The Ways in which Artificial Intelligence Can be Applied into Businesses

Artificial intelligence onward referred to as AI in this document is an innovation that has allowed today’s generation to be witnesses to the makings of history. Though AI has been an advancement that has been in the overall market for over 50 years, progress and adaptation within this sector has only recently been seen. As defined by Skilton (2017), Artificial Intelligence is the capacity of a computerized system to display intelligence which can be harnessed into improving the efficiency and quality of both operations and system within a firm or industry.

The display of this intelligence by AI is done without the system following a system of instructions that are hand coded. Most importantly, the intelligence that the system displays is similar to human intelligence. Ransbothan et al (2017) use the definition provided by the Oxford Dictionary adding that the tasks displaying human intelligence include recognition of speech, visual perception, the easing of decision making and translation from one language to another. According to Skilton’s brief, AI will most probably induce the Fourth Industrial Revolution thus bringing about immense changes in production and the profits made by majority of the firms that will chose to adapt the developments.

To date, a number of significantly large technology companies have made strides towards helping AI to further develop into a useful commodity. According to a discussion paper by McKinsley (2017), leading companies such as Amazon, Google and Baidu have invested billions in the research and development of AI systems believing and already having seen great returns to the evolution. Though a lot of news and coverage is being provided by media on the benefits and advantages of AI, businesses have been very slow to adopt these innovations. McKinsley (2017) points out that businesses are hesitant to making large investments towards AI first because of the uncertainty of the market. This is not the first time that AI systems have been introduced in the market. AI has endured highs and lows since the 1940s. Additionally the most significant question of where to apply the systems to in different industries and the where these systems are purchased and acquired are questions that need answers before any long lasting decisions are made. And as majority of companies within the economy are profit maximizers another question thus needs to answered. Will an investment into AI offer significant returns? Consumers and employees are also scared of the impact that AI will have on their livelihoods. Some experts see it as an international threat while others see it as a weapon of knowledge based mass destruction. Biotechnology has advanced to the point of enabling scientists to modify any kind of DNA leading to devastating results. However, majority of the population is concerned of the ability of robots to replace them at the workplace and make them obsolete (Walker, 2017).This report therefore intends to bring into focus the ways in which artificial intelligence can be applied into businesses and the ways in which it can bring benefits both financially and operationally to firms that are struggling. The paper begins with a discussion of the current status of AI system application in the current economy.

Current Status and Future Expectations of Application of AI in Businesses

As mentioned before, there has been a lot of talk in AI but very little intake by firms in almost all sectors. A study by Ransobotham et al (2017) performed an analysis of 3,000 businesses from 112 countries and found the adoption levels of AI to be barely a quarter as shown below:

McKinsley (2017) however points out that firms or corporations with certain characteristics are the ones that seem to have adopted AI have certain characteristics. The authors define these corporations as early adopters. The first characteristic of early adopters is that of industries that have been seen to invest in digitization in the past. The industries with this characteristic are mostly from the financial and telecommunication sectors. The automotive sector is also recognized for high adoption of AI due the sectors acceptance of robotics during assembly. Sectors such as health and education are very low on adoption. Secondly, a factor that both McKinsley and Ransobothan et al (2017) agree on is that larger companies tend to be early adopters as compared to reasonably sized firms. Ransobotham et al specifically indicates large firms as those with at least 100,000 employees.

The third characteristic for early adopters is those of corporations that adopt a number of AI technologies into their processes and not just one. The adoption of AI into core processes in their operations is also another characteristic of early adopters. A very significant characteristic of early adopters is the level of support from top management. McKinsley (2017) states that corporations that have successfully adopted AI have had almost twice or more of the support from top executives as compared to the rest of the firms. Early adopters also are seen to adopt the technologies due to their focus on growth of both revenue and the market share. A reduction of cost of production is only secondary to the considerations of adoption.

However, though some companies may have all the above characteristics, they may simply not adopt. They are a lot of challenges that need to be considered before adoption. Apart from the difficulty of figuring out in which section of the business AI can be applied and benefit the business, the top executives need to consider other investment priorities competing with AI investments, the unclear value of it to the business, the expense of acquiring the required talent and the security and ethical concerns that will arise with its application. To understand how AI may bring value to a business one first needs to understand its applications. The next section discusses five major ways AI can be applied to businesses.

Applicable AI systems on business

In this report, focus is placed on narrow systems, these are systems that perform one particular task and thus assist in solving problems faced by businesses. These technology systems include: machine learning, language, robotics & autonomous vehicles, computer vision and virtual agents. According to McKinsey (2017), machine learning is based on algorithms which are similar to previous software. However, in this case the algorithms learn from the data provided without following specific instructions in place. Robotics, autonomous vehicles are AI systems act on information provided. Virtual agents are AI systems used to have conversations with human beings and thus tend to be used mostly in solving customer facing transaction problems. For example, the American Insurance Company uses a virtual assistant named Eva to handle the customer’s financial transactions (Tata Consultancy Services, 2016). These various applications may assist businesses in the following broad functions according to Tsai (2017). First, AI application gets rid of tasks that are considered repetitive and consume a lot of time. This means ridding the need for personnel to supervise vehicles in the assembly line or the loading and packaging of factory commodities. Also, the application of AI eases the processing of data that is too much or very complex. Individuals may take too much time to process this data keeping customers waiting. For example, paralegal in the legal sector do not have to peruse through every document collecting details concerning the preparation of a contract. AI systems make it possible for real time decisions to be made within a dynamic environment such as the stock market. Lastly, the application of AI technologies allow for the performance of activities that are not within human capabilities.

Benefits of AI to Businesses

To be able to fully capture the benefits of AI to businesses, one needs to capture the economic advantages that will be found due to a dive into this investment. McKinsley (2017) categorized the pathways through which AI can do this under the four P’s that is for the first P being Project which means the anticipation of future logistics such as supply, demand, trends and the performance of assets and liabilities. The second P is for Produce which stands for the improvement of production levels in terms of quality and quantity but at lower costs. The third P stands for promote which stands for efficient marketing strategies that improve the market share of corporations. And the last P stands for provide which means that the application of AI will improve the kind of experiences users are having making them more personal and convenient. Thus for example in the education sector the application of AI systems can assist through the four pathways in the following ways: project the demand in the market and determine the motivators for performance in students, it can help in producing better results by automating the tasks set for educators and assist in the formation of better learning groups in terms of objectives and lastly it can provide virtual coaches that train the learner with a learning curriculum that fits their abilities thus easing the human educator’s tasks.

Therefore, though AI applications depend on the type of data being fed to the system, if applied well the system can increase the value of the products and the business as well. According to predictions made by experts, if applied efficiently, AI can increase the value of not only commodities but also a firm itself. Thus the prediction for the world economy of growth is the gross value added by 2035 might come to pass. The graph below shows growth in all the industries worldwide:

The efficient application of AI will definitely result in positive results for firms and corporations not only in terms of profits but also in the reduction of costs and increases in quality and quantity. AI continues to grow and expand showing no signs of slowing down. The hesitation of majority of firms may result in them lagging behind and in the end becoming extinct. AI is the future. It is only proper for corporations intending to be participants in that time to invest in it.

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