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Artificial Intelligence in Business Management is a review of artificial intelligence (AI) applications in businesses. This book adopts a cross-disciplinary strategy toward AI adoption. Book chapters explore many projects that go beyond simple data management and accessibility to showcase the growing role of artificial intelligence and machine learning in the enterprise data space. AI methods for tackling marketing and commercial strategies, as well as the use of AI and machine learning in tourism, insurance and healthcare systems, are discussed. A study on the significance of cultural assets in evaluating risks and protection is also presented. The content gives valuable insights on the application and implications of artificial intelligence and machine learning from this book to readers aiming for corporate roles, such as directors, executives, senior software developers, and digital transformation managers.
The book is an essential resource for researchers and professionals in business, economics, and allied disciplines.
Readership
Researchers and professionals in business, economics and allied disciplines.
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Seitenzahl: 260
Veröffentlichungsjahr: 2024
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The world is in the era of digital transformation, which is affecting society and businesses alike. One of the major enablers of recent times is artificial intelligence (AI). This book is for business managers/owners and workforces who are looking to understand how the use of AI transforms the business sector. Most people have at least one encounter with AI every day. There are many ways in which AI can be applied to the management of businesses, including the enhancement of control operations, the reduction of complexity in decision-making, the eradication of human error, the simplification of work procedures, and the consolidation of business data. As AI improves and becomes more widespread in our daily lives, the stigma that it is only seen in scientific fiction dystopias is beginning to fade. Hence, the author’s goal for writing this book is to provide business leaders the knowledge on how to apply artificial intelligence in managing their businesses. Artificial intelligence is often considered a supporting tool rather than an alternative to human intellect and innovation. By the end of the book, readers will have a firm grasp of AI progress and the part it plays in boosting operations across industries. Managers can then devise a plan to help workers acquire new skills and adjust to the changing nature of their jobs as a result of AI evaluations. Therefore, it is crucial to evaluate this technology with an eye toward its potential advantages, practical uses, and room for future development.
The goal of this book is to provide business leaders the knowledge on how to apply artificial intelligence in managing their businesses. As a result of AI's success as a key marketing weapon, it has quickly become one of the business sector's most fashionable catchphrases. Artificial intelligence has been around for many years, but its current renaissance can be ascribed to the proliferation of large data, the decrease in cost of computing power, and the advancements in general technology. This book adopts a cross-disciplinary strategy toward the use of AI by serving as a unified resource for students and practitioners in the fields of business, economics, and other related fields. Corporate executives, directors/managers, software developers, and those who implement AI can gain valuable insights into the application and implications of artificial intelligence and machine learning from this book. The subject matter of this book explores many projects that go beyond simple data management and accessibility to showcase the growing role of artificial intelligence and machine learning in the enterprise data space. Spatial methods for tackling marketing and commercial strategies, as well as insurance and healthcare systems, are discussed, and the significance of cultural assets is investigated for the sake of evaluating risks and protection.
Over the course of the next few decades, AI will permeate every industry on the planet. Improvements in the AI environment are reflected in recent tendencies in AI-driven robotics. Changes in how businesses view, use, and invest in artificial intelligence are a clear indication of this shift. Businesses may want to consider using AI marketing to produce leads and conversions because of the clear advantages it delivers, such as having complete, transparent, accurate, pertinent, constant and fast data. The AI-generated programs will, more or less, supply the information essential to expanding marketing activities. Now that AI is more readily available, many businesses are using it in their advertising campaigns. There are many ways in which artificial intelligence might improve marketing and advertising, and businesses that embrace AI-driven strategies will undoubtedly see increased success. In order to strengthen customer relationships and accomplish marketing objectives, businesses can benefit from using AI to customize content, improve campaigns, and enrich the consumer experience.
The use of artificial intelligence (AI) is revolutionizing several sectors of the economy. Increasing processing power, decreasing computational expenses, the easy accessibility of large data, and the development of predictive techniques and models have all contributed to the rise of AI in marketing. Artificial intelligence (AI) is being widely used in several fields of marketing today [1] and this trend is expected to continue. Businesses may save time and effort by using AI to automate routine tasks. Gathering information, analysis, and further assessments of consumer or economic developments that may affect marketing efforts all feed into the automated judgments made by AI marketing. Artificial intelligence is widely utilised in the fast-paced world of digital marketing. The goal of artificial intelligence marketing (AI Marketing) is to enhance the customer experience by predicting your customers' next steps based on historical data and applying AI concepts like machine learning. Retail businesses and marketers can reap significant benefits from incorporating AI into their operations. With the help of AI, online shopping has surpassed brick-and-mortar stores and has become an integral part of the growing digital revolution [1] meeting consumers' urgent
requirements and providing them with greater convenience. In marketing, AI is utilized to make suggestions for handling customer interactions. Artificial intelligence (AI) may develop a profile for each consumer by combining numerous data sources and systems, helping businesses better understand their customers and their motivations for making decisions.
