Artificial intelligence (AI) enter companies en masse by the end of this decade. However, unlike previous waves of new technology, which have primarily disrupted blue collar and service jobs, recent advances in AI will affect all management levels, from the C - suite to the front. Imagine an organization where AI automates the planning, allocation, and reporting of resources — taking administrative and time-consuming tasks off the shoulders of managers. Imagine what AI-assisted analytics, simulation, and hypothesis tests can do throughout the company for decision - making, strategy and innovation.
AI presents not only unprecedented value creation opportunities but also awful challenges for managers and managers. It will force them to reexamine their parts and to redefine the fundamental principles that guide their organizations at present. The division of labor is changing, and cooperation between people and machines is increasing. AI will put an end to the managerial work. There are resilience and readiness in the ranks. The manager of the next generation will develop judgment work. Follow the first strategy for people. Managers must begin experimenting with AI.
Now would be the right time for directors to start experimenting with AI and their organizations to learn from these experiences.
Background
Everyone from Vladimir Putin to Elon Musk seems to talk suddenly about artificial intelligence( AI) and how the market is likely to change– for better or worse. However, what does AI mean when one sets aside the hype and fears of killer robots like " Terminator?" What is it going actually to mean for corporations? How fast is it going to come?
When people talk about AI in 2018, what exactly do they mean? Artificial intelligence is a comprehensive term from 1956 and describes efforts to get computers to do things that previously only human beings could do. It often occurs in science fiction, but today's current euphoria is centered on a particular subfield of AI known as " machine learning," that includes teaching machines to do things by example– rather than, say, " expert systems," which rely on rules and knowledge distilled by human experts.
However, optimism is primarily predicated on a particular machine- learning procedure known as " deep learning," in which operating system algorithms of simple models of the human mind are taught to do simple things by demonstrating them very many examples. The simulations are known as, " Neural networks," have been around for a while, but " deep" networks are becoming ever more perfectly capable in recent decades, that are more refined and can be equipped to understand perhaps more slight differences.
In other words, Deep Learning is only one particular example of an AI subfield, but the excitement around this particular subfield stems from its ability to deal with a wide range of problems, from image recognition to language translation and speech transcription. The most basic questions about the nature of consciousness and intelligence are as impenetrable as ever.
Why has AI taken off abruptly over the last couple of years? The recent increase in AI is indeed the consequence of sustained advances in machine learning and, in particular, in deep learning. There are multiple reasons for it though. First, the Internet– and digitization more usually – has provided an enormous amount of data that can be used for training. Secondly, researchers have identified more efficient training algorithms for larger– " deeper" – neural networks. Secondly, researchers have identified more efficient training algorithms for larger– " deeper" – neural networks.
The significance of AI to the firm. The reason it is so necessary to look at AI regarding business use is that it is possible that over the next 15 years it will likely rewrite entire industries. Business researchers often do not reach a consensus. However, the one thing they always seem to concur upon is that AI and machine learning could modify the way things are done in the decades ahead. By either automation or increase, it seems clear that AI will improve " work" and indeed it knows it, and as the Internet 20 years ago, AI is a technology factor that must be on the radar of businessmen.
People with a basic knowledge of AI will not be surprised to learn that artificial intelligence applications were not necessarily new in 2010. AI's first push into the world of business (famous through so-called " expert systems ") began in the 1980s and consisted primarily of hard-coding human intelligence into rules and steps. One has to look at the most profitable businesses of today to understand the depth to which AI and machine learning have crept into the lives of the people. Amazon, Facebook, Netflix, and Google, are the leaders in their segment, only because they happen to understand the value of AI and have managed to integrate it wonderfully into the mainstream day to day management of affairs.
The majority of AI applications in the company are little more than " pilots." In particular, vendor companies that sell artificial intelligence marketing solutions, healthcare solutions and financing solutions are merely trying things out.
