effects of Artificial Intelligence. Strategies for merging Artificial Intelligence and human labor should be established to reduce the number of people losing their jobs due to the use of this technology.
References
Bond, A. H., & Gasser, L. (Eds.). (2014). Readings in distributed artificial intelligence. Morgan Kaufmann.
Jiang, F., Jiang, Y., Zhi, H., Dong, Y., Li, H., Ma, S., … & Wang, Y. (2017). Artificial intelligence in healthcare: past, present, and future. Stroke and vascular neurology, 2(4).
Nadimpalli, M. (2017). Artificial intelligence risks and benefits. International Journal of Innovative Research in Science, Engineering and Technology, 6(6).
Russell, S. J., & Norvig, P. (2016). Artificial intelligence: a modern approach. Malaysia.
Yeasmin, S. (2019, May). Benefits of artificial intelligence in medicine. In 2019 2nd International Conference on Computer Applications & Information Security (ICCAIS) (pp. 1-6). IEEE.
Zuiderveen Borgesius, F. (2018). Discrimination, artificial intelligence, and algorithmic decision-making.
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