Finance, as well as government, medical care, recreation, retail, and other sectors all use AI in their marketing efforts. Campaign success, client satisfaction, and the effectiveness of advertising activities are only a few of the results that can be achieved through various use cases. Marketers are utilizing AI to solve a number of problems with programmatic marketing. Bidding on real-time ad space that is relevant to target viewers is facilitated by ML on programmatic marketplaces. There's some speculation that AI could help streamline marketing processes by cutting down on human error [2]. Artificial intelligence (AI) is defined as the practice of programming a computer to perform activities normally requiring human intelligence and emotional, cognitive, and physical faculties. Instead of seeing AI as a single, monolithic intelligence, the “AI intelligence view” takes into account the fact that, like humans, AI can be programmed to have specialized intelligence for various purposes. Mechanical, cognitive, and emotional AI intelligences are ranked in order of increasing difficulty for AI to address them [3]. Artificial intelligence (AI) describes computer-based devices that can learn, reason, and carry out activities just like humans. Simply said, AI-powered tools have the capacity to carry out operations that would ordinarily need human intelligence, such as problem-solving, data analysis, and decision-making. Absolutely, Marketers have already embraced AI in a wide variety of applications, including chatbots that provide 24/7 customer care, AI-powered sentiment analysis tools used to monitor social media feeds, robust data analysis tools, and highly targeted content production. Hyper-personalization and pinpoint targeting are two areas where AI is making a significant impact in marketing and advertising campaigns [4]. Firms can better target campaigns and develop more relevant, engaging content across social media posts, subject lines, and blogs with the help of AI algorithms that analyze data to learn about our customers' behavior and preferences.
BD is actually a rather simple concept which means a marketer can collect and organize lots of data with little effort. This information can then be used by marketing teams to send the most relevant message to the most relevant person at the most relevant time via the most relevant channel. According to Dekimpe [5], retailers can utilize big data to fine-tune dynamic best response pricing algorithms that take into account customer preferences, competitive moves, and supply parameters.
When trying to make sense of this massive data warehouse, marketers might benefit from machine learning tools. Marketers can learn more about the causes and probabilities of specific activities by using these tools to spot trends or common occurrences and make accurate predictions about common insights, responses, and reactions. A subfield of artificial intelligence, machine learning allows computers to teach themselves new skills by analyzing large amounts of previously collected data. However, machine learning can only draw inferences from the data that has previously been given to it; it cannot produce new information or ideas on its own; it can only identify patterns in the data.
Digital advertising platforms powered by AI have human-level comprehension. This means that the platforms can rapidly and accurately discover meaningful patterns and correlations in massive data volumes. The ability of AI systems to read free-form information like social media posts, natural language, and email responses is based on their ability to interpret emotion and communication in the same way that humans do.
The tools for artificial intelligence remain in their infancy. As a result, many marketing departments might not know how to effectively implement AI marketing even if they need it. Marketers face new complications as a result of implementing these solutions. The following difficulties with AI marketing have been raised by Tjepkema [2]. There could be downsides to employing AI in marketing as well as advertising, but there could be downsides to using any technology.
It's crucial that when marketing teams launch AI implementations they have a firm grasp on implementation guidelines for the particular solution they intend to apply. Teams will need dedicated training time and communication with implementation specialists.
It's possible that stakeholders will not see the potential benefits of investing in AI. The marketing department needs a way to quantify the benefits of AI investments, particularly with regards to the quality of the customer experience and the company's public image.
The biggest difficulty is how ethical it is. There are concerns from some people that this practice raises ethical concerns, such as invasion of privacy and dubious data collection. However, digital marketers still regard AI-led marketing as vital, especially in driving growth [6]. They address moral issues by being open and honest about the data they collect, using technology solely for the benefit of their clients, making sure all marketing practices are compliant with human rights and encouraging diversity and inclusion.
The danger of becoming too reliant on technology is another possible consequence of using AI in advertising and marketing. While artificial intelligence (AI) can help businesses automate numerous activities and make better judgments, it shouldn't be used to replace human intuition and creativity [7] in the workplace. In order to get the best results, businesses should leverage AI but also incorporate human insight.
Efficient budgeting is essential for every company, and some have speculated that AI-powered marketing calls for substantial investments. It could be expensive for businesses to adopt this strategy because of the need to automate procedures associated with the customer journey and enhance user experiences generally [6].
There is some hesitance among businesses and entrepreneurs to fully embrace AI marketing, despite its many benefits. Concerns have been raised about the possible misuse of data and the development of programmable weaponry. It's also concerning that so much private information is being gathered and examined. Identity theft and information leaks are concerns for many people. Thankfully, steps are being taken to restore confidence [6].
For an artificial intelligence-driven marketing strategy to be effective, a robust IT backbone is essential. Artificial intelligence generates massive amounts of data. Strong equipment is needed for this purpose. The initial investment and ongoing upkeep of these computer systems can be very high. Furthermore, they will require frequent updates and maintenance to ensure optimal performance [8]. This is a significant barrier, especially for smaller businesses whose IT budgets are already tight.