Machine vision impact on AI. Machine learning and AI are limited by the fact that we are slow in the first place when we enter data as humans and make mistakes. The capture of data through image analysis and cameras is one of the fastest growing technologies. What prevents firms from adopting this concept of machine vision? Probably there are two things. One is a talent — people who can use image analysis in a useful way in business; people who can translate it into actionable, tangible results. The second problem is, how does one link these types of proposals to an existing business model that doesn't work that way?
There have been many alarms about the potential for artificial intelligence( AI) technologies to increase the workforce, particularly for easy- to- automate jobs. However, managers at all levels need to adapt to the smart machine world. The fact is that artificial intelligence will soon be able to perform administrative tasks that consume a lot of managers ' time more quickly, better and at a lower price. Managers spend more than half of their time on administrative coordination and control tasks at all levels. These are the very responsibilities which AI is most affected by the same managers. Moreover, they are right: AI automates many of these tasks.
Machine learning and AI allows people to focus on other essential tasks and save their time as it carries out the relatively menial jobs by itself. Thus, many managers now prefer using AI to write their articles or draw graphs or tables, which in return allows them to control better and reporting functions of the management. (Harris)
Many verdicts necessitate insight beyond what artificial intelligence alone can compress data. Managers use their knowledge of the history and culture of the organization, as well as empathy and ethics. This is the essence of human judgment— the use of expertise and experience in critical business decisions and practices. Managers feel a shift in this direction and identify the judgment- oriented skills of creative thinking and experimentation, data analysis and interpretation and strategic development as three of the four top new skills to succeed in the future.
Managers who see AI as a kind of colleague will recognize that there is no need to " race against a machine." Although human judgment is unlikely to be automated, intelligent machines can significantly contribute to this type of work, supporting decision- making and data-driven simulations as well as search and discovery. Managers believe that they will rely on the advice of smart systems to make future business decisions (Seewooruttun).
Kensho Technologies, an investment analysis provider for the next generation, is a company that tries to address these opportunities. Its system allows investment managers to ask questions in plain English, such as " What sectors and industries do best three months before and after a rate increase? " And within minutes, to receive answers. Illustrate how such technologies can help managers evaluate the impact of decisions and explore scenarios. AI will not only increase managers ' work but also enable managers to interact in collegial ways, through conversation or other intuitive interfaces with smart machines. At all times, AI will be their assistant and advisor.
While managers ' creative skills are vital, their ability to harness the creativity of others is perhaps even more important. Managers and designers combine various ideas in integrated, workable and attractive solutions. They embed design into their teams and organizations ' practices. Managers acknowledged the value of justice. However, they underestimate the profound social skills that are critical for networking, coaching, and cooperation, which will aid them to stand out in a world where AI carries out many of the administrative and analytical tasks that they carry out.
Problem Identification
Although artificial intelligence improves our world dramatically in many ways, there are considerable concerns about A.I 's future impact on jobs and the workforce (O'Sullivan). In the coming decades, there are predictions about millions of unemployed people, mainly due to the impact of Intelligent Automation and A.I. Systems. In any event, the whole socioeconomic system is entering a phase of accelerating transformation: markets, enterprises, education, government, social welfare, and employment models are severely affected.
Tasks, roles, and jobs at risk: Tasks that are monotonous can easily be automated, making specific roles obsolete gradually. For example, tasks and activities related to the operation of customer care/call centers, classification of documents, discovery, and retrieval, content moderation are increasingly based on technology and automation and fewer people. The same applies to the operation and support of production lines and factories: people are replaced by intelligent robots that can safely navigate the space, find and move objects (such as products, parts or tools) or perform complex assembly operations.
AI proves to be very efficient in handling even more complex activities— those that require multiple signals, data streams and acquired knowledge processing in real time. A unique case is that autonomous vehicles can capture and ' understand ' the environment and its dynamics; they can ' see,' decide and act in real time to achieve clear optimization goals.