In order to avoid severe fines, businesses must adhere to data privacy legislation such as GDPR and CCPA. This means that marketers must use data in a responsible manner. These regulations pose a danger to AI implementations because of the potential for non-compliance with data privacy laws if tools are not properly developed to adhere to these requirements. Adherence to privacy standards is complementary to the use of AI in marketing. Businesses need to understand where they may and cannot go in terms of sharing customer information. Companies using AI-driven marketing should adhere to regulatory authorities to avoid this danger, damage to their brand, and potential fines. The security measures that have been put in place over the years have made it such that consumers no longer have to be concerned about having their rights violated. Offsite data storage is prohibited by regulators as well. In this day and age, privacy is a major issue. There's a chance that as AI learns more about consumers and their habits, such knowledge could be exploited or compromised. There is also the risk of discriminating outcomes due to prejudice in the data or algorithms employed in AI [7] that could be avoided. Businesses can lessen their exposure by taking measures to improve the openness, ethics, and safety of their AI systems. This involves giving users access to their data and being forthright about what information is being gathered and how it will be used. Businesses should also check their AI systems for bias on a regular basis and take corrective action if necessary.
Finding the correct skills and people to handle and execute AI marketing is an issue because of its complexity and technological requirements. AI-related tools and software necessitate a specialized skill set due to the complexity of the algorithms used and the amount of computer power required [6]. Before implementing AI, companies should assess their current staffing levels and determine whether or not they can outsource certain positions. Third-party providers can assist with data collection, analysis, and maintenance, as well as provide the necessary AI training programs for personnel interested in Artificial Intelligence and data science through partnerships.
Artificial intelligence (AI) relies on accurate information. If organizations provide poor-quality data into an AI system, the system will return poor-quality outcomes. In an ever-changing big data landscape, businesses are amassing massive amounts of information. The problem is that this data is not always reliable. The resources available to back up a successful AI marketing strategy are either inadequate or lacking. These issues with data in AI marketing prevent businesses from fully leveraging big data [8]. Companies must always double check that the information they are using is reliable. Otherwise, businesses would suffer from subpar AI results, reducing the overall efficacy of their AI-driven advertising campaigns.
Data collecting is the primary use case for AI in business. The data gathered by AI helps companies better understand their customers and focus their efforts on what matters most to them. Through the analysis of the large amounts of internet content available via social media, blogs, and other channels, AI gives access to information about foreign markets. Using the billions of data points collected by AI systems, marketers can quickly and effectively develop customer personas. Some examples include face-to-face meetings, regional discounts, repeat customers, communications from satisfied customers, and word-of-mouth advertising. It is from this vantage point that efficient client segmentation may be achieved. To better match customers with products they are likely to buy and to avoid pushing irrelevant or out-of-stock products to customers, marketers can more precisely determine which customers should be targeted and included or excluded from the campaign.
Because AI may help businesses anticipate what their customers will buy, adopting the technology should significantly enhance the predictive capacity of the organization. Advertising and marketing are also seeing success with another AI application: predictive analytics. This entails analyzing client data with machine learning algorithms to foretell their future actions, such as which products they will buy or which channels they will frequent. These details can be used to enhance marketing initiatives and strengthen relationships with existing customers [7]. Depending on the precision of their forecasts, businesses may restructure how they operate fundamentally to meet the evolving demands of their customers. This opens up a wide range of possible avenues for investigation into the interplay between marketing techniques and consumer preferences. Predicting what customers want to buy, what price to charge, and whether price discounts should be made are all areas where AI is predicted to play a significant role [9]. Guha et al. [10] noted that price and price promotions can have a significant impact on sales, making this an essential subject of study for marketing scholars. Therefore, the application of AI to determine the ideal prices to charge and whether or not discounts should be granted is a key topic for future study. Artificial intelligence-based software can analyze large data sets, compile this information, and generate precise predictions based on observable patterns. Marketers can now use the constantly evolving data they acquire to foresee potential outcomes. Following market optimization, this study will enable more timely and accurate customisation of metrics and improved product and service promotion. A successful marketing campaign also requires an understanding of the market's potential and an analysis of the competition. Market predictive analytics entails monitoring the competition's website, forums, and other online presences for real-time alterations and upgrades. Using AI, businesses can provide each consumer with tailored content and promotions as well as superior service.
Understanding consumer habits is essential for the retail and packaged goods businesses in order to optimize supply and revenue. By analyzing massive amounts of data, identifying patterns, and providing buyers with personalized recommendations, machine learning (ML) can help organizations gain insight into customer spending habits [11].
Using the customer's previous conduct and psychological features, AI uses statistical techniques and computer software to predict the customer's next move. To better understand how people shop, AI customer behavior Analytics employs a wide range of model behaviors. With this information, businesses may better anticipate their consumers' actions and adapt to their changing needs [1] and manage their clientele accordingly. This helps the business anticipate client needs and keep an eye on profit, sensitivity, compliance, and other risk factors. Therefore, industry developments can be forecasted in advance by merging AI in digital marketing with machine learning statistics.
Ads on Google, Facebook, and Instagram, for example, can now be targeted to specific demographics and interests, and this opens up countless possibilities for organizations using AI in digital marketing. These platforms evaluate user data like gender, age, interests, demographics, and more to tailor their services to each user [1