Sectors that are directly affected include transport, E-commerce, legal professionals, financial services, accountants, insurance, to name a few. A well accomplished A.I. System can comprehend client requirements in accepted language, identify the aforementioned or implied entities (e.g. the product or service to which the request refers); estimate the customer's intention early enough (e.g. to activate a service or request assistance); process large volumes of data instantly and apply corporate policy to identify the best action/decision for them.
Alternatives
In the long term, we will see specific roles and jobs becoming less relevant and ultimately outdated. In most cases, however, artificial intelligence will have a supportive role for human beings — enabling the human factor to manage better complex and critical situations that require judgment and creative thought. At the same time, many new roles and specialties are focusing on technology and science. For example, highly qualified professionals will need to supervise or manage or coordinate the training of sophisticated artificial intelligence systems to ensure their integrity, safety, objectivity, and proper utilization (Dutton).
The Automation Revolution will usher in a new evolving economy, inventiveness and well- being under certain assumptions and after the initial disruption due to technological unemployment. Human beings no longer need routine, limited value, jobs. The labor force and the employment models underlying it will move from long-term, full - time employment agreements to flexible, selective premium services.
The positive scenario mentioned above requires a common understanding of the technology, its opportunities, and its risks. Companies must adapt to the new technological landscape, become more flexible and have lifelong learning, collaboration, innovation, and entrepreneurship attitude. States need a new education strategy; they need to rethink how markets, enterprises, and employment agreements should function in the new era of intelligent automation; they need to redesign social mechanisms to cover a variety of new scenarios and situations.
We need a robust framework at an even higher level to avoid the unbalanced concentration of technology power and control.
Early AI technologies and the ongoing AI revolution are forcing organizations to reassess numerous strategies that have been established. Instead of appointing perhaps the most suitable candidate for a given task, many multinationals now however primarily focus on improving fitness and adaptability, knowing that individual roles must evolve in conjunction with the implementation of AI. The notion that we are going to create a near perfect, impartial AI is a utopian but unreal paradigm. The difficulty is that although an AI is a blank canvas, it learns from people of a civilization that does have preconceptions and prejudices, like letters passing through a rock.
Training on- the- the job has become more important for making the transition people into better roles as new methods are developed. The purpose of HR is gradually moving away from its core monitoring and recruitment and training function that can be done more competently using Big Data and AI software, to a more significant commitment to improving actual staff experience in an increasingly contingent workforce. The integration of relatively early artificial intelligence techniques also leads to much more participatory and team-oriented entities than traditional hierarchical structures.
As AI becomes more advanced, representatives will ultimately have to determine where and when to justify staying, which chores are ideally suited for machines and which can be achieved most competently by combining the two. We all see the title: robots and AI are going to destroy jobs. This is more fiction than fact. AI encourages a gradual evolution in the labor market that will be positive with the right preparation. People will still work, but with the help of AI, they will work better. In the workforce of the future, the unparalleled combination of man and machine becomes a new normal.
The growth of AI in our society will improve our lifestyle and make businesses more efficient. Some of the everyday tasks, for example answering emails and entering data, are carried out by intelligent assistants. Smart homes will also reduce energy consumption and provide better security, marketing will be more focused, and better health care will be offered through better diagnosis (Fekety).
AI is a benefit to society because machines can become more intelligent and efficient over time. Also, computers are not predisposed to the same likelihood of error as humans. From an energy point of view, AI can be used to analyze and historical research data on how to distribute energy loads most efficiently from a grid perspective.
There are numerous advantages that a user gains by deploying AI and machine learning in their business. The advancements in this field allow the corporations to focus on more critical tasks and free up the time of their employees to focus on inventiveness and working on ideas that otherwise seemed far-fetched or could not be a part of their busy schedule and lives (Reddy).
Moreover, by adopting AI in daily life, the businesses would save time and money by automating routine processes and tasks, enhancing productivity and operational efficiency, making faster business decisions based on cognitive technology outputs to avoid errors and ' human errors,' provided that intelligent systems are correctly set up to predict and better offer customer preferences. Personalized experience mines massive amounts of data to generate quality leads and increase the cost savings of one’s customers base. By optimizing one's business, the employees or the products, one themselves increases revenue by identifying and maximizing sales opportunities, increasing expertise by evaluating and delivering smart advice and assistance. (Writer)
Computerized methods of reasoning, learning and perception have become a familiar everyday phenomenon. We have got to help our lady Siri or Cortana out. We are also on the road with GPS for long drives and excursions. The smartphone is an illustration of how we use artificial intelligence in apt and routine tasks. In utilities, we discovered that they could forecast what we will type and correct human spelling errors. This is workplace machine intelligence.
However, on paper, the deployment of AI for day to day transactions seems fantastic, with the everything that comes into existence, there is permanently the anxiety of making it work in the real-time world. Numerous things can and will go wrong once AI becomes a part of the human life and governs how the organizations conduct their dealings. The costs of upkeep and repair are one of the main downsides of artificial intelligence. Programmes must be restructured to encounter the varying requirements and machines must be made more intelligent. In the instance of an interruption, the restoration costs can be very high. Missing code or data recovery actions can be time-consuming and expensive (Forbes Technology Council).
It is believed that intelligence is a gift of nature. There remains an ethical argument about whether or not human intelligence should be imitated. Thus, the inquiry that is always on the mind of some people is whether AI will replace what the humans do and whether or not will that lead to a decrease in the number of jobs, in an already scarce job market, for the humans. As we know, machines perform routine and repeatable tasks far better than human beings. Also, technologies are used as an alternative to humans, to increase their cost-effectiveness in companies. If machines start substituting people in all areas, they sooner or later lead to redundancy. There will be not anything left for people to do. There will be so much empty time, that it will have a damaging use. Thinking machines oversee all fields and hold the positions of people, leaving thousands of individuals jobless. (Martin)
Ethics and moral values are an essential concern in the application of artificial intelligence. Is it ethically accurate to produce human replicas? Is it possible for our moral values to recreate intelligence? Intelligence is nature's gift. It might not be right to install it in a machine to help us. Also, because of the reduced need to use people's intelligence, lateral thinking and multi-tasking skills can be reduced. With so much help from machines, if people do not have to use their thinking skills, these skills will gradually decrease. When artificial intelligence is heavily applied, people can become overly dependent on machines and lose their mental capacity.
The idea of machines that replace people sounds fantastic. However, is it exciting to think that it will save us all from the pain? Ideas such as working wholeheartedly, with a sense of belonging and dedication in the world of artificial intelligence do not exist. Imagine hospital robots working. Do you imagine them showing people 's care and concern? You think that online assistants (avatars) can provide the kind of service that a person would provide? Concepts like care, understanding, and unity cannot be understood by machines, which is why they always lack the human touch, how intelligent they become (Wilson, Daugherty and Morini-Bianzino).
In addition to all these disadvantages of AI, there is a fear that robots will supersede people. Ideally, people should remain the masters of machines. However, if things turn around the other way, the world becomes chaos. Smart machines can be smarter than we are, they can enslave us and begin to rule the world. Artificial intelligence should be understood to have several advantages, but it also has its disadvantages. Before using it for human convenience, its benefits and risks should be carefully weighed. Alternatively, man can destroy himself in the greed to play God.
Recommendations
So far, we have come across the pros and cons of using AI in the business world, but how does one exactly go about to make sure that their ideas and approaches are executed in a style that is not only efficient but cost effective as well (Institute). We know, that using AI to conduct day to day business is not a cheap task, however, there are always some means to an end. So how does one exactly come to these methods? (Kolbjørnsrud, Amico and Thomas)
Currently, the managers are facing a shortage of true analytical talent, a field that is bound to be overtaken by AI in the coming years. In such a situation it becomes necessary for the leaders to ensure that they as well as their organization is well equipped to handle the human part of this area when the AI takes over (Rosenberg). To achieve this, the managers must take some steps including, starting early. Managers must carry out tests with AI and employ their intuitions to the next experiment cycle in order to navigate in an uncertain future.
Adopt new critical indicators of performance to drive adoption. AI will bring new success criteria: collaboration, information sharing, experimentation, learning, and decision- making efficiency and the ability to exceed the organization's insights. Develop creativity, collaboration, empathy and judgment training, and recruitment strategies. Leaders should cultivate an assorted workforce and team of managers who balance their experience with creative and social intelligence, complementing each other in order to support the sound collective judgment. (Joshi, Stewart and Shapiro)
Before releasing an AI system, companies should carry out rigorous pre-release tests to ensure that they do not amplify bias and errors due to training data, algorithms or other system design elements. Since this is a promptly changing field, the methods and assumptions by which these tests are conducted, together with the results, should be openly documented and publicly available, with clear versions for updates and new findings. Companies should continue to monitor their use in different contexts and communities after the introduction of an AI system. The monitoring methods and results should be defined by open, academically rigorous processes and accountable to the public. The opinions and perspectives of traditionally marginalized societies must be prioritized, particularly in high- stakes policymaking contexts.
More research and policy-making on the use of AI systems in the management and monitoring of workplaces, including recruitment and HR. This research complements the current focus on the replacement of workers through automation. Specific attention should be paid to the potential impact on labor rights and practices and in particular to the potential for behavioral manipulation and the unintentional strengthening of recruitment and promotion bias.
Develop standards to track the origin, development, and use of data sets during their entire life cycle. This is necessary to understand better and monitor bias and skew issues. In addition to creating better records for the creation and maintenance of a training dataset, social scientists and estimation experts in the area of AI bias studies should closely monitor existing training data sources and continue working to comprehend potential blind spots and preconceptions that might very well be at work.
New senior management and transparency structures must also follow ethical codes targeted at propelling the AI area. More work is required on how vital ethical and moral principles and procedures for good practice can be substantially related to common development methods, promotion and product launch cycles.
Implementation Ideas
Thus, so far in this paper, numerous issues that can arise due to the usage of AI by the corporations to reduce the workload of their employees, as well to create a system that allows them to work on hiring and economic issues, and work on future predictions have been discussed. Throughout this paper, the one theme that has been constant is the fact that, no matter how much the managers, as well as the employees, want to deny it, AI will overtake the humans in many fields. Which will then led to developing new career paths that will allow them to utilize the resources at their disposal to make themselves more efficient? However, while putting a plan into motion, there are some things need to be considered before acting upon it. These factors include recommendations of all of those who are actively involved in the implementation process as well as those who will face the direct impact of said changes in their lives.
Companies will require access to financing and value chains for larger organizations to which they can provide data and services based on AI. AI requires substantial financial investment to develop core technologies and applications; Big Data to train and develop machine intelligence, and a variety of talents to equip smart technology with human cognition and empathy. Combinations of technologies, multiple data and interdisciplinary skills — these do not have a single player. Smaller companies may be at a handicap, in particular regarding data access.
In addition to supporting innovation ecosystems by governments, there are additional challenges for sustainable growth in AI that policymakers can help tackle. Responsible AI to describe five principles that help to foster trust and deal with unintended consequences, unintended bias and the challenges of compliance. Honesty, transparency, fairness, accountability and human centricity are the following principles. These elements are essential for the protection of employees, customers and citizens ' interests and confidence.
Although AI has been a part of the economic and the business ecosystem for quite some time now, it is of recent advancements in the field of big data and related technology that it has become more commonplace. However, it is not something that has happened overnight. Years of planning and execution have been put to work, to make sure that something like this exists in the future. The immediate goal of adopting AI is to ensure that people are not misguided anyhow and keep it in their minds, that it is their use of technology that will determine the way it reacts. One has to be careful while supplying information to it because the output cannot be controlled, but the input can be managed.
Similarly, the short-term goals associated with it to make it less expensive to use and more accessible and commonplace, so that the small businesses do not lose out to the large corporations in the race to become the best in this field. Moreover, it needs to be created in a language that can be understood by the common man and not by just sure technological experts. Creating an easily accessible technology at the relatively low cost is the short-term goal.
The long-term problems that will arise will be due to the safety and security of the data that is being handed to the AI currently. To ensure that the AI future ready, large volumes of data is being fed to it, without a thought about the safety and security of the same. It is no surprise that of late the newspapers are filled with articles on the acts of data breach and identity theft. The companies rushing to win this race have forgotten that they need to put in place adequate safety measures so that the consumers do not feel threatened and do not have to risk any data loss or personal information. Security and moral values of the AI are the few sectors that will require continuous work, both short-term as well as long-term.
Depending on our decisions as a community, we can move towards a more beautiful future with economic stability, leisure, and creativity— or economic/social unrest and robot upheavals. The idea that the integration of AI with business is the future of this industry goes to show further that we are gradually becoming a part of a society that is mostly dependent on technology to carry out tasks. Before AI become the mainstream, the whole idea was to make human lives relatively easier and make data tracking comfortable. However, the growth with technology allows the humans to incorporate AI in the day to day tasks while making sure that none of their values are compromised.
AI will come across as an idea that may hurt the jobs because of many people with high caliber are a part of mundane tasks. Once AI overtakes these jobs, the humans will be able to devote adequate time and energy in creating ideas and tools that will further improve the quality of their life. The progress in this field is nothing to be afraid of; preferably it is something to embrace and work with, as it has been created to help us and make our lives more comfortable and reach the heights of human potential, which in turn will allow them to help those who seek them out.
References
Dutton, Tim. "An Overview of National AI Strategies." 29 June 2018. medium.com. 10 November 2018.
Fekety, Mike. "Pros and Cons of Artificial Intelligence." 12 August 2015. linkedin.com. 11 November 2018.
Forbes Technology Council. "14 Ways AI Will Benefit Or Harm Society." 1 March 2018. www.forbes.com. 11 November 2018.
Harris, Micheal. "Impact Of Artificial Intelligence And Machine Learning on Trading And Investing." 27 July 2017. towardsdatascience.com. 10 November 2018.
Institute, AI Now. "The 10 Top Recommendations for the AI Field in 2017." 19 October 2017. medium.com. 10 November 2018.
Joshi, Bhautik, Kristen Stewart and David Shapiro. "Bringing Impressionism to Life with Neural Style Transfer in Come Swim." Cornell University Library (2017).
Kolbjørnsrud, Vegard, Richard Amico and Robert J. Thomas. "How Artificial Intelligence Will Redefine Management." Harvard Business Review (2016).
Martin, Alan. "5 problems artificial intelligence needs to overcome for all our sakes." 6 March 2017. www.alphr.com/.
11 November 2018.
O'Sullivan, Andy. "The AI solution you’re building might cost people their jobs. Here’s why you should care." 18 March 2018. medium.freecodecamp.org. 11 November 2018.
Reddy, Krishna. "Advantages and Disadvantages of Artificial Intelligence." n.d. content.wisestep.com. 11 November 2018.
Rosenberg, Seth. "The human cost — and potential profit — of AI." 8 December 2016. venturebeat.com. 11 November 2018.
Seewooruttun, Gavin. "If a company is a coalition of people brought together to do something better, cheaper and/or faster, what happens when Artificial Intelligence (AI) can replicate what employees do? What will this mean for an organization’s future?" 2 July 2018. consulting.ey.com.
11 November 2018.
Wilson, H. James, Paul R. Daugherty and Nicola Morini-Bianzino. "The Jobs That Artificial Intelligence Will Create." September 2017. sloanreview.mit.edu. 10 Novmeber 2018.
Writer. "Artificial intelligence in business." 2017. www.nibusinessinfo.co.uk/. 11 November 2018